DocsMCP: Documentation MCP Server

What does “DocsMCP” MCP Server do?

DocsMCP is a Model Context Protocol (MCP) server designed to provide documentation access to Large Language Models (LLMs). By connecting to both local and remote documentation sources, DocsMCP enables LLMs to fetch, parse, and query documentation in real time. This enhances AI assistants and developer workflows by allowing seamless retrieval of technical references, guides, and API docs relevant to the current task or code context. DocsMCP acts as an intermediary, translating requests from LLMs into actionable searches or fetches against documentation resources, thereby enabling tasks such as searching for function usage, exploring library docs, or integrating contextual help directly into development environments.

List of Prompts

No prompt templates are mentioned in the repository.

List of Resources

No explicit MCP resources are documented in the repository.

List of Tools

• getDocumentationSources
  Lists all available documentation sources that have been configured for DocsMCP.
• getDocumentation
  Fetches and parses documentation from a specified URL or local file path.
  • Parameter: url – The URL or file path to fetch the documentation from.

Use Cases of this MCP Server

• Instant Documentation Lookup
  Developers can fetch library or API documentation directly within their development environment, reducing context switching and speeding up coding.
• Contextual Code Help
  LLMs can provide context-aware assistance by referencing relevant documentation sections based on the code being written or reviewed.
• Automated API Reference Retrieval
  When working with unfamiliar APIs, DocsMCP enables LLMs to retrieve up-to-date usage details, examples, and parameter information on demand.
• Remote and Local Docs Integration
  Teams can aggregate both internal (local) and external (remote) documentation, making all resources uniformly accessible through a single MCP interface.

How to set it up

Windsurf

No setup instructions provided for Windsurf.

Claude

No setup instructions provided for Claude.

Cursor

1. Prerequisite: Ensure Node.js and npx are installed.
2. In your project, create or edit the .cursor/mcp.json file.
3. Add the DocsMCP server configuration as below.
4. Save the file and restart Cursor if needed.
5. Verify that Cursor can access documentation through DocsMCP.

Example .cursor/mcp.json:

{
  "mcpServers": {
    "docs-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "docsmcp",
        "'--source=Model Context Protocol (MCP)|https://modelcontextprotocol.io/llms-full.txt'"
      ]
    }
  }
}

Securing API Keys: No API keys or env configuration shown in the repository.

Cline

No setup instructions provided for Cline.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "docs-mcp": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “docs-mcp” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Our opinion

DocsMCP is a focused and straightforward MCP server for documentation delivery to LLMs. It exposes essential tools for documentation fetching but lacks advanced features like resource exposure, prompt templates, or explicit security guidance. The absence of prompt and resource definitions, as well as missing setup guides for some platforms, limits its flexibility. It is open source under MIT, but community traction is minimal. Overall, it is a useful but basic MCP server.

MCP Score

Rating: 4/10 – DocsMCP provides core MCP server utility for documentation, but lacks advanced or flexible MCP features, prompt templates, and broader platform support. Its simplicity is a strength for focused use cases but a limitation for extensibility.