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Mcp Server Ragdocs

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An MCP server that provides tools for retrieving and processing documentation through vector search, both locally or hosted. Enabling AI assistants to augment their responses with relevant documentation context.

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Overview

Mcp Server Ragdocs is an MCP server that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to enhance their responses with relevant documentation context.

To use Mcp Server Ragdocs, set up the server by configuring the environment variables and deploying it locally or in the cloud. You can then utilize its API to perform documentation searches and retrievals.

  • Vector-based documentation search and retrieval - Support for multiple documentation sources - Local and cloud deployment options - Semantic search capabilities - Real-time context augmentation for AI models
  1. Enhancing AI responses with relevant documentation.
  2. Building documentation-aware AI assistants.
  3. Implementing semantic documentation search for developers.
  4. Augmenting existing knowledge bases with contextual information.

Add to your AI client

Use these steps to connect Mcp Server Ragdocs in Cursor, Claude, VS Code, and other MCP-compatible apps. The same JSON appears in the Use with menu above for one-click copy.

Cursor

Add this to your .cursor/mcp.json file in your project root, then restart Cursor.

.cursor/mcp.json

{
  "mcpServers": {
    "mcp-server-ragdocs-sanderkooger": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-mcp-server-ragdocs-sanderkooger"
      ]
    }
  }
}

Claude Desktop

Add this server entry to the mcpServers object in your Claude Desktop config, then restart the app.

~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)

{
  "mcpServers": {
    "mcp-server-ragdocs-sanderkooger": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-mcp-server-ragdocs-sanderkooger"
      ]
    }
  }
}

Claude Code

Add this to your project's .mcp.json file. Claude Code will detect it automatically.

.mcp.json (project root)

{
  "mcpServers": {
    "mcp-server-ragdocs-sanderkooger": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-mcp-server-ragdocs-sanderkooger"
      ]
    }
  }
}

VS Code (Copilot)

Add this to your .vscode/mcp.json file. Requires the GitHub Copilot extension with MCP support enabled.

.vscode/mcp.json

{
  "servers": {
    "mcp-server-ragdocs-sanderkooger": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-mcp-server-ragdocs-sanderkooger"
      ]
    }
  }
}

Windsurf

Add this to your Windsurf MCP config file, then restart Windsurf.

~/.codeium/windsurf/mcp_config.json

{
  "mcpServers": {
    "mcp-server-ragdocs-sanderkooger": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-mcp-server-ragdocs-sanderkooger"
      ]
    }
  }
}

Cline

Open Cline settings, navigate to MCP Servers, and add this server configuration.

Cline MCP Settings (via UI)

{
  "mcpServers": {
    "mcp-server-ragdocs-sanderkooger": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-mcp-server-ragdocs-sanderkooger"
      ]
    }
  }
}

FAQ

Can I deploy Mcp Server Ragdocs locally?

Yes! Mcp Server Ragdocs can be deployed locally using Docker Compose.

What types of documentation can be processed?

It supports various documentation formats and sources, allowing for flexible integration.

Is there support for cloud deployment?

Yes! You can deploy Mcp Server Ragdocs on cloud platforms with the appropriate configuration.7:["$","div",null,{"className":"container mx-auto flex flex-col gap-4","children":["$L26","$L27",["$","$L28",null,{"currentProject":{"id":2321,"uuid":"f3b2e8f4-2a24-461d-b678-bf4b35b33202","name":"mcp-server-ragdocs","title":"Mcp Server Ragdocs","description":"An MCP server that provides tools for retrieving and processing documentation through vector search, both locally or hosted. Enabling AI assistants to augment their responses with relevant documentation context.","avatar_url":null,"created_at":"2025-03-09T15:52:17.831+00:00","updated_at":"2025-03-12T22:29:31.649+00:00","status":"created","author_name":"sanderkooger","author_avatar_url":null,"tags":"mcp-server,documentation,vector-search","category":"research-and-data","is_featured":false,"sort":1,"url":"https://github.com/sanderkooger/mcp-server-ragdocs","target":"_self","content":"$29","summary":"$2a","img_url":null,"type":null,"metadata":null,"user_uuid":"26ad883d-5957-45a7-8816-e113fede44d1","tools":null,"sse_url":null,"sse_provider":null,"sse_params":null,"is_official":false,"server_command":null,"server_params":null,"server_config":null,"allow_call":false,"is_innovation":false,"is_dxt":false,"dxt_manifest":null,"dxt_file_url":null,"is_audit":false},"randomProjects":[],"currentServerKey":"$undefined"}]]}]

Research and data