"Python code quality improvement and codebase diagram generation tools" matching MCP servers:

AI building world

A Docker-based MCP server providing codebase memory and search tools. It enables storing/retrieving memories, regex search of code, and file summarization for AI assistants.

MCP server for local codebase memory: semantic indexing, hybrid search, and clean code analysis (static + LLM) with retrievable project notes, designed to run fully local on modest hardware.

Audits your Claude Code memory store with 4-dimension quality scoring and actionable cleanup recommendations, including a visual dashboard.

Provides persistent memory for AI coding agents through the Model Context Protocol, enabling them to store and retrieve project knowledge across sessions.

An MCP server that indexes codebases into a local knowledge graph, providing 52 AI tools for semantic search, call-graph traversal, git archaeology, and impact analysis to give AI agents deep understanding of code.

Enables AI agents to index, search, and retrieve architectural documentation and store self-learning notes from codebases.

High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph — average repo in milliseconds. 159 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies.

MCP server that wraps codebase-memory-mcp to provide code indexing, search, tracing, and architecture analysis tools with automatic reindexing after source changes.

Transforms code repositories and development documentation into a queryable Neo4j knowledge graph, enabling AI assistants to perform intelligent code analysis, dependency mapping, impact assessment, and automated documentation generation across 15+ programming languages.

A simple note-taking MCP server that allows adding notes and summarizing them via a prompt.

Persistent project memory + architectural decisions + pre-execution safety hooks for Claude Code. Local-only storage, multi-repo workspace, automatic knowledge extraction via background auditor.

A local, cross-editor MCP server that provides persistent memory for coding agents, capturing and recalling decisions, conventions, and fixes across sessions without API keys.

Provides semantic code search and code insights via a knowledge graph, enabling AI to understand, navigate, and modify complex projects with deep dependency and architecture analysis.

Gives AI coding agents persistent memory by storing observations, decisions, and learnings in a local SQLite database with vector search, full-text search, and a rules engine.

An advanced MCP server implementing diagrammatic reasoning with memory-augmented spatial exploration, enabling structured chain-of-thought reasoning through visual reasoning spaces.

MCP server for semantic code search and dependency graph analysis. Indexes codebases into a knowledge graph with vector embeddings for AI-powered code understanding.

Provides persistent codebase context caching via Gemini API, enabling fast, cost-effective repeat queries for MCP hosts like Claude Code.

A Model Context Protocol server that enables AI agents to query a Graphiti knowledge graph and pgvector document store for evidence-backed responses via hybrid search and RAG.

Enables AI coding agents to keep persistent, verifiable memory of a codebase, including the reasons behind code, prior rejected approaches, and invariants, anchored to the code and carried along as the code moves.