"List of This Week's 15 Most Popular Free Minecraft Servers" matching MCP servers:

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 that bridges ChatGPT Web Pro to local tools, enabling file read/write, shell command execution, git operations, and search within a specified project directory.

An MCP execution layer that lets capable AI models safely control a developer workstation for file edits, terminal and process execution, Git operations, language-server analysis, browser and Windows UI automation, media processing, job/resource control, and checkpointing. It also coordinates durable single- or multi-agent tasks across providers with leases, dependency graphs, evidence logs, repair loops, and separate verification gates.

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.

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

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.

Enables AI agents to interact with GitHub repositories, issues, pull requests, code, and more through a comprehensive set of tools.

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 read-only access to the canonical-vault GitHub repository through MCP, letting clients list files, retrieve file contents and history, inspect commits, and search code.

Enables coding agents to receive scored, verified library recommendations, compare repositories side by side, and list trending GitHub repositories by day, week, or month.

A Model Context Protocol server that connects GitHub code to Claude.ai. This server utilizes the Pera1 service to extract code from GitHub repositories and provide better context to Claude.

MCP server that acts as a thin proxy over GitLab REST API v4, enabling users to list merge requests, view diffs, and leave inline comments without leaving their MCP client.

MCP server that ranks and deduplicates your GitHub pull request review queue across direct requests, team requests, and your own waiting PRs into a single prioritized list via one get_review_queue tool.

MCP server for the Berbotu vault, providing tools to ping health, list demos and releases, and add new demos via GitHub commits over stdio.

MCP server for code review of Bitbucket Cloud pull requests: list PRs, read diffs, file contents and comments, and post review comments.

This server enables GitHub issue triage with three focused tools: searching issues, summarizing an issue with recent comments, and drafting comments with dry-run/gated posting, using shaped payloads and retries to keep context small.

This MCP server analyzes Git reflog and object data to provide recovery signals after accidental resets or deletions, helping assess whether lost commits or branches may still be recoverable without exposing sensitive details.

An MCP server that turns any public GitHub repository into a PDF report containing a codebase summary, the most recent commits, and suggested improvements — generated locally by an Ollama model.