Microsoft Learn MCP
Server Details
Official Microsoft Learn MCP Server – real-time, trusted docs & code samples for AI and LLMs.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- MicrosoftDocs/mcp
- GitHub Stars
- 1,587
- Server Listing
- Microsoft Learn Docs MCP Server
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Tool Definition Quality
Average 4.5/5 across 3 of 3 tools scored.
Each tool has a clearly distinct purpose: microsoft_docs_search finds relevant documentation pages, microsoft_docs_fetch retrieves complete content from specific pages, and microsoft_code_sample_search focuses on code snippets. There is no overlap in functionality, making tool selection straightforward for an agent.
All tool names follow a consistent snake_case pattern with a 'microsoft_' prefix and descriptive verb_noun combinations (docs_search, docs_fetch, code_sample_search). This uniformity enhances readability and predictability across the tool set.
With 3 tools, the server is well-scoped for its purpose of accessing Microsoft Learn documentation and code samples. It covers search, retrieval, and code-specific needs efficiently, though a slightly larger set might allow for more granular operations without being excessive.
The tool set provides complete coverage for the domain: search for documentation, fetch full content, and search for code samples. This covers the core workflows of discovering, retrieving, and utilizing Microsoft/Azure documentation and code, with no apparent gaps that would hinder agent tasks.
Available Tools
3 toolsmicrosoft_code_sample_searchMicrosoft Code Sample SearchARead-onlyIdempotentInspect
Search for code snippets and examples in official Microsoft Learn documentation. This tool retrieves relevant code samples from Microsoft documentation pages providing developers with practical implementation examples and best practices for Microsoft/Azure products and services related coding tasks. This tool will help you use the LATEST OFFICIAL code snippets to empower coding capabilities.
When to Use This Tool
When you are going to provide sample Microsoft/Azure related code snippets in your answers.
When you are generating any Microsoft/Azure related code.
Usage Pattern
Input a descriptive query, or SDK/class/method name to retrieve related code samples. The optional parameter language can help to filter results.
Eligible values for language parameter include: csharp javascript typescript python powershell azurecli al sql java kusto cpp go rust ruby php
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | a descriptive query, SDK name, method name or code snippet related to Microsoft/Azure products, services, platforms, developer tools, frameworks, APIs or SDKs | |
| language | No | Optional parameter specifying the programming language of code snippets to retrieve. Can significantly improve search quality if provided. Eligible values: csharp javascript typescript python powershell azurecli al sql java kusto cpp go rust ruby php |
Output Schema
| Name | Required | Description |
|---|---|---|
| results | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds valuable behavioral context beyond what annotations provide. While annotations indicate read-only, idempotent, and non-destructive operations, the description emphasizes that it retrieves 'LATEST OFFICIAL' code snippets and provides 'practical implementation examples and best practices.' This adds important context about the source quality and practical utility that annotations don't cover. No contradictions with annotations exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, when to use, usage pattern) and front-loads the core purpose. While slightly verbose with some repetition (language values appear twice), every sentence serves a purpose - explaining the tool's value, when to use it, and how to use it. The structure helps the agent quickly understand key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity, comprehensive annotations (readOnlyHint, idempotentHint, destructiveHint), 100% schema coverage, and the presence of an output schema, the description provides excellent contextual completeness. It covers purpose, usage guidelines, and behavioral context sufficiently for the agent to understand when and how to use this tool effectively. The output schema will handle return value documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the schema already documents both parameters thoroughly. The description adds some value by providing the 'Usage Pattern' section that explains how to formulate queries and mentions that the language parameter 'can help to filter results,' but this largely repeats what's in the schema descriptions. The list of eligible language values is duplicated from the schema. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Search for code snippets and examples in official Microsoft Learn documentation.' It specifies the resource (Microsoft documentation code samples) and distinguishes it from siblings like 'microsoft_docs_search' by focusing specifically on code samples rather than general documentation. The mention of 'LATEST OFFICIAL' code snippets adds important scope information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes explicit 'When to Use This Tool' and 'Usage Pattern' sections. It provides clear guidance on when to use this tool ('When you are going to provide sample Microsoft/Azure related code snippets' and 'When you are generating any Microsoft/Azure related code') and distinguishes it from alternatives by focusing on code samples specifically. The guidance is practical and directly addresses the agent's decision-making needs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
microsoft_docs_fetchMicrosoft Docs FetchARead-onlyIdempotentInspect
Fetch and convert a Microsoft Learn documentation webpage to markdown format. This tool retrieves the latest complete content of Microsoft documentation webpages including Azure, .NET, Microsoft 365, and other Microsoft technologies.
