Alternatives to Microsoft Agent Framework
Compare Microsoft Agent Framework alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Microsoft Agent Framework in 2026. Compare features, ratings, user reviews, pricing, and more from Microsoft Agent Framework competitors and alternatives in order to make an informed decision for your business.
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Gemini Enterprise Agent Platform is a comprehensive solution from Google Cloud designed to help organizations build, scale, govern, and optimize AI agents. It represents the evolution of Vertex AI, combining advanced model development with new capabilities for agent orchestration and integration. The platform provides access to over 200 leading AI models, including Google’s Gemini series and third-party options like Anthropic’s Claude. It enables teams to create intelligent agents using both low-code and code-first development environments. With features like Agent Runtime and Memory Bank, businesses can deploy long-running agents that retain context and perform complex workflows. The platform emphasizes security and governance through tools like Agent Identity, Agent Registry, and Agent Gateway. It also includes optimization tools such as simulation, evaluation, and observability to ensure consistent agent performance.
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Claude Code
Anthropic
Claude Code is an AI-powered coding agent designed to work directly inside your existing development environment. It goes beyond simple autocomplete by understanding entire codebases and helping developers build, debug, refactor, and ship features faster. Developers can interact with Claude Code from the terminal, IDEs, Slack, or the web, making it easy to stay in flow without switching tools. By describing tasks in natural language, users can let Claude handle code exploration, modifications, and explanations. Claude Code can analyze project structure, dependencies, and architecture to onboard developers quickly. It integrates with common command-line tools, version control systems, and testing workflows. This makes it a powerful companion for both individual developers and teams working on complex software projects.Starting Price: $20/month -
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Vercel
Vercel
Vercel is an AI-powered cloud platform that helps developers build, deploy, and scale high-performance web experiences with speed and security. It provides a unified set of tools, templates, and infrastructure designed to streamline development workflows from idea to global deployment. With support for modern frameworks like Next.js, Svelte, Vite, and Nuxt, teams can ship fast, responsive applications without managing complex backend operations. Vercel’s AI Cloud includes an AI Gateway, SDKs, workflow automation tools, and fluid compute, enabling developers to integrate large language models and advanced AI features effortlessly. The platform emphasizes instant global distribution, enabling deployments to become available worldwide immediately after a git push. Backed by strong security and performance optimizations, Vercel helps companies deliver personalized, reliable digital experiences at massive scale. -
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CrewAI
CrewAI
CrewAI is a leading multi-agent platform that enables organizations to streamline workflows across various industries by building and deploying automated processes using any Large Language Model (LLM) and cloud platform. It offers a comprehensive suite of tools, including a framework and UI Studio, to facilitate the rapid development of multi-agent automations, catering to both coding professionals and those seeking no-code solutions. The platform supports flexible deployment options, allowing users to move their created 'crews'—teams of AI agents—to production with confidence, utilizing powerful tools for different deployment types and autogenerated user interfaces. CrewAI also provides robust monitoring capabilities, enabling users to track the performance and progress of their AI agents on both simple and complex tasks. Additionally, it offers testing and training tools to continually enhance the efficiency and quality of outcomes produced by these AI agents. -
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AutoGen
Microsoft
An Open-Source Programming Framework for Agentic AI. AutoGen provides multi-agent conversation framework as a high-level abstraction. With this framework, one can conveniently build LLM workflows. AutoGen offers a collection of working systems spanning a wide range of applications from various domains and complexities. AutoGen supports enhanced LLM inference APIs, which can be used to improve inference performance and reduce cost.Starting Price: Free -
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Claude Agent SDK
Claude
The Claude Agent SDK is a developer toolkit that enables the creation of autonomous AI agents powered by Claude, allowing them to perform real-world tasks beyond simple text generation by interacting directly with files, systems, and tools. It provides the same underlying infrastructure used by Claude Code, including an agent loop, context management, and built-in tool execution, and is available for use in Python and TypeScript. With this SDK, developers can build agents that read and write files, execute shell commands, search the web, edit code, and automate complex workflows without needing to implement these capabilities from scratch. It maintains persistent context and state across interactions, enabling agents to operate continuously, reason through multi-step problems, take actions, verify results, and iterate until tasks are completed.Starting Price: Free -
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Agent Development Kit (ADK)
Google
