Serveurs MCP GitHub

Lets an AI client launch, message, and stream events from durable agents on any model, tool, or machine via the Omnara API.

Lets AI coding agents search open-source code, docs, packages, and vulnerabilities with cited evidence.

Wraps git, GitHub, GitLab, Bitbucket and Jira actions so an AI client can manage repos, work items, commits, issues and pull requests.

Queries GitHub Security Advisories from a local cloned database to identify vulnerabilities in software ecosystems.

Provides guided exercises to build features using GitHub Copilot CLI, custom agent skills, and the Playwright MCP server.

Packs a local or remote codebase into a single AI-friendly file with token counts so LLMs and coding agents can read or search it.

Connects AI clients to GitHub so they can read repositories, manage issues and pull requests, and inspect workflows.

Generates architecture diagrams, explanations, Mermaid source, and narrated videos for GitHub repositories.

Tracks emerging AI models, products, and repositories to identify trending search terms before they appear in traditional keyword tools.

Connects AI agents to external tools like Gmail, GitHub, Google Sheets, and Slack to perform actions and manage data.

Enables AI agents to research local and external codebases through AST search, LSP semantics, and efficient GitHub repository analysis.

Emulates enterprise SaaS APIs like Slack, GitHub, and Jira locally for testing integrations and evaluating AI agents without vendor accounts.

Automates trivial Git merge conflict resolution and provides AI-assisted workflows for branch management, pull requests, and code reviews.

Integrates multiple search providers like Tavily, Brave, and GitHub into LLMs using a sandboxed JavaScript execution environment.

Allows an AI agent to manage hosting services including GitHub app deployments, PostgreSQL databases, domains, mail, and billing.

Wraps the gh CLI to give AI clients structured, token-efficient JSON for GitHub pull requests, issues, and Actions workflows.

Lets AI clients run structured GitHub operations like pull requests, issues, and actions as typed JSON.

Lets an AI client manage GitHub Projects, issues, sprints, and releases, and coordinate a swarm of coding agents with task checkout and budgets.

Manages open source contributions by tracking pull requests, discovering issues, and providing AI-driven triage and response tools.

Let your AI assistant create GitHub profile and repository cards for READMEs, link previews, and social posts using live GitHub data.

Helps open-source contributors navigate repository rules, prepare proposals, and verify changes to earn maintainer trust.

Turns documentation sites, GitHub repos, PDFs, and other sources into packaged AI skills and RAG-ready knowledge assets.

Lets an AI client call real web APIs, including Slack, GitHub, and Jira, through the user's authenticated browser session.

Provides a security-graded directory of open-source Claude skills, MCP servers, and AI agent tools with quality scoring and automated updates.

Exposes the MDMA specification, authoring prompts, package metadata, and documentation to AI assistants.

Provides AI agents with persistent project memory through knowledge graphs, semantic search, and deep GitHub integration.

Connects coding agents to a live registry of reviewed engineering skills to discover, verify, and apply proven fixes for software failures.

Syncs and manages task context across multiple platforms like TickTick, Notion, and GitHub using hybrid retrieval and a unified task hierarchy.

Search, rank, and compare open-source AI projects using Archestack's curated rankings and GitHub data.

Enables AI agents to triage issues, fix bugs, verify SARIF scanner reachability, and perform semantic code recall within a repository.

Lets an AI client browse public GitHub repositories, list directories, and read code or text file contents.

An acceptance test agent that drives real browsers to verify code changes and automatically manages pull request feedback loops.

Analyzes codebases to provide dependency graphs, security scanning, architecture insights, and multimodal knowledge graph ingestion for LLM agents.

Allows coding agents to host artifacts like screenshots, recordings, and logs, then automatically attach them to GitHub pull requests as managed comments.

Enables AI clients to read web content by fetching URLs as clean markdown using a multi-tier fallback system.

Scans GitHub, Hacker News, npm, PyPI, and Stack Overflow to score whether an app idea already exists and suggest pivots.

Enables AI agents to manage local git repositories and interact with GitHub, GitLab, Gitea, and Forgejo through a unified set of tools.

Installs and verifies a curated set of MCP servers for DeepSeek Harness profiles with one command.

Acts as a high-performance federated GraphQL gateway that allows AI agents to surgically query and introspect large, complex GraphQL schemas.

Provides AI agents with bounded, auditable access to propose changes to an Obsidian vault stored in GitHub using expiring bearer tokens.

Enables AI clients to perform web scraping, browser automation, computer vision, social sentiment research, and visual regression testing via a remote API.

Generates detailed setup manuals for GitHub repositories, providing platform-specific installation steps for macOS, Windows, and Linux.

Lets coding agents plan and run marketing workflows for a project, from organic growth and content to social posts and paid ads.

Allows a coding agent to read, act upon, and resolve review comments collected on preview deployments.

Runs real-browser acceptance tests on coding-agent changes and posts screenshots and a verdict to the pull request.

Enables Pi to perform web searches, read URLs, browse public GitHub repositories, and analyze images or videos using Z.AI tools.

Prevents coding agents from introducing known bugs by matching lockfile versions to open GitHub issues and providing workarounds.

Converts webhooks from various services into MCP Events that AI agents can subscribe to for real-time reactions.

Enables AI agents to evaluate GitHub issues for availability, project activity, and maintainer responsiveness to avoid duplicate work.

Lets an AI find open-source tools on GitHub and install them as sandboxed MCP tools after security scanning and user approval.