codebase-memory-mcp
★ 47.7k
vs
matryca-plumber
★ 100
codebase-memory-mcp vs matryca-plumber
codebase-memory-mcp: codebase-memory-mcp is a structural analysis backend that indexes codebases into a persistent knowledge graph, drastically reducing token usage for code exploration by providing precise structural results. It integrates with AI assistants like Claude Code, offering advanced capabilities such as call graph tracing, architecture overviews, and dead code detection.; matryca-plumber: Matryca is a headless MCP server and CLI that turns a local Logseq graph into an agentic workspace. It operates without network APIs or background desktop app, using atomic AST writes and X-Ray token compression. It provides spatial intelligence, sandboxed privacy, and zero-database lexical engine.
01
TL;DR
codebase-memory-mcpMemory & Context · ★ 47.7k
When to choose:
- Your agent burns tokens searching a medium or large codebase: one graph query replaces many grep and read steps, according to the README.
- You want everything local: a single static binary with no runtime dependencies or API keys.
- You work in many languages and with several coding agents, which the installer configures automatically.
When to skip:
- You do not want an installer to edit your agents' config files and add hooks; the README offers --skip-config to install only the binary.
- You need project decisions and conventions rather than code structure; a scaffold such as mex is closer.
- You are cautious about unsigned binaries: some antivirus engines have flagged the release, which the project documents as a false positive.
matryca-plumberMemory & Context · ★ 100
Privacy-preserving AI knowledge management
02
Side-by-Side Comparison
Field
codebase-memory-mcpmatryca-plumberCategory
Memory & Context
Memory & Context
Stars
★ 47.7k
★ 100
License
MIT
Apache-2.0
Install Command
curl -fsSL https://raw.githubusercontent.com/DeusData/codebase-memory-mcp/main/install.sh | bash
git clone https://github.com/MarcoPorcellato/matryca-logseq-llm-wiki.git && cd matryca-logseq-llm-wiki && make install
Updated
1d ago
1d ago
Open Source
Yes
Yes
Tags
knowledge-graph, codebase-analysis, AI-assistant-tools
agentic-memory, ai-agents, andrej-karpathy
03
Features
codebase-memory-mcp01Indexes a codebase into a persistent knowledge graph using tree-sitter, with semantic type resolution for several major languages
02Supports 150+ languages with grammars compiled into a single static binary
0317 MCP tools: search, call tracing, architecture overview, impact analysis, dead code detection, Cypher queries and more
04Indexes infrastructure-as-code such as Dockerfiles and Kubernetes manifests
05Built-in 3D graph visualisation served locally
matryca-plumber01AST Spatial Intelligence
02100% Headless & Local-First
03X-Ray Token Economy
04Sandboxed Privacy
05Agent-Native CLI
04
Use Cases
codebase-memory-mcp↳Code exploration and understanding: Quickly understand codebase architecture, find functions, and trace call paths without high token costs.
↳Impact analysis and refactoring: Map git diffs to affected symbols, detect dead code, and analyze function fan-out to aid refactoring efforts.
↳AI assistant integration: Enhance AI assistants like Claude Code with precise structural queries for more effective code-related questions.
↳Architecture Decision Records management: Store, update, and retrieve architectural decisions directly within the codebase context.
↳Automated scripting and CI/CD: Utilize CLI mode for single-shot graph operations in scripts or CI/CD pipelines.
matryca-plumber↳Privacy-preserving AI knowledge management
↳Agentic writing and refactoring of Logseq pages
↳Local-first automation with MCP clients like Claude Desktop
05
Best For
codebase-memory-mcpMost Popular
matryca-plumber—
FAQ
FAQ
What is the difference between codebase-memory-mcp and matryca-plumber?
Both codebase-memory-mcp and matryca-plumber are in the Memory & Context category. codebase-memory-mcp has 47.7k stars, while matryca-plumber has 100 stars.
Which is better, codebase-memory-mcp or matryca-plumber?
The best choice depends on your use case. Choose codebase-memory-mcp if Code exploration and understanding: Quickly understand codebase architecture, find functions, and trace call paths without high token costs., and matryca-plumber if Privacy-preserving AI knowledge management.
Is codebase-memory-mcp free or open source?
Yes, codebase-memory-mcp is open source on GitHub (MIT).
Is matryca-plumber free or open source?
Yes, matryca-plumber is open source on GitHub (Apache-2.0).
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