The Agent Development Kit (ADK) is a flexible, open-source framework for building and deploying AI agents. It is tightly integrated with Google’s ecosystem, including Gemini models, and supports popular large language models (LLMs). ADK simplifies the development of both simple and complex AI agents, providing a structured environment for building dynamic workflows and multi-agent systems. With built-in tools for orchestration, deployment, and evaluation, ADK helps developers create scalable, modular AI solutions that can be easily deployed on platforms like Gemini Enterprise Agent Platform or Cloud Run.Starting Price: Free -
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Amazon Bedrock AgentCore
Amazon
Amazon Bedrock AgentCore enables you to deploy and operate highly capable AI agents securely at scale, offering infrastructure purpose‑built for dynamic agent workloads, powerful tools to enhance agents, and essential controls for real‑world deployment. It works with any framework and any foundation model in or outside of Amazon Bedrock, eliminating the undifferentiated heavy lifting of specialized infrastructure. AgentCore provides complete session isolation and industry‑leading support for long‑running workloads up to eight hours, with native integration to existing identity providers for seamless authentication and permission delegation. A gateway transforms APIs into agent‑ready tools with minimal code, and built‑in memory maintains context across interactions. Agents gain a secure browser runtime for complex web‑based workflows and a sandboxed code interpreter for tasks like generating visualizations.Starting Price: $0.0895 per vCPU-hour -
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Model Context Protocol (MCP)
Anthropic
Model Context Protocol (MCP) is an open protocol designed to standardize how applications provide context to large language models (LLMs). It acts as a universal connector, similar to a USB-C port, allowing LLMs to seamlessly integrate with various data sources and tools. MCP supports a client-server architecture, enabling programs (clients) to interact with lightweight servers that expose specific capabilities. With growing pre-built integrations and flexibility to switch between LLM vendors, MCP helps users build complex workflows and AI agents while ensuring secure data management within their infrastructure.Starting Price: Free -
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LangChain
LangChain
LangChain is a powerful, composable framework designed for building, running, and managing applications powered by large language models (LLMs). It offers an array of tools for creating context-aware, reasoning applications, allowing businesses to leverage their own data and APIs to enhance functionality. LangChain’s suite includes LangGraph for orchestrating agent-driven workflows, and LangSmith for agent observability and performance management. Whether you're building prototypes or scaling full applications, LangChain offers the flexibility and tools needed to optimize the LLM lifecycle, with seamless integrations and fault-tolerant scalability. -
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LangGraph
LangChain
Gain precision and control with LangGraph to build agents that reliably handle complex tasks. Build and scale agentic applications with LangGraph Platform. LangGraph's flexible framework supports diverse control flows – single agent, multi-agent, hierarchical, sequential – and robustly handles realistic, complex scenarios. Ensure reliability with easy-to-add moderation and quality loops that prevent agents from veering off course. Use LangGraph Platform to templatize your cognitive architecture so that tools, prompts, and models are easily configurable with LangGraph Platform Assistants. With built-in statefulness, LangGraph agents seamlessly collaborate with humans by writing drafts for review and awaiting approval before acting. Easily inspect the agent’s actions and "time-travel" to roll back and take a different action to correct course.Starting Price: Free -
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OpenAI Agents SDK
OpenAI
The OpenAI Agents SDK enables you to build agentic AI apps in a lightweight, easy-to-use package with very few abstractions. It's a production-ready upgrade of our previous experimentation for agents, Swarm. The Agents SDK has a very small set of primitives, agents, which are LLMs equipped with instructions and tools; handoffs, which allow agents to delegate to other agents for specific tasks; and guardrails, which enable the inputs to agents to be validated. In combination with Python, these primitives are powerful enough to express complex relationships between tools and agents, and allow you to build real-world applications without a steep learning curve. In addition, the SDK comes with built-in tracing that lets you visualize and debug your agentic flows, evaluate them, and even fine-tune models for your application.Starting Price: Free -
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PydanticAI
Pydantic
PydanticAI is a Python-based agent framework designed to simplify the development of production-grade applications using generative AI. Built by the team behind Pydantic, the framework integrates seamlessly with popular AI models such as OpenAI, Anthropic, Gemini, and others. It offers type-safe design, real-time debugging, and performance monitoring through Pydantic Logfire. PydanticAI also provides structured responses by leveraging Pydantic to validate model outputs, ensuring consistency. The framework includes a dependency injection system to support iterative development and testing, as well as the ability to stream LLM outputs for rapid validation. It is ideal for AI-driven projects that require flexible and efficient agent composition using standard Python best practices. We built PydanticAI with one simple aim: to bring that FastAPI feeling to GenAI app development.Starting Price: Free -
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Strands Agents
Strands Agents
