octocode-mcp and srclight
These are **competitors** — both provide semantic code search and indexing capabilities for MCP servers, but OctoCode emphasizes real-time LLM-based search across public/private repositories while Srclight focuses on local deep indexing with hybrid FTS5+embedding search and advanced analysis tools like call graphs and git blame.
About octocode-mcp
bgauryy/octocode-mcp
MCP server for semantic code research and context generation on real-time using LLM patterns | Search naturally across public & private repos based on your permissions | Transform any accessible codebase/s into AI-optimized knowledge on simple and complex flows | Find real implementations and live docs from anywhere
This project helps software developers enhance their AI assistants by providing a comprehensive understanding of codebases. It takes code from GitHub, GitLab, and local repositories and processes it to allow AI assistants to perform tasks like code search, understanding implementations, and reviewing pull requests with deep context. This tool is for software engineers, tech leads, or engineering managers who want their AI assistants to operate with the expertise of a senior staff engineer.
About srclight
srclight/srclight
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-accelerated semantic search, 10 languages via tree-sitter. Fully local, zero cloud dependencies.
This helps AI coding assistants work faster and more effectively by providing a deep, searchable index of your codebases. It takes your source code and documentation files as input, instantly delivering precise answers to complex queries about code structure, relationships, and semantic meaning. Developers who use AI coding agents like Claude Code or Cursor will find this indispensable.
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