"How to use GitHub to pull, push code, create PRs, and trigger actions" matching MCP servers:

This MCP server lets AI agents connect to Figma to read, analyze, create, and modify designs, including elements, styles, assets, and code generation. It works with free Figma accounts and supports parallel multi-agent use across MCP-compatible clients.

Enables AI assistants to query PostgreSQL, MySQL, SQL Server, Oracle, and MongoDB databases through MCP with read-only, audited access.

Enables AI assistants to create projects, deploy files, container images, or Git repositories, attach domains, set write-only secrets, add Postgres, read logs, metrics, and failure summaries, and roll back.

Enables searching and retrieving US federal enforcement actions from DOJ and SEC primary sources, including recent actions and SEC proceedings.

Enables agents to transform tabular Markdown content into structured, type-inferred records with normalized formatting through an MCP-compatible interface.

Enables converting Markdown and HTML tables into structured JSON records with automatic column type inference and format normalization. It also offers supporting web-agent primitives such as DOM semantic pruning, form field auto-mapping, and execution trajectory evaluation, all via a zero-dependency MCP server.

Enables agents to break high-level business objectives into dependency-ordered sub-task graphs and then directly generate the finished deliverables, such as financial spreadsheets, executive presentations, and analytical reports. It runs as a zero-dependency Python MCP server over JSON-RPC stdio, adding deterministic authorization, role-boundary validation, and telemetry.

GitHub's official MCP Server

Analyzes Git pull request diffs to detect breaking REST and GraphQL API schema changes, providing deterministic AST-level code review and breaking change alerts for CI/CD workflows.

embedded code search engine CLI -AST based that just works - improves speed and efficiency for coding agent

Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.

Connects LLMs and AI agents directly to GitHub repositories, enabling repository inspection, file and tree exploration, code search, commit history, issues, pull requests, and releases for both public and private repos.

A production-grade MCP server for the Code-Fundi API, enabling AI agents to map codebases, search semantically, and analyze blast radius. It provides tools for repository management, AI-powered research, and impact analysis before shipping changes.

Persistent project memory + architectural decisions + pre-execution safety hooks for Claude Code. Local-only storage, multi-repo workspace, automatic knowledge extraction via background auditor.

Enables AI assistants to surgically extract and analyze code, reducing token usage and costs by up to 200x compared to reading entire files.

Thin MCP server that enables AI agents to generate video, image, and audio content via the Deepy API using a personal API key, with safe generation flow and no business logic.

This MCP server is designed for planning with Claude Code, Cline, or Cursor and making changes with Cerebras to maximize speed and intelligence while avoiding API limits. It uses the Qwen 3 Coder model for high-quality code generation and can be embedded in IDEs.

Injects the Code-Me brand identity, tone, and visual guidelines into LLMs with zero latency using built-in context files.

Publishes what an AI made — a page, a markdown or PDF doc, or a whole site — to a live HTTPS link. Runs locally over stdio from the @drop2run/mcp npm package, or hosted at https://mcp.dropto.run/mcp for chats that connect by URL.

Deterministic code review MCP server that provides tools for file selection, rule matching, comment positioning, and reflection, ensuring stable review quality without LLM calls.