Strands Agents is an open-source framework designed to help developers build controllable and flexible AI agents using Python and TypeScript. It enables users to create agents by defining tools as simple functions, eliminating the need for complex workflows or orchestration pipelines. The SDK works with any model and cloud provider, giving developers full freedom in how they deploy and scale their agents. It introduces a streamlined agent loop where the model handles reasoning while developers maintain control through code. Features like steering hooks allow developers to validate and guide agent behavior before and after actions are taken. The platform also includes built-in capabilities such as memory management, observability, and evaluation tools. Overall, Strands Agents SDK simplifies agent development while improving reliability, control, and performance.Starting Price: Free -
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Swarm
OpenAI
Swarm is an experimental, educational framework developed by OpenAI to explore ergonomic, lightweight multi-agent orchestration. It is designed to be scalable and highly customizable, making it suitable for scenarios involving a large number of independent capabilities and instructions that are challenging to encode into a single prompt. Swarm operates entirely on the client side and, like the Chat Completions API it utilizes, does not store state between calls. This stateless nature allows for the construction of scalable, real-world solutions without a steep learning curve. Swarm agents are distinct from assistants in the assistants API; they are named similarly for convenience but are otherwise completely unrelated. It includes examples demonstrating fundamentals such as setup, function calling, handoffs, and context variables, as well as more complex scenarios like a multi-agent setup for handling different customer service requests in an airline context.Starting Price: Free -
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Semantic Kernel
Microsoft
Semantic Kernel is a lightweight, open-source development kit that lets you easily build AI agents and integrate the latest AI models into your C#, Python, or Java codebase. It serves as an efficient middleware that enables rapid delivery of enterprise-grade solutions. Microsoft and other Fortune 500 companies are already leveraging Semantic Kernel because it’s flexible, modular, and observable. Backed with security-enhancing capabilities like telemetry support, hooks, and filters you’ll feel confident you’re delivering responsible AI solutions at scale. Version 1.0+ support across C#, Python, and Java means it’s reliable, and committed to nonbreaking changes. Any existing chat-based APIs are easily expanded to support additional modalities like voice and video. Semantic Kernel was designed to be future-proof, easily connecting your code to the latest AI models evolving with the technology as it advances.Starting Price: Free -
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Mastra
Mastra AI
Mastra is an open-source TypeScript framework for building, deploying, and managing AI agents and intelligent applications. The platform provides tools for developing autonomous agents, orchestrating multistep workflows, managing persistent memory, and integrating large language models with external services. Its agent framework supports configurable instructions, tool calling, structured outputs, and connections to thousands of AI models through a unified model router. Developers can create durable workflows with conditional branches, retries, human approval steps, and the ability to pause and resume long-running tasks. Mastra also includes agent observability, performance evaluations, tracing, metrics, and debugging tools to help developers monitor and improve AI applications. The framework integrates with React, Next.js, Node.js, and other JavaScript environments, with options for standalone deployment, Mastra Cloud hosting, and enterprise infrastructure.Starting Price: Free -
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AgentScope
AgentScope
AgentScope is an AI-driven agent observability and operations platform that provides visibility, control, and performance analytics for autonomous AI agents across production workloads. It enables engineering and DevOps teams to monitor, diagnose, and optimize complex multi-agent applications in real time by capturing detailed telemetry on agent actions, decisions, resource usage, and outcome quality. With rich dashboards and timelines, AgentScope helps teams trace execution flows, identify bottlenecks, and understand how agents interact with external systems, APIs, and data sources, improving debugging and reliability for autonomous workflows. It supports customizable alerting, log aggregation, and structured event views so teams can quickly surface anomalous behavior or errors across distributed agent fleets. In addition to real-time monitoring, AgentScope provides historical analysis and reporting that help teams measure performance trends, model drift, etc.Starting Price: Free -
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Claude Managed Agents
Anthropic
Claude Managed Agents is a pre-built, configurable agent system from Anthropic designed to run long-running, asynchronous tasks on managed infrastructure without requiring developers to build their own agent loops. It acts as a complete “agent harness,” allowing developers to define goals while the system handles execution, orchestration, and state management behind the scenes. Unlike direct model prompting, which requires step-by-step interaction, Managed Agents are designed for tasks that unfold over time, such as research, automation, or multi-step workflows, where the agent can continue working independently after being started. It supports advanced capabilities such as multi-agent orchestration, where a primary agent can coordinate specialized sub-agents that operate in parallel with isolated contexts, improving both speed and output quality. -
