codebase-memory-mcp and code-memory
These are competitors offering different architectural approaches to codebase indexing—one uses a knowledge graph with exact matching for speed, the other uses vector embeddings for semantic search—so you'd choose based on whether you prioritize query latency or search relevance.
About codebase-memory-mcp
DeusData/codebase-memory-mcp
MCP server that indexes your codebase into a persistent knowledge graph. 64 languages, sub-ms queries, 99% fewer tokens than grep. Single Go binary, no Docker, no API keys.
Builds an AST-based knowledge graph using tree-sitter parsers with optional LSP-style type resolution for Go, C, and C++, persisting the graph to in-memory SQLite for sub-millisecond structural queries. Indexes codebases at extreme speed through RAM-first pipeline with LZ4 compression and fused Aho-Corasick pattern matching, completing the Linux kernel in 3 minutes. Implements the Model Context Protocol with 14 tools including architecture analysis, call graph tracing, impact mapping from git diffs, and Cypher-like graph queries—integrating with 10 coding agents (Claude Code, Zed, Gemini CLI, and others) through automatic MCP configuration on install.
About code-memory
kapillamba4/code-memory
MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.
Implements a three-tier retrieval strategy (BM25 + dense vectors via SQLite-vec + AST parsing) across specialized tools that route queries by type—code definitions, architectural documentation, and Git history—powered by local sentence-transformers embeddings. Integrates as an MCP server with Claude Desktop, VS Code (Copilot/Continue), Gemini CLI, and Claude Code, supporting 8 languages with full AST extraction and 9+ with fallback whole-file indexing.
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