When to Use This Tool
When search results provide incomplete information or truncated content
When you need complete step-by-step procedures or tutorials
When you need troubleshooting sections, prerequisites, or detailed explanations
When search results reference a specific page that seems highly relevant
For comprehensive guides that require full context
Usage Pattern
Use this tool AFTER microsoft_docs_search when you identify specific high-value pages that need complete content. The search tool gives you an overview; this tool gives you the complete picture.
URL Requirements
The URL must be a valid HTML documentation webpage from the microsoft.com domain
Binary files (PDF, DOCX, images, etc.) are not supported
Output Format
markdown with headings, code blocks, tables, and links preserved.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL of the Microsoft documentation page to read |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds valuable behavioral context beyond annotations, including URL requirements (must be HTML from microsoft.com, no binary files), output format details (markdown with preserved elements), and the tool's role in a workflow. Annotations already cover safety (readOnlyHint=true, destructiveHint=false, idempotentHint=true), so the description appropriately supplements rather than contradicts.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, when to use, usage pattern, URL requirements, output format), front-loaded with essential information, and every sentence serves a specific purpose without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity, rich annotations, and clear sibling context, the description provides comprehensive guidance on purpose, usage, constraints, and output, making it complete enough for effective agent use despite the lack of an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage for the single parameter (url), the schema already documents it adequately. The description adds minimal additional context about URL validity and domain requirements, but this doesn't significantly enhance understanding beyond the schema's basics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('fetch and convert') and resources ('Microsoft Learn documentation webpage'), distinguishing it from sibling tools by focusing on complete content extraction rather than search functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance with a dedicated 'When to Use This Tool' section, specific use cases, and clear direction to use this tool AFTER microsoft_docs_search, effectively distinguishing it from alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
microsoft_docs_searchMicrosoft Docs SearchARead-onlyIdempotentInspect
Search official Microsoft/Azure documentation to find the most relevant and trustworthy content for a user's query. This tool returns up to 10 high-quality content chunks (each max 500 tokens), extracted from Microsoft Learn and other official sources. Each result includes the article title, URL, and a self-contained content excerpt optimized for fast retrieval and reasoning. Always use this tool to quickly ground your answers in accurate, first-party Microsoft/Azure knowledge.
Follow-up Pattern
To ensure completeness, use microsoft_docs_fetch when high-value pages are identified by search. The fetch tool complements search by providing the full detail. This is a required step for comprehensive results.
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | a query or topic about Microsoft/Azure products, services, platforms, developer tools, frameworks, or APIs |
Output Schema
| Name | Required | Description |
|---|---|---|
| results | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds valuable behavioral context beyond what annotations provide: it specifies the return format (up to 10 content chunks, each max 500 tokens), content characteristics (article title, URL, self-contained excerpt), and optimization purpose (fast retrieval and reasoning). While annotations cover safety (readOnlyHint, destructiveHint), the description enriches understanding of the tool's operational behavior without contradicting annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with zero wasted sentences. The first paragraph establishes core functionality, the second defines the follow-up pattern with sibling tools. Each sentence adds distinct value: purpose, scope, output format, usage guidance, and complementary tool relationship. The information is front-loaded and logically organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity, comprehensive annotations (readOnlyHint, idempotentHint, destructiveHint), 100% schema coverage, and existence of an output schema, the description provides complete contextual understanding. It explains the tool's role in the ecosystem, output characteristics, and relationship with sibling tools, making it fully adequate for an AI agent to understand when and how to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage for the single 'query' parameter, the description doesn't need to add parameter details. The schema already fully documents the parameter's purpose and format. The description appropriately focuses on tool behavior rather than repeating parameter information, meeting the baseline expectation for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('search', 'find', 'returns') and resources ('official Microsoft/Azure documentation', 'Microsoft Learn and other official sources'). It explicitly distinguishes this search tool from its sibling microsoft_docs_fetch by explaining their complementary relationship, making the differentiation clear and actionable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool ('Always use this tool to quickly ground your answers in accurate, first-party Microsoft/Azure knowledge') and when to use alternatives ('use microsoft_docs_fetch when high-value pages are identified by search'). It clearly defines the follow-up pattern and positions this as the first step in a two-step process with microsoft_docs_fetch.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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