nkapila6/mcp-local-rag

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
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.
Run Directly via uvx
This is the easiest and quickest method. You need to install uv for this to work.
Add this to your MCP server configuration:
Using Docker (recommended)
Ensure you have Docker installed.
Add this to your MCP server configuration:
Agent Skills
This repository includes **Agent Skills** that teach Claude how to effectively use the mcp-local-rag tools for intelligent web searches and deep research. Skills are folders of instructions that Claude loads dynamically to improve performance on specialized tasks.
Available Skills
**local-rag-search** - Teaches Claude best practices for:
- **Smart tool selection**: Choosing between quick searches or comprehensive deep research
- **Multi-engine research**: Using multiple search backends for diverse perspectives
- **Effective query formulation**: Writing natural language queries that yield better results
- **Parameter tuning**: Adjusting num_results, top_k, and backend selection for different use cases
- **Privacy-aware searching**: Defaulting to privacy-focused engines while allowing comprehensive searches when needed
Deep Research Use Cases
The skill enables comprehensive topic research using multiple search terms and engines. It's particularly useful for technical deep dives that leverage Google's documentation coverage, multi-perspective analysis that compares information across different search engines, privacy-focused research using DuckDuckGo or Brave, and factual verification by cross-referencing Wikipedia and other authoritative sources.