"GitHub Sponsors" matching MCP servers:

Turns raw GitHub commit history into a categorized, human-readable changelog directly inside Claude or any MCP-compatible client.

An MCP server that reads public GitHub Projects v2 boards (including item-level data like status and custom fields) without authentication, using official APIs and fallback methods for user-owned projects.

MCP server for exploring GitHub public data. It provides tools to fetch user profiles, list top repositories, and calculate language usage statistics, which AI agents can invoke dynamically.

An MCP server that enables AI assistants to interact with GitHub via a fine-grained personal access token — pushing commits, managing branches, opening and merging PRs, creating issues, and reading repositories. It runs locally with no telemetry and supports a read-only mode.

MCP server that enables AI assistants to look up and analyze GitHub repositories, including stars, forks, description, open issues, and README content.

An MCP (Model Context Protocol) server for handling GitHub URLs with validation and parsing capabilities. This server provides tools to convert between GitHub repository information and URLs, with intelligent validation to distinguish between public repositories, private repositories, and non-exist

Enables AI agents to analyze employee GitHub activity including PRs, code reviews, comments, and contributions across repositories with time-range filtering for performance assessment and impact analysis.

Wraps GitHub Copilot CLI as an MCP server, enabling MCP clients to run Copilot conversations for code tasks with support for session resumption and permission modes.

Enables AI agents to analyze public GitHub repositories directly through tools for repo health scoring, recent commit summaries, good first issue discovery, and semantic Q&A over docs and issues.

Local MCP server for safe GitHub developer workflows. Enables pulling main, creating feature branches, pushing them, and opening ready-for-review pull requests via tools like github_create_feature_branch and github_create_pull_request.

An MCP server that caches your GitHub starred repositories in a local SQLite database and lets you search, list, and retrieve details about them through any MCP client (Claude Desktop, Cursor, VS Code, etc.), with automatic freshness checks via GitHub's ETag mechanism.

Converts Jenkins declarative pipelines into GitHub Actions workflow YAML files, facilitating migration from Jenkins to GitHub Actions CI/CD.

A production-ready MCP server for triaging and reviewing GitHub pull requests via the GitHub REST API, providing typed tools to list, inspect, comment, add labels, and submit reviews.

Enables answering 'what needs me right now?' across GitHub issues by determining whose turn it is and returning ready-to-read Markdown reports.

A read-only MCP server that lets AI assistants inspect local workspace files, search context, view git diffs, and fetch a fixed GitHub profile, all within a sandboxed stdio transport.

An MCP server that lets Claude (or any MCP client) manage GitHub branch protection rulesets programmatically.

Enables AI assistants to query GitHub repositories, issues, pull requests, CI status, and discover trending repos via natural language. Provides MCP tools, resources, and prompts for GitHub data access.

Lets MCP clients such as Claude or ChatGPT find the pull requests waiting on your review, read their details and changed files, check CI status, post comments, and submit approve, request-changes, or comment reviews. It runs locally over stdio with a personal token or as a remote server with its own OAuth 2.1 authorization server (PKCE, dynamic client registration, per-client consent, and refresh-token rotation) so GitHub is only used to sign the user in.

Enables querying GitHub repositories for pull requests, commits, and comparisons to understand code changes.

Enables local AI agents to manage GitHub Codespaces workspaces and execute remote tasks by checking out exact commits, running builds, tests, scripts or temporary services, downloading logs and artifacts, and stopping or exporting managed environments.