mcp-local-rag

"primitive" RAG-like web search model context protocol (MCP) server that runs locally. ✨ no APIs ✨

A RAG-based web search and deep research model context protocol (MCP) server that runs entirely locally. Features multi-engine research across 9+ search backends with semantic similarity ranking, and requires no API keys.

• Features
  • Multi-Engine Deep Research
• Installation
  • Run Directly via uvx
  • Using Docker (recommended)
• Agent Skills
• Security audits
• MCP Clients
• Examples on Claude Desktop
  • Result
• Contributing
• License

%%{init: {'theme': 'base'}}%%
flowchart TD
    A[User] -->|1.Submits LLM Query| B[Language Model]
    B -->|2.Sends Query| C[mcp-local-rag Tool]
    
    subgraph mcp-local-rag Processing
    C -->|Search DuckDuckGo| D[Fetch 10 search results]
    D -->|Fetch Embeddings| E[Embeddings from Google's MediaPipe Text Embedder]
    E -->|Compute Similarity| F[Rank Entries Against Query]
    F -->|Select top k results| G[Context Extraction from URL]
    end
    
    G -->|Returns Markdown from HTML content| B
    B -->|3.Generated response with context| H[Final LLM Output]
    H -->|5.Present result to user| A

    classDef default stroke:#333,stroke-width:2px;
    classDef process stroke:#333,stroke-width:2px;
    classDef input stroke:#333,stroke-width:2px;
    classDef output stroke:#333,stroke-width:2px;

    class A input;
    class B,C process;
    class G output;

Features

Multi-Engine Deep Research

The server supports comprehensive multi-engine research capabilities that go beyond simple single-query searches:

• 9+ Search Backends: DuckDuckGo, Google, Bing, Brave, Wikipedia, Yahoo, Yandex, Mojeek, Grokipedia
• Multi-Topic Research: Search multiple related queries simultaneously
• Semantic Ranking: RAG-like similarity scoring ranks the most relevant results
• Privacy Options: Choose privacy-focused engines (DuckDuckGo, Brave) or comprehensive ones (Google)
• No API Keys Required: All processing runs locally with embedded models

Deep Research Tools

1. deep_research - Comprehensive multi-engine research

   • Search across multiple engines simultaneously
   • Ideal for complex topics requiring diverse perspectives
   • Customizable backends and result limits

2. deep_research_google - Google-focused deep dive

   • Leverage Google's comprehensive index
   • Best for technical/scientific queries

3. deep_research_ddgs - Privacy-first deep research

   • Use DuckDuckGo for private, extensive research
   • Great for general topics without tracking

4. rag_search_ddgs & rag_search_google - Quick single searches

   • Fast, focused searches when you need quick answers

Installation

Locate your MCP config path here or check your MCP client settings.