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Agent Squad
Amazon
Agent Squad is a flexible and powerful open source framework developed by AWS for managing multiple AI agents and handling complex conversations. It enables multi-agent orchestration, allowing seamless coordination and leveraging of multiple AI agents within a single system. It offers dual language support, being fully implemented in both Python and TypeScript. Intelligent intent classification dynamically routes queries to the most suitable agent based on context and content. Agent Squad supports both streaming and non-streaming responses from different agents, ensuring flexible agent responses. It maintains and utilizes conversation context across multiple agents for coherent interactions. The architecture is extensible, allowing easy integration of new agents or customization of existing ones to fit specific needs. Agent Squad can be deployed universally, running anywhere from AWS Lambda to local environments or any cloud platform.Starting Price: Free -
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AG2
AG2
AG2 is the open source AgentOS for building production-ready AI agents and multi-agent systems in minutes, not months. Formerly AutoGen, it provides an open source Python framework for building, orchestrating, and scaling AI agents that can collaborate through shared context, use tools, execute workflows, and support both autonomous and human-in-the-loop patterns. AG2 is designed for developers who want to build systems, not prompts, with simple and intuitive syntax, built-in conversation patterns, and a flexible platform for multi-agent automation. Agents in AG2 can extend their capabilities with tools, allowing them to interact with external systems, fetch real-time data, execute code, search the web, process documents, and complete complex tasks beyond a model’s internal knowledge. It supports many LLM providers and local models, including OpenAI-compatible endpoints, Anthropic Claude, Gemini through Vertex AI, DeepSeek, and LM Studio.Starting Price: Free -
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MetaGPT
MetaGPT
The Multi-Agent Framework: Given one line Requirement, return PRD, Design, Tasks, Repo Assign different roles to GPTs to form a collaborative software entity for complex tasks. MetaGPT takes a one line requirement as input and outputs user stories / competitive analysis / requirements / data structures / APIs / documents, etc. Internally, MetaGPT includes product managers / architects / project managers / engineers. It provides the entire process of a software company along with carefully orchestrated SOPs.Starting Price: Free -
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Agno
Agno
Agno is a lightweight framework for building agents with memory, knowledge, tools, and reasoning. Developers use Agno to build reasoning agents, multimodal agents, teams of agents, and agentic workflows. Agno also provides a beautiful UI to chat with agents and tools to monitor and evaluate their performance. It is model-agnostic, providing a unified interface to over 23 model providers, with no lock-in. Agents instantiate in approximately 2μs on average (10,000x faster than LangGraph) and use about 3.75KiB memory on average (50x less than LangGraph). Agno supports reasoning as a first-class citizen, allowing agents to "think" and "analyze" using reasoning models, ReasoningTools, or a custom CoT+Tool-use approach. Agents are natively multimodal and capable of processing text, image, audio, and video inputs and outputs. The framework offers an advanced multi-agent architecture with three modes, route, collaborate, and coordinate.Starting Price: Free -
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AgentKit
OpenAI
AgentKit is a unified suite of tools designed to streamline the process of building, deploying, and optimizing AI agents. It introduces Agent Builder, a visual canvas that lets developers compose multi-agent workflows via drag-and-drop nodes, set guardrails, preview runs, and version workflows. The Connector Registry centralizes the management of data and tool integrations across workspaces and ensures governance and access control. ChatKit enables frictionless embedding of agentic chat interfaces, customizable to match branding and experience, into web or app environments. To support robust performance and reliability, AgentKit enhances its evaluation infrastructure with datasets, trace grading, automated prompt optimization, and support for third-party models. It also supports reinforcement fine-tuning to push agent capabilities further.Starting Price: Free -
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CAMEL-AI
CAMEL-AI
CAMEL-AI is the first LLM-based multi-agent framework and an open-source community dedicated to exploring the scaling laws of agents. It enables the creation of customizable agents using modular components tailored for specific tasks, facilitating the development of multi-agent systems that address challenges in autonomous cooperation. The framework serves as a generic infrastructure for various applications, including task automation, data generation, and world simulations. By studying agents on a large scale, CAMEL-AI.org aims to gain valuable insights into their behaviors, capabilities, and potential risks. The community emphasizes rigorous research, balancing urgency with patience, and encourages contributions that enhance infrastructure, improve documentation, and implement research ideas. The platform offers components such as models, tools, memory, and prompts to empower agents, and supports integrations with various external tools and services. -
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Langflow
Langflow
