srclight and code-memory
These two tools are competitors, as both are offline, self-hosted MCP servers designed for deep codebase indexing and semantic search to empower AI agents, offering similar functionalities like vector search, Git history analysis, and code graph generation.
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.
About code-memory
kapillamba4/code-memory
MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.
This tool helps software developers quickly find relevant information within their large codebases without manually sifting through files. It takes your code and documentation as input, processes it locally, and then allows you to semantically search for code definitions, architectural patterns, or even Git history. The output is precise code snippets, documentation sections, or commit messages relevant to your query, helping you understand, debug, or extend existing projects more efficiently.
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