"Python" matching MCP servers:

Exposes repository reconnaissance tools — file listing and verbatim reading, regex search, dependency-tree parsing across Python/Node/Rust/Go, and test-coverage ingestion — so agents can gather line-numbered evidence from real source files. This lets an audit pipeline physically re-verify every claim and drop findings that cannot be located in the code.

Enables AI-driven Python debugging with debugpy, allowing Claude Code to control breakpoints, stepping, variable inspection, and expression evaluation.

Enables comprehensive security vulnerability scanning and code quality analysis for Python applications. Provides detailed reports with scoring, actionable suggestions, and comparison tracking specifically designed for backend developers working with frameworks like Django, Flask, and FastAPI.

Enables AI assistants to interact with Azure DevOps projects, including work items, test results, Git repositories, and dependency analysis via the Model Context Protocol.

Enables AI agents to hire verified human operators for tasks requiring physical presence, human perception, or judgment, such as real-world verification, product testing, and data collection.

Audits a module against its test suite and reports the cases the tests are structurally unable to see, then proves each gap with a real failing test rather than a warning. Covers Python, TypeScript, JavaScript, Java, Rust and Go.

Visual CVE audit dashboard for npm, Python, Go, and Rust projects. Scans your project manifests (package-lock.json, requirements.txt, go.sum, Cargo.lock) against OSV.dev live data, opens a browser dashboard for human review, then applies fixes only after explicit confirmation. Supports multi-service monorepos in one command.

Enables chat assistants to insert graded coding exercises (Python, JavaScript, TypeScript, SQL) with hidden tests, and returns failed attempts to the conversation so the tutor can explain the learner's specific mistake.

An MCP server that enables AI assistants to discover and execute Nox sessions for project automation tasks like testing, linting, and building. It provides tools to list available sessions and run them using specific Python versions, tags, or keyword expressions.

Enables AI coding agents to diagnose and repair Python Selenium UI automation using real evidence from live DOM and test runs, with enforced safety boundaries and verifiable fixes.

Enables real-time code analysis for JavaScript, TypeScript, and Python through Claude Desktop and other MCP clients, detecting bugs, code smells, and security vulnerabilities with automated quick fixes.

Runs a regular expression on real engines — JavaScript (V8), Python (CPython re), PCRE2 and RE2 — reporting each engine's own compile errors with positions, every match with its groups and named groups, replacement results, and where the engines disagree. It also detects catastrophic backtracking (ReDoS), naming the at-risk part of the pattern, generating an attack string, and timing how long each engine actually takes on it.

An MCP server that gives AI coding agents the ability to analyze a Python repository's test health: coverage, flaky tests, and ML-based pull-request risk prediction.

Enables coding agents to drive and inspect running Shiny apps (R and Python) by setting inputs, clicking, reading outputs, and getting detailed error information.

MCP server that provides audit and safety-check tools for enterprise SDLC code integrity, enabling AI agents to scan workspaces for lifecycle gaps, mock-theater tests, DRY violations, and language-specific issues in shell, JavaScript/HTML, and Python.

Python MCP server for running and inspecting Bruno API collections

Voice-powered bug reporting MCP server with 13 tools. Captures console logs, network errors, DOM traces, and developer voice descriptions. AI reads structured reports to find and fix bugs automatically. Chrome Extension + Python CLI.

A minimal MCP server built with the official Python SDK that runs over stdio and exposes a health capability, providing a practical integration-testing target for AI and agent codebases.

Zero-sidecar MCP server embedded directly in the Godot 4 editor as a GDScript EditorPlugin — no Node or Python sidecar. Reflection-driven tools over any engine class, validate-before-write GDScript, scene/script/resource authoring, and a runtime play-test loop (play, screenshot, input, assert).

Enables AI assistants to see, control, and debug PySide6 desktop applications without modifying their source code, by capturing screenshots, inspecting widget trees, performing clicks and typing, reading logs, and running Python inside the app process.