Langflow is a low-code AI builder designed to create agentic and retrieval-augmented generation applications. It offers a visual interface that allows developers to construct complex AI workflows through drag-and-drop components, facilitating rapid experimentation and prototyping. The platform is Python-based and agnostic to any model, API, or database, enabling seamless integration with various tools and stacks. Langflow supports the development of intelligent chatbots, document analysis systems, and multi-agent applications. It provides features such as dynamic input variables, fine-tuning capabilities, and the ability to create custom components. Additionally, Langflow integrates with numerous services, including Cohere, Bing, Anthropic, HuggingFace, OpenAI, and Pinecone, among others. Developers can utilize pre-built components or code their own, enhancing flexibility in AI application development. The platform also offers a free cloud service for quick deployment and test -
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Smolagents
Smolagents
Smolagents is an AI agent framework developed to simplify the creation and deployment of intelligent agents with minimal code. It supports code-first agents where agents execute Python code snippets to perform tasks, offering enhanced efficiency compared to traditional JSON-based approaches. Smolagents integrates with large language models like those from Hugging Face, OpenAI, and others, enabling developers to create agents that can control workflows, call functions, and interact with external systems. The framework is designed to be user-friendly, requiring only a few lines of code to define and execute agents. It features secure execution environments, such as sandboxed spaces, for safe code running. Smolagents also promotes collaboration by integrating deeply with the Hugging Face Hub, allowing users to share and import tools. It supports a variety of use cases, from simple tasks to multi-agent workflows, offering flexibility and performance improvements. -
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TEN
TEN
TEN (Transformative Extensions Network) is an open source framework designed to empower developers to build real-time multimodal AI agents capable of voice, video, text, image, and data-stream interaction with ultra-low latency. It includes a full ecosystem, TEN Turn Detection, TEN Agent, and TMAN Designer, allowing developers to rapidly assemble human-like, responsive agents that can see, speak, hear, and interact. With support for languages like Python, C++, and Go, it offers flexible deployment on both edge and cloud environments. Using components like graph-based workflow design, drag-and-drop UI (via TMAN Designer), and reusable extensions such as real-time avatars, RAG (Retrieval-Augmented Generation), and image generation, TEN enables highly customizable, scalable agent development with minimal code.Starting Price: Free -
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Deep Agents
LangChain
Deep Agents is an open-source developer library and agent harness for building LLM-powered agents that can work through multi-step tasks. It provides an agent loop with built-in capabilities for planning, persistent memory, file-system interaction, and delegation to subagents, while allowing developers to connect model providers and tools. The library is intended for software developers and teams creating custom agent applications, including research, coding, and other workflows that require an agent to plan and act across several steps. Developers can extend its behavior with custom tools, middleware, and backends, and integrate it with LangGraph and LangSmith for orchestration, tracing, and deployment workflows. Deep Agents is a software development framework rather than a ready-made end-user agent application; users implement and run agents within their own applications and environments.Starting Price: Free -
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OpenChiip Harness
OpenChiip
OpenChiip Harness is a self-hosted AI agent runtime and orchestration framework for developers building local or coordinated agent workflows. It combines LLM conversations, skill orchestration, tool execution, multi-layer memory, resource monitoring, and multi-agent collaboration in a React administration dashboard. Run it as a local service or connect it to the OpenChiip platform for collaborative scheduling. Its CLI, web dashboard, HTTP API, and WebSocket interface support chat, tools, sessions, memory, task management, and monitoring. It supports Baidu ERNIE, OpenAI-compatible model providers, and delegation to Codex or Claude Code. Install via pip or deploy with Docker, Linux packages, systemd, or Windows installers; macOS supports pip installation. Licensed under AIGCGPL-1.0. -
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FastAgency
FastAgency
FastAgency is an open source framework designed to accelerate the deployment of multi-agent AI workflows from prototype to production. It provides a unified programming interface compatible with various agentic AI frameworks, enabling developers to deploy agentic workflows in both development and production settings. With features like multi-runtime support, seamless external API integration, and a command-line interface for orchestration, FastAgency simplifies the creation of scalable, production-ready architectures for serving AI workflows. Currently, it supports the AutoGen framework, with plans to extend support to CrewAI, Swarm, and LangGraph in the future. Developers can easily switch between frameworks, choosing the best one for their project's specific needs. FastAgency also features a common programming interface that enables the development of core workflows once and reuse them across various user interfaces without rewriting code.Starting Price: Free -
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AgentSea
AgentSea
