rahulretnan/mcp-ragdocs

3.5

If you are the rightful owner of mcp-ragdocs and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.

An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.

Tools

Functions exposed to the LLM to take actions

search_documentation

Search for documents through vectors and return relevant fragments and source information

list_sources

List all available document sources and their metadata

extract_urls

Extract URL from text and check if it already exists in the document

remove_documentation

Delete documents from specific sources

list_queue

List all items in the processing queue and their status

run_queue

Process all items in the queue and automatically add new documents to vector storage

clear_queue

Clear all items in the processing queue

add_documentation

Add new documents to the processing queue

Prompts

Interactive templates invoked by user choice

No prompts

Resources

Contextual data attached and managed by the client

No resources

Author

rahulretnan

Claim Ownership

Verify you have write access to the repository

Version

v.1.0.0

Repository

https://github.com/rahulretnan/mcp-ragdocs

GitHub Stars

License

Other

Last publish date

2025-02-07

Last update date

2025-08-16

Server configs

in cline

{
  "mcpServers": {
    "rag-docs": {
      "command": "node",
      "args": ["/path/to/your/mcp-ragdocs/build/index.js"],
      "env": {
        "EMBEDDING_PROVIDER": "ollama", // default
        "EMBEDDING_MODEL": "nomic-embed-text", // optional
        "OPENAI_API_KEY": "your-api-key-here", // required for fallback
        "FALLBACK_PROVIDER": "openai", // recommended for reliability
        "FALLBACK_MODEL": "nomic-embed-text", // optional
        "QDRANT_URL": "http://localhost:6333"
      },
      "disabled": false,
      "autoApprove": [
        "search_documentation",
        "list_sources",
        "extract_urls",
        "remove_documentation",
        "list_queue",
        "run_queue",
        "clear_queue",
        "add_documentation",
        "add_repository",
        "list_repositories",
        "update_repository",
        "remove_repository",
        "watch_repository",
        "get_indexing_status"
      ]
    }
  }
}

in claude desktop

{
  "mcpServers": {
    "rag-docs": {
      "command": "node",
      "args": ["/path/to/your/mcp-ragdocs/build/index.js"],
      "env": {
        "EMBEDDING_PROVIDER": "ollama", // default
        "EMBEDDING_MODEL": "nomic-embed-text", // optional
        "OPENAI_API_KEY": "your-api-key-here", // required for fallback
        "FALLBACK_PROVIDER": "openai", // recommended for reliability
        "FALLBACK_MODEL": "nomic-embed-text", // optional
        "QDRANT_URL": "http://localhost:6333"
      },
      "autoApprove": [
        "search_documentation",
        "list_sources",
        "extract_urls",
        "remove_documentation",
        "list_queue",
        "run_queue",
        "clear_queue",
        "add_documentation",
        "add_repository",
        "list_repositories",
        "update_repository",
        "remove_repository",
        "watch_repository",
        "get_indexing_status"
      ]
    }
  }
}

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