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

A Model Context Protocol (MCP) server designed to easily dump your codebase context into Large Language Models (LLMs).

An MCP server for securely executing Python code, supporting STDIO, Streamable HTTP, and SSE transports, with easy deployment on Heroku.

Enables coding agents to turn OpenSpec intents and Git changes into revision-bound proofs by planning, selecting, and running the smallest safe protection set, then verifying composite verdicts and explaining evidence or unresolved states.

Enables coding agents to run deterministic, zero-dependency AST static analysis over source code, building call graphs and dependency metrics to find orphaned functions, unreachable methods, breaking API surface diffs, and token-bloat clusters, then return a structured refactoring plan. It plugs into MCP clients like Claude Desktop, Cursor, and Windsurf via a single Python entrypoint.

Enables real-time China nationwide air quality monitoring via CNEMC, with AQI, pollutant concentrations and levels, quality ratings, city rankings, and station-level details.

Enables deterministic AST static analysis and call-graph auditing to identify orphaned functions, unreachable methods, and token-bloat clusters, producing refactoring plans that reduce context waste.

embedded code search engine CLI -AST based that just works - improves speed and efficiency for coding agent

MCP server that exposes tools to route natural language queries to typed IDs, describe catalog entries, and list repository verification commands for the m-dev-tools organization.

Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.

Deterministic code review MCP server that provides tools for file selection, rule matching, comment positioning, and reflection, ensuring stable review quality without LLM calls.

A production-grade MCP server for the Code-Fundi API, enabling AI agents to map codebases, search semantically, and analyze blast radius. It provides tools for repository management, AI-powered research, and impact analysis before shipping changes.

Enables LLMs to query live data from over 250+ sources via CData Python Connectors using natural language. Wraps connectors as a Model Context Protocol server.

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

Enables AI assistants to surgically extract and analyze code, reducing token usage and costs by up to 200x compared to reading entire files.

Enables generating images from text prompts using various AI models (FLUX, Recraft, GPT Image, etc.) and automatically delivering them through Cloudinary's platform.

Enables secure execution of Python code in a sandboxed WebAssembly environment using Pyodide and Deno. Automatically handles package management and captures complete execution results including stdout, stderr, and return values.

Exposes the SiftingIO market-data SDK to AI assistants, enabling live prices, fundamental data, and market information retrieval.

Provides deterministic tools for transforming, formatting, and inspecting structured data for AI agents.

Enables users to translate geometric bounding boxes, flowchart node connections, and architectural sketches into clean Mermaid graphs, JSON topology matrices, and boilerplate code scaffolds through MCP.

Provides a collection of MCP servers for computational chemistry tasks including molecular generation and retrosynthesis. Also offers property prediction and molecule pricing capabilities.