AgentSea is an open source platform designed to build, deploy, and share AI agents with ease. It delivers a collection of libraries and tools for building AI agent apps, favoring the UNIX philosophy of doing one thing well. Tools can be used individually or stacked together into a single agent app, and are compatible with frameworks like LlamaIndex and LangChain. Key components include SurfKit, a Kubernetes-style orchestrator for agents; DeviceBay, offering pluggable devices like file systems and desktops; ToolFuse, a library that wraps scripts, third-party apps, and APIs as Tool implementations; AgentD, a daemon making a Linux desktop OS accessible to bots; AgentDesk, a library for running AgentD-powered VMs; Taskara, for task management; ThreadMem, for building multi-role persistent threads; and MLLM, simplifying communication with multiple LLMs and multimodal LLMs. AgentSea also offers alpha agents like SurfPizza and SurfSlicer, which navigate GUIs using multimodal approaches.Starting Price: Free -
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OpenHarness
OpenHarness
OpenHarness is an open-source TypeScript SDK for developers building custom AI-agent applications, including coding agents, CLI tools, and web-based assistants. It provides stateless agent execution, explicit conversation-state handling, streaming events, composable middleware for retries, persistence and context compaction, hierarchical subagents, and permission-controlled tools. Developers can connect model providers through the Vercel AI SDK, add external capabilities through Model Context Protocol (MCP), and use filesystem or shell tools through configurable providers. The SDK also offers React hooks and Vue composables for streaming agent output into application interfaces. OpenHarness is installed as an npm package and is intended to be embedded in projects running on Node.js or edge runtimes; it is a developer library rather than a hosted end-user agent service. -
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EdgeVerve AI Next
EdgeVerve
EdgeVerve AI Next is a unified, scalable platform designed to drive business transformations through powerful agentic AI, generative AI, responsible AI, and multi-cloud capabilities. Built from the ground up to leverage the power of generative AI, the AI Next platform bridges silos in people, processes, data, and technology to drive transformation in business operations. It features robust agent lifecycle management, accelerated agent development with intuitive no-code/low-code interfaces, flexible orchestration frameworks, and an extensive tool library. EdgeVerve AI Next's adaptable AI architecture supports multiple AI models and frameworks within a secure enterprise environment. With a unified enterprise control tower, organizations can monitor, manage, and govern operations with real-time analytics. -
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OpenAGI
OpenAGI
OpenAGI is a developer-focused framework designed to help teams build autonomous, human-like AI agents capable of planning, reasoning, and executing tasks independently. It bridges the gap between traditional LLM applications and fully autonomous agents by offering tools for decision-making, continual learning, and long-term task execution. The platform allows developers to create specialized agents for real-world use cases across industries such as education, finance, healthcare, and software development. With its flexible architecture, OpenAGI supports sequential, parallel, and dynamic communication patterns between agents. Developers can choose automated configuration generation or manually tailor every detail for complete customization. OpenAGI represents an early but significant step toward making powerful, adaptive agent technology accessible to everyone.Starting Price: Free -
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Koog
JetBrains
Koog is a Kotlin‑based framework for building and running AI agents entirely in idiomatic Kotlin, supporting both single‑run agents that process individual inputs and complex workflow agents with custom strategies and configurations. It features pure Kotlin implementation, seamless Model Control Protocol (MCP) integration for enhanced model management, vector embeddings for semantic search, and a flexible system for creating and extending tools that access external systems and APIs. Ready‑to‑use components address common AI engineering challenges, while intelligent history compression optimizes token usage and preserves context. A powerful streaming API enables real‑time response processing and parallel tool calls. Persistent memory allows agents to retain knowledge across sessions and between agents, and comprehensive tracing facilities provide detailed debugging and monitoring.Starting Price: Free -
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Calljmp
Calljmp
Calljmp is a developer-first AI agent runtime designed to build, run, and scale long-running stateful workflows written in TypeScript. While many modern tools like Mastra AI provide rich frameworks to define agents and workflows, Calljmp focuses on actually running them reliably in production. Calljmp combines agent logic, durable execution, human-in-the-loop pause/resume, retries with idempotency, and built-in observability into a unified execution environment. Developers implement agents as code, and the runtime guarantees reliable execution, state persistence, and operational visibility without gluing together custom queues, databases, and monitoring stacks. Calljmp is ideal for engineering teams, product developers, and backend architects who want to embed intelligent agents into product systems while offloading execution complexity to a purpose-built runtime.Starting Price: Free -
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Upsonic
Upsonic
