"Minecraft Protocol Servers Written in Python" matching MCP servers:

Provides 7 MCP servers with 95 tools for git, GitHub, .NET, Ollama, Rust, template sync, and Python, enabling natural-language commands to perform real development operations.

A workspace of six MCP servers—grounded-cv (hybrid RAG with citations), repo-intel (GitHub repo intelligence), web-research (safe web search/extraction), ats-jobs (unified ATS job boards), outcome-ledger (durable task ledger), and coding-workflows (code review & planning)—purpose-built for agentic hiring evaluations.

An MCP server for BitBucket Cloud operations that enables AI agents to manage repositories, branches, pull requests, and search code.

A modular monolith MCP server connecting multiple providers (Redash, PostgreSQL, GitHub) with unified permission, security, and auditing, enabling secure data access and tool execution.

This MCP server provides unified diffs of two text inputs using Python's standard library difflib.

MCP servers for querying and submitting Ubuntu data via ubq, covering bugs, packages, versions, and merge requests with multiple authentication providers.

A Python implementation of an MCP server that enables secure, local Bitbucket integration for AI applications, providing tools for repository management, branch creation, file operations, issue tracking, and pull request creation.

Summarizes Slack activity and GitLab merge requests with OpenAI to help generate daily standups, weekly reports, or quarterly check-ins.

Python-based server that provides AI-native access to Alfresco content management operations through the Model Context Protocol, enabling search, document lifecycle management, version control, and other content operations.

Enables secure integration between GitHub and Jira with permission controls, allowing users to manage repositories, create issues and pull requests, and handle Jira project workflows through natural language. Supports OAuth authentication and comprehensive security enforcement for both platforms.

Enables interaction with GitHub through the GitHub API, supporting file operations, repository management, advanced search, and issue tracking with comprehensive error handling and automatic branch creation.

Enables AI agents to interact with GitHub, providing tools to list and get repository details using a personal access token.

A GitHub-based implementation of the Model Context Protocol that enables LLMs to access and manipulate data in a Universal Object Reference (UOR) framework, providing standardized interfaces for object management with decentralized storage.

A server implementation demonstrating how AI models can interact with external tools and services through Model Context Protocol, featuring integrations for calculator functions, GitHub repositories, and Google Maps searches.

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

A Model Context Protocol server for Git repository interaction and automation. This server provides tools to read, search, and manipulate Git repositories via Large Language Models.

Enables ChatGPT to securely operate a single Windows development workspace via a local MCP server, offering file editing, Git status, static analysis, approved test/build, and limited ADB operations with audit logging.

Transforms any GitHub repository into a documentation hub for AI assistants, enabling up-to-date access to documentation and code to eliminate hallucinations.

Coordination protocol for parallel coding agents, built above Git. The MCP server exposes the full 17-tool lifecycle over stdio: register agents, publish intents with semantic scopes and declared operations, claim work, check for conflicts before code is written, publish ChangeSets, run trusted named verification checks, and record accepted work. Deterministic rules raise findings when two agents'

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.