mcp-local-rag and knowledge-to-action-mcp

mcp-local-rag
56
Established
Maintenance 13/25
Adoption 10/25
Maturity 16/25
Community 17/25
Maintenance 13/25
Adoption 3/25
Maturity 18/25
Community 12/25
Stars: 118
Forks: 19
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stars: 3
Forks: 1
Downloads:
Commits (30d): 0
Language: TypeScript
License: MIT
No Package No Dependents
No risk flags

About mcp-local-rag

nkapila6/mcp-local-rag

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

Implements multi-engine web search across 9+ backends (DuckDuckGo, Google, Bing, Brave, Wikipedia) with semantic ranking using Google's MediaPipe text embeddings, extracting markdown from fetched URLs without external APIs. Exposes tools like `deep_research`, `deep_research_google`, and `rag_search_ddgs` as MCP resources compatible with Claude Desktop, Cursor, and other MCP clients. Deployable via `uvx` or Docker and includes Agent Skills that guide LLMs on query formulation and backend selection for privacy-aware or comprehensive research.

About knowledge-to-action-mcp

tac0de/knowledge-to-action-mcp

MCP server for Obsidian GraphRAG, agent-ready context, preview-only planning, and safe repo handoffs

Combines graph-aware note retrieval with optional embeddings-based semantic reranking to surface contextual neighbors, then structures results into agent-ready packets containing briefs, risks, and repo file hints. Implements preview-only action planning and bounded workspace inspection (ripgrep, git status) without exposing shell access, integrating via stdio with Claude, VS Code, and Cursor.

Scores updated daily from GitHub, PyPI, and npm data. How scores work