# Microsoft Learn MCP Server (`agentify/microsoft-learn-mcp-server`) Actor

The Microsoft Learn MCP Server enables AI clients to access trusted and up-to-date information directly from Microsoft's official documentation. It provides semantic search and document retrieval capabilities from Microsoft Learn.

- **URL**: https://apify.com/agentify/microsoft-learn-mcp-server.md
- **Developed by:** [agentify](https://apify.com/agentify) (community)
- **Categories:** MCP servers, Open source
- **Stats:** 11 total users, 1 monthly users, 75.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event + usage

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

### Microsoft Learn MCP Server

The Microsoft Learn MCP Server enables AI clients to access trusted and up-to-date information directly from Microsoft's official documentation. It provides semantic search and document retrieval capabilities from Microsoft Learn.

**About this MCP Server:** To understand how to connect to and utilize this MCP server, please refer to the official Model Context Protocol documentation at [mcp.apify.com](https://mcp.apify.com).

### Connection URL

MCP clients can connect to this server at:

```text
https://mcp-servers--microsoft-learn-mcp-server.apify.actor/mcp
```

### Client Configuration

To connect to this MCP server, use the following configuration in your MCP client:

```json
{
  "mcpServers": {
    "microsoft-learn": {
      "url": "https://mcp-servers--microsoft-learn-mcp-server.apify.actor/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_APIFY_TOKEN"
      }
    }
  }
}
```

**Note:** Replace `YOUR_APIFY_TOKEN` with your actual Apify API token. You can find your token in the [Apify Console](https://console.apify.com/account/integrations).

### 🚩 Claim this MCP server

All credits to the original authors of https://github.com/MicrosoftDocs/mcp
To claim this server, please write to <ai@apify.com>.

***

## 🌟 Microsoft Learn MCP Server

The Microsoft Learn MCP Server is a remote MCP Server that enables clients like GitHub Copilot and other AI agents to bring trusted and up-to-date information directly from Microsoft's official documentation. It supports streamable http transport, which is lightweight for clients to use.

### 🎯 Overview

#### ✨ Key Capabilities

- **High-Quality Content Retrieval**: Search and retrieve relevant content from Microsoft's official documentation in markdown format.
- **Semantic Understanding**: Uses advanced vector search to find the most contextually relevant documentation for any query.
- **Real-time Updates**: Access the latest Microsoft documentation as it's published.

### 🛠️ Currently Supported Tools

| Tool Name                | Description | Input Parameters |
|--------------------------|-------------|------------------|
| `microsoft_learn_search` | Performs semantic search against Microsoft official technical documentation | `query` (string): The search query for retrieval |
| `microsoft_learn_fetch`  | Fetch and convert a Microsoft documentation page into markdown format | `url` (string): URL of the documentation page to read |

#### ✨ Example Usage

Your AI assistant should automatically use these tools for Microsoft-related topics. With both search and fetch capabilities, you can get quick answers or comprehensive deep dives.

##### **Quick Search & Reference**

> "Give me the Azure CLI commands to create an Azure Container App with a managed identity. **search Microsoft Learn**"

> "Is gpt-4.1-mini available in EU regions? **fetch full doc**"

##### **Code Verification & Best Practices**

> "Are you sure this is the right way to implement `IHttpClientFactory` in a .NET 8 minimal API? **search Microsoft Learn and fetch full doc**"

> "Show me the complete guide for implementing authentication in ASP.NET Core. **fetch full doc**"

##### **Comprehensive Learning & Deep Dive**

> "I need to understand Azure Functions end-to-end. **search Microsoft Learn and deep dive**"

> "Get me the full step-by-step tutorial for deploying a .NET application to Azure App Service. **search Microsoft Learn and deep dive**"

### References

To learn more about Apify and Actors, take a look at the following resources:

- [Apify SDK for JavaScript documentation](https://docs.apify.com/sdk/js)
- [Apify SDK for Python documentation](https://docs.apify.com/sdk/python)
- [Apify Platform documentation](https://docs.apify.com/platform)
- [Apify MCP Server](https://docs.apify.com/platform/integrations/mcp)
- [Webinar: Building and Monetizing MCP Servers on Apify](https://www.youtube.com/watch?v=w3AH3jIrXXo)
- [Join our developer community on Discord](https://discord.com/invite/jyEM2PRvMU)

## Actor input object example

```json
{}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("agentify/microsoft-learn-mcp-server").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("agentify/microsoft-learn-mcp-server").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call agentify/microsoft-learn-mcp-server --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,agentify/microsoft-learn-mcp-server"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/lgxvMvZXZbIe7xc7d/builds/Ahh7ohznXMUc7mtZg/openapi.json