"python" matching MCP servers:

A DevOps-friendly template for building MCP servers with CI/CD, Docker support, and automatic documentation generation using fastmcp and FastAPI.

Enables automated Python code quality checks including linting, complexity analysis, typo detection, structure validation, duplicate detection, and test coverage, with integration into Cursor IDE and CLI.

Enables AI coding tools to scaffold, build, and deploy Node.js or Python apps to Varity with a single command, automatically provisioning databases and backend services.

Enables scanning Python repos for dead code and automatically drafting a branch + PR for the safe subset (unused single-name imports) after running the repo's full test suite. All other findings are reported without modification, and a human always merges.

Local CI/CD engine for AI agents. ActionD listens to LGH git events and runs plugin jobs (Go/Python/Java/web toolchains) in isolated checkouts, with structured results, root-cause failure diagnosis, approval gates, and auto-rollback. The MCP server exposes 23 tools, including dev_cycle_run (commit → CI → structured verdict in one call) and actiond_diagnose for failed-job analysis.

MCP server for GitLab CI/CD — pipelines, jobs, schedules, branches, tags, merge requests and repository files. Works with any GitLab (SaaS gitlab.com or self-hosted) via python-gitlab.

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.

Python MCP server for GitHub operations, providing native tool integration with Claude Code and other MCP clients. It enables managing issues, pull requests, CI status, milestones, and batch operations via natural language.

A local Python MCP server that exposes the Codemagic CI/CD REST API as Claude-callable tools. Trigger builds, manage apps, download artifacts, and clear caches — all from Claude Code or Claude Desktop without leaving the chat.

Enables AI agents to manage Databricks Lakeflow jobs by building and uploading Python wheels and triggering runs with specific arguments. It provides a structured way to orchestrate complex data experiments and monitor execution directly on Databricks clusters.

Python MCP server for Selenium WebDriver — 84 tools for browser automation, element interactions, assertions, self-healing locators, and codegen for Java TestNG / JUnit 5 / Cucumber / pytest / C# NUnit / Playwright and CI pipelines (GitHub Actions / Jenkins / GitLab CI). No ChromeDriver setup needed.

A Python MCP server that wraps the GitHub CLI (gh) to provide structured tools for searching, reading, and managing GitHub resources like repos, issues, PRs, releases, and workflows, with write commands disabled by default.

Enables managing SAP Cloud Integration iFlows, packages, configurations, deployments, and runtime artifacts via natural language through the OData API.

An MCP server that executes tox commands to run Python tests within a project using pytest, allowing users to run all tests or specific test groups, files, cases, or directories.

An MCP server that complements Epic's official Unreal Engine MCP server with 78 additional tools across 14 subsystems for build/cook/package, cinematics, Niagara, automation testing, source control, profiling, World Partition, and project maintenance, using Unreal's built-in Python and Remote Control plugins.

Enables AI agents and MCP-compliant clients to autonomously evaluate SLA breach incidents, escalate alerts, and execute canary rollback playbooks with deterministic, zero-dependency Python tooling.

A production-ready template for building Model Context Protocol (MCP) servers in Python, using Docker Compose for containerized development and CI/CD.

Magga lets coding agents prove their changes before claiming they’re done by building the code and verifying that newly added tests fail before the fix and pass after it. It returns evidence-backed verdicts through the verify_change tool and supports 16 languages, including Rust, Go, Python, Solidity, and C/C++.

An intelligent continuous integration server that provides automated Python code analysis, linting, and static type checking through the Model Context Protocol. It enables AI assistants to perform quality assessments and run tests using tools like pylint, mypy, and pytest.

Provides real-time Python package vulnerability data, enabling AI agents to check CVEs, CVSS scores, and safe versions for informed dependency decisions.