Autopilot by Directionally Local
Autopilot is an open-source terminal coding agent and SDK for developers working in Git repositories. It reads a repository, plans tasks, edits files and runs commands, with plan, edit and automatic-approval modes. It connects to 25+ hosted model providers using your own credentials, supports local models through Ollama and LM Studio, and works with OpenAI-compatible endpoints. Autopilot runs on macOS, Linux and Windows for interactive sessions and unattended server jobs with runtime, token and cost budgets, checkpoint recovery and email notifications. It supports MCP servers, language-server features, hooks and local memory. Its headless SDK and JSONL-over-stdio RPC enable integration into other applications. On OpenRouter, subagents can run in read-only Hotcell sandboxes with short-lived, spend-capped tokens instead of the provider key. Autopilot is free and MIT-licensed; model-provider usage may incur separate charges.
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Flue
Flue is an open agent framework for building durable AI agents with a programmable TypeScript harness. Created by the team behind Astro, it uses a React-like hooks API to compose agent behavior, persistent state, lifecycle events, models, tools, sandboxes, subagents, skills, and MCP servers in code. Agents are stateful and addressable over HTTP, keep context across conversations and events, and can change capabilities as work progresses. Flue records every session in a durable stream, so accepted work survives crashes, restarts, and deploys; interrupted sessions resume automatically and clients reconnect without starting over. Developers can run agents locally, in CI, from their own backend, or orchestrate them with systems such as Cloudflare Workflows and Inngest. Secure sandboxes let agents run commands, edit files, and do real work, while tools connect them to APIs and data. Flue is powered by Pi and supports different LLM providers, allowing teams to choose the models they want.
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dcode
dcode is an open-source terminal coding agent for developers and software teams. Built on the Deep Agents SDK, it can plan and execute coding tasks, inspect and edit project files, run tools, and delegate work to subagents. Its interactive terminal interface streams responses and lets users resume conversations across sessions; headless mode supports scripted and CI workflows. Users select a compatible model provider and supply their own credentials, then customize models, tools, plugins, skills, memory, middleware, hooks, and approval rules. Tool calls can be approved or rejected, and code can run locally or in supported remote sandboxes. dcode supports MCP tools and can connect to LangSmith for tracing prompts, responses, tool calls, errors, and token usage. It is intended for developers who want to configure and inspect an AI coding agent rather than use a fixed coding assistant.
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Muse Spark 1.1
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Muse Spark 1.1 is a multimodal reasoning model from Meta Superintelligence Labs built for agentic tasks, coding, computer use, tool use, and multimodal understanding. The model improves on the original Muse Spark with stronger performance in planning, orchestration, long-context work, coding workflows, and external app interactions. Muse Spark 1.1 can manage a 1 million token context window, remember earlier actions, retrieve important information, compact context, and delegate tasks across parallel subagents. It is designed to operate across tools, MCP servers, custom skills, browsers, native apps, scripts, images, video, PDFs, and audio-based workflows. Developers can access Muse Spark 1.1 through the new Meta Model API public preview, while users can try it in Thinking mode in the Meta AI app and on meta.ai.
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