"Using LinkedIn to find GASP animations" matching MCP servers:

An MCP server that enables AI agents to retrieve detailed GitHub Pull Request information using git commit hashes, branch names, or PR numbers. It automatically detects repositories and extracts comprehensive PR data including descriptions, labels, and reviews via the GitHub CLI.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

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

A read-only MCP server for the Bitbucket Cloud REST API v2.0 that enables AI assistants to browse workspaces, repositories, and review pull requests.

Helps support engineers find similar GitHub issues to speed up troubleshooting by searching repositories and calculating similarity scores based on issue descriptions.

Provides a read-only MCP bridge that lets Claude Web inspect workspace files, git state, and recorded test results while Codex remains the sole executor of changes.

Enables MCP-compatible AI clients to connect to a Windows machine for file operations, PowerShell execution, Git inspection, task management, memory, and skills.

A custom MCP server that lets AI assistants interact with GitHub accounts, offering tools for repository creation, file viewing, code search, and issue management.

An MCP server that automates the backup of Cloudflare projects to a GitHub repository, providing a systematic way to preserve Cloudflare configurations and assets.

Enables phone-issued approve/commit/push/pull commands to control an AI coding agent's git actions by bridging GitHub webhooks and MCP tool calls.

Provides full read/write access to the GitHub REST API via a single tool using a personal access token.

Model Context Protocol (MCP) server for GitLab — exposes 1006 GitLab REST & GraphQL API operations as MCP tools (42 meta-tools / 57 enterprise), 24 resources, 38 prompts, and 17 completion types for AI assistants. Written in Go, single static binary, stdio and HTTP transport.

Enables assistants to read Forgejo repositories and manage issues and pull requests directly from the working session, using the caller's own token against any Forgejo instance.

Provides MCP tools to review git changes using OpenAI Codex CLI, enabling code review of unstaged, staged, or last-commit changes.

Enables code search across indexed repositories using regex patterns, with pagination, repository listing, and file context retrieval via Hound integration.

Facilitates interaction with Bitbucket Server for pull request management using the MCP protocol, supporting operations such as creating, merging, commenting, and reviewing pull requests.

Enables LLMs to list, create, and comment on GitHub issues using your own GitHub identity via stdio transport.

Analyzes codebases using Repomix and LLMs to provide structured code reviews with specific issues and recommendations, supporting multiple LLM providers including OpenAI, Anthropic, and Gemini.

Enables developers to find personalized open-source contributions by analyzing GitHub profiles and matching them with relevant 'good first issues' and beginner-friendly repositories. Provides comprehensive contribution tooling including repository health scoring, setup difficulty assessment, impact estimation, and automated PR planning.

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.