Upsonic is an open source framework that simplifies AI agent development for business needs. It enables developers to build, manage, and deploy agents with integrated Model Context Protocol (MCP) tools across cloud and local environments. Upsonic reduces engineering effort by 60-70% with built-in reliability features and service client architecture. It offers a client-server architecture that isolates agent applications, keeping existing systems healthy and stateless. It provides more reliable agents, scalability, and a task-oriented structure needed for completing real-world cases. Upsonic supports autonomous agent characterization, allowing self-defined goals and backgrounds, and integrates computer-use capabilities for executing human-like tasks. With direct LLM call support, developers can access models without abstraction layers, completing agent tasks faster and more cost-effectively. -
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Cua
Cua
Cua is a computer-use agent platform that lets AI agents see screens, click buttons, type, and run code just like a human across macOS, Windows, Linux, browsers, and mobile environments. It provides cloud-based, sandboxed desktops where agents can automate real software workflows without relying on APIs. Built on open-source Cua agents, the platform enables developers to build, run, and scale computer-use agents with precision and reliability. Cua supports multi-step tasks, structured outputs, and human-in-the-loop recovery for complex automation. Agents operate in fully isolated environments to ensure safety and reproducibility. Cua is designed to make AI interaction with real applications practical and scalable.Starting Price: $10/month -
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Agent Builder
OpenAI
Agent Builder is part of OpenAI’s tooling for constructing agentic applications, systems that use large language models to perform multi-step tasks autonomously, with governance, tool integration, memory, orchestration, and observability baked in. The platform offers a composable set of primitives—models, tools, memory/state, guardrails, and workflow orchestration- that developers assemble into agents capable of deciding when to call a tool, when to act, and when to halt and hand off control. OpenAI provides a new Responses API that combines chat capabilities with built-in tool use, along with an Agents SDK (Python, JS/TS) that abstracts the control loop, supports guardrail enforcement (validations on inputs/outputs), handoffs between agents, session management, and tracing of agent executions. Agents can be augmented with built-in tools like web search, file search, or computer use, or custom function-calling tools. -
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GraphBit
GraphBit
GraphBit is an enterprise-grade agentic AI framework built to run critical AI systems with security, governance, and predictable production performance. It combines a Rust execution core with a Python wrapper to give developers high-performance orchestration with the accessibility of Python, helping teams build reliable multi-agent workflows with minimal CPU and memory usage. GraphBit is designed around the layers that reduce risk, including interfaces, configuration, models, tools, actions, memory, orchestration, and observability. It integrates into existing apps, powers custom AI interfaces, and lets users interact through familiar workflows with controlled actions. Teams can define policies, rules, and guardrails centrally, while GraphBit enforces behavior without changing application code. It supports LLMs and multimodal models from multiple providers, allowing teams to swap models freely without breaking workflows or governance. -
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OpenLegion
OpenLegion
OpenLegion is a production-grade AI agent framework and platform for building an AI workforce by describing the team you want. Tell OpenLegion “I want a marketing agency,” “I want a sales team,” or “I want a research desk,” and it deploys the agent stack with roles, budgets, permissions, and secure credential controls built in. Instead of stopping at chat, OpenLegion is designed for real workflows; agents can browse websites, fill out forms, write and run code, send emails and messages, manage files and folders, research and summarize, scrape data, qualify sales leads, process spreadsheets, post to social media, monitor for changes, and trigger workflows through Slack, Telegram, or Discord. Each agent runs in its own isolated container with per-agent budgets, tool permissions, persistent memory, MCP-compatible skills, and vault-secured credentials that agents never touch.Starting Price: $19 per month -
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Letta
Letta
Create, deploy, and manage your agents at scale with Letta. Build production applications backed by agent microservices with REST APIs. Letta adds memory to your LLM services to give them advanced reasoning capabilities and transparent long-term memory (powered by MemGPT). We believe that programming agents start with programming memory. Built by the researchers behind MemGPT, introduces self-managed memory for LLMs. Expose the entire sequence of tool calls, reasoning, and decisions that explain agent outputs, right from Letta's Agent Development Environment (ADE). Most systems are built on frameworks that stop at prototyping. Letta' is built by systems engineers for production at scale so the agents you create can increase in utility over time. Interrogate the system, debug your agents, and fine-tune their outputs, all without succumbing to black box services built by Closed AI megacorps.Starting Price: Free -
44
Lyzr
Lyzr AI
Lyzr Agent Studio is a low-code/no-code platform for enterprises to build, deploy, and scale AI agents with minimal technical complexity. Built on Lyzr's robust Agent Framework - the first and only agent framework to have safe and responsible AI natively integrated into the core agent architecture, this platform allows you to build AI Agents while keeping enterprise-grade safety and reliability in mind. The platform allows both technical and non-technical users to create AI-powered solutions that drive automation, improve operational efficiency, and enhance customer experiences—without the need for extensive coding expertise. Whether you're deploying AI agents for Sales, Marketing, HR, or Finance, or building complex, industry-specific applications for sectors like BFSI, Lyzr Agent Studio provides the tools to create agents that are both highly customizable and compliant with enterprise-grade security standards.Starting Price: $19/month/user -
