mcp-local-rag and srag

These two tools are complements, as **shinpr/mcp-local-rag** provides a local-first RAG server leveraging the MCP protocol, which **wrxck/srag** is designed to integrate with as a semantic code search and RAG system, also utilizing an MCP server for IDE integration.

mcp-local-rag
62
Established
srag
35
Emerging
Maintenance 10/25
Adoption 10/25
Maturity 22/25
Community 20/25
Maintenance 10/25
Adoption 6/25
Maturity 11/25
Community 8/25
Stars: 156
Forks: 32
Downloads:
Commits (30d): 0
Language: TypeScript
License: MIT
Stars: 20
Forks: 2
Downloads:
Commits (30d): 0
Language: Rust
License: GPL-3.0
No risk flags
No Package No Dependents

About mcp-local-rag

shinpr/mcp-local-rag

Local-first RAG server for developers using MCP. Semantic + keyword search for code and technical docs. Fully private, zero setup.

This tool helps developers quickly find answers within their technical documentation and codebase. You feed it your code, internal specs, research papers, or API docs (PDFs, Word docs, text files, or HTML from websites), and it provides relevant snippets in response to your questions. It's designed for developers who need to search their private, sensitive, or offline project documents.

developer-tools technical-documentation code-search private-data-management knowledge-retrieval

About srag

wrxck/srag

Semantic code search and RAG system written in Rust with tree-sitter chunking, MCP server for IDE integration, prompt injection detection, and secret redaction

This tool helps software developers leverage their existing codebase for AI coding assistants. It indexes all your code repositories and allows your AI assistant to semantically search across them, finding relevant patterns, implementations, and conventions. This means your AI agent can reuse your own code for new features, maintain consistent style, and debug with context, acting as a knowledgeable partner who understands your unique coding practices.

software-development ai-assisted-coding code-reuse architectural-consistency developer-productivity

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