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srclight/srclight

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Deep code indexing MCP server for AI agents. 25 tools: hybrid FTS5 + embedding search, call graphs, git blame/hotspots, build system analysis. Multi-repo workspaces, GPU-accelerate

S

MCP

srclight/srclight

Added 1 June 2026

#code-indexing #code-intelligence #code-search #developer-tools #embeddings #fts5 #mcp #mcp-server

Overview

A deep code indexing MCP server for AI agents. It provides 25 tools including hybrid FTS5 and embedding search, call graphs, git blame/hotspots, and build system analysis. It supports multi-repo workspaces, GPU-accelerated semantic search, and 10 languages via tree-sitter, all fully local with no cloud dependencies.

Best for

Best for
Developers and AI agent builders who need a local, privacy-preserving code indexing server

Use cases

  • Enabling AI agents to navigate and understand large codebases
  • Performing semantic code search with GPU acceleration
  • Analyzing build systems and git history for hotspots

Notes

A deep code indexing MCP server for AI agents. It provides 25 tools including hybrid FTS5 and embedding search, call graphs, git blame/hotspots, and build system analysis. It supports multi-repo workspaces, GPU-accelerated semantic search, and 10 languages via tree-sitter, all fully local with no cloud dependencies.

44 stars on GitHub. Last updated 2026-04-27. Licensed MIT.

Use cases

  • Enabling AI agents to navigate and understand large codebases
  • Performing semantic code search with GPU acceleration
  • Analyzing build systems and git history for hotspots

Pros

  • Fully local with no cloud dependencies ensures privacy and offline use
  • Wide range of tools from search to call graphs and git analysis
  • GPU-accelerated semantic search for fast code retrieval

Cons

  • Small community and limited adoption may mean fewer resources
  • GPU acceleration required for optimal performance, not available on all setups
  • Language support limited to 10 languages via tree-sitter

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Fully local with no cloud dependencies ensures privacy and offline use
  • Wide range of tools from search to call graphs and git analysis
  • GPU-accelerated semantic search for fast code retrieval

Cons

  • Small community and limited adoption may mean fewer resources
  • GPU acceleration required for optimal performance, not available on all setups
  • Language support limited to 10 languages via tree-sitter