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Oraczen
Oraczen
Oraczen is an AI-driven solution designed to help enterprises navigate complex systems by deploying agentic AI frameworks. These frameworks integrate seamlessly with existing infrastructures, facilitating tasks such as bridging data gaps, integrating legacy IT systems, and blending human-AI workflows. Oraczen emphasizes security with containerized environments that ensure data protection and compliance with industry standards. Its rapid deployment capabilities allow organizations to implement AI solutions within two weeks, enhancing operational efficiency across sectors like finance, supply chain, and healthcare. Oraczen fuses industry expertise and AI mastery with our Zen Platform to deploy AI agents that conquer enterprise complexity, bridging data gaps, integrating legacy IT, and blending human-AI design for seamless workflows in just 2 weeks. -
46
KaibanJS
KaibanJS
KaibanJS is a JavaScript framework for building and visualizing multi‑agent AI systems using a familiar Kanban‑style interface. After installing via npm or npx and importing core classes, you can define agent goals, tasks, and teams programmatically, then run workflows locally or deploy to platforms like Vercel or AWS, no vendor lock‑in thanks to its MIT license. A Trello‑like Kaiban Board transforms console logs into shareable, real‑time workflows, while its Redux‑inspired state management ensures consistent handling of agent states, tasks, and results. Built‑in observability captures every state change, tool call, and log for easy debugging and performance monitoring, and extensibility comes via integrations with major frameworks, multiple LLM providers, language‑chain‑compatible tools, and custom plugins. Lightweight and framework‑agnostic, KaibanJS lets JavaScript developers orchestrate, monitor, and iterate on complex agentic workflows. -
47
ZGI
ZGI
ZGI is an open source enterprise AI platform for building business-ready agents with company data, tools, workflows, models, and skills. Its Agent Runtime lets agents load Skills, use company knowledge and live data, call tools, and return useful work fast. The Model Gateway connects global and domestic providers such as OpenAI, Anthropic, Google, DeepSeek, and Qwen, allowing teams to choose the right model for each agent by quality, availability, cost, or region while centrally controlling access, quotas, routing policies, and fallback. The product workspace covers the full agent lifecycle: Agent Studio combines Skills, knowledge, tools, and models; Workflows orchestrate multi-step work and let users inspect every execution; Database supports natural-language queries over live business data with governed access; Model Management handles provider connections and enterprise routing; and Knowledge Assets turn company files into searchable, source-aware knowledge.Starting Price: Free -
48
Phinite
Phinite AI
Phinite provides shared infrastructure for building, deploying, and governing AI agents across orchestration, security, observability, lifecycle management, and environment promotion — so engineering teams don't rebuild these layers for every new agent use case. Core capabilities: Orchestration for multi-agent systems (agent-to-agent, nested calls) Deep session-level observability: execution timelines, decision variables, tool calls, latency/cost tracking Private Agent Registry for skill discoverability Eval suite for accuracy/safety benchmarking Dev-to-Production workflow with environment promotion Kubernetes-native deployment, VPC-internal deployability SOC 2 Type 2 complianceStarting Price: $20/month -
49
Asteroid AI
Asteroid AI
Asteroid is an AI-driven browser-automation platform that lets both non-technical users and engineers build, deploy, monitor, and refine complex web workflows without writing traditional code. Its core is a graph-based agent builder where you describe desired tasks in natural language and configure repeatable logic with variables and structured outputs. Behind the scenes, Asteroid combines encrypted credential management, selector-based guardrails powered by Playwright, and live browser control to navigate pages, interact with UI elements, and call external APIs as needed. You can instantly deploy agents via a RESTful API, embed them into existing systems, or iterate in the platform’s console with real-time supervision, debugging tools, and human-in-the-loop checkpoints. Use cases range from multi-step data retrieval (insurance quotes, grant applications) and intelligent data entry into legacy systems (patient records, supplier portals) to automated reporting.Starting Price: $30 per month -
50
HelpNow Agentic AI Platform
Bespin Global
Bespin Global’s HelpNow Agentic AI Platform is an enterprise-grade AI agent automation and orchestration platform that lets organizations rapidly create, deploy, and manage autonomous AI agents tailored to real business workflows without deep coding, using a visual builder (Agentic Studio) and centralized portal to design single or multi-agent workflows, integrate with existing systems via APIs and connectors, and monitor performance in real time with an Agent Control Tower for governance, policy enforcement, and quality oversight; it supports LLM orchestration, multimodal inputs (text, voice, STT/TTS), and flexible deployment across cloud environments (AWS, GCP, Azure, on-premises) with connectivity to internal data, documents, and business processes so agents can act on context-rich enterprise information. It combines tools for agent lifecycle management, real-time observability, integration with voice and document processing, and enterprise governance.
