"Planning a Trip and Booking a Hotel" matching MCP servers:

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

Gives AI coding agents typed, mode-gated access to a real WordPress site — content, media, users and settings via core REST, plus PHP execution, SQL queries, filesystem operations and Elementor page read/build/patch/snapshot via a companion bridge plugin. Destructive actions and code execution are guarded by feature flags, explicit confirm literals, dry runs, redaction and audit logging.

Provides a secure workspace for AI-driven file management and Python script execution designed to run on Vercel. It enables tools for full file operations and code execution within a sandboxed environment.

Enables agents to accomplish multi-step work by writing a single sandboxed JavaScript program that drives shell, filesystem, HTTP, and every tool of any configured MCP server, returning only a small summary instead of raw JSON. This collapses dozens of advertised tool schemas into one tool, cutting per-request context by roughly 26× while keeping disabled upstream servers reachable.

A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.

A self-hosted MCP server that enables AI coding agents to read, edit, search, and run code in local projects with human review loops and policy controls.

A simple server that acts as a Master Control Program (MCP) for unified interaction with OpenAI and Anthropic (Claude) AI models through a single API endpoint.

A production-ready foundation template for building Model Context Protocol (MCP) servers with FastAPI, featuring modular tools, comprehensive testing, and OpenShift deployment configurations. Includes automated transformation scripts to create custom domain-specific MCP servers.

Lets Claude write and run short JavaScript programs against the YouTube Data, Analytics, and Reporting APIs, plus transcripts and search autocomplete, so multi-step channel tasks like joining upload stats with analytics finish in a single round trip. Code executes in a sandboxed isolate with quota tracking and confirmation gates for destructive or public actions.

Enables Claude Code to perform programmatic tool calling by executing Python scripts that interact with multiple MCP servers in a single round-trip. This reduces latency and token consumption by keeping intermediate tool results within the local Python runtime instead of the conversation context.

A Model Context Protocol server that allows Claude Desktop to manage and execute tasks in a queue-based system, supporting planning, execution, and completion phases.

Enables Claude to generate executable test cases from decision tables in CSV, JSON, or Markdown formats. Provides intelligent test planning guidance and generates Playwright/API test code with TypeScript support.

A Model Context Protocol server that enables Docker container management through natural language interactions using a custom GPT interface.

Enables running Jupyter notebooks on temporary AWS compute (EC2 + SSM) with cost estimation, dry-run planning, progress reporting, and automatic cleanup.

An MCP server that supercharges AI assistants with powerful tools for software development, enabling research, planning, code generation, and project scaffolding through natural language interaction.

A demonstration MCP server created for learning purposes, allowing Claude AI to interact with local files and a Postgres database while implementing a custom Model Context Protocol.

A server that enables retrieval of Sentry issues through two simple tools - get a specific issue by URL/ID or get a list of issues from a project.

A Model Context Protocol server that enables AI assistants to securely interact with OceanBase databases by listing tables, reading data, and executing SQL queries through a controlled interface.

A basic Model Context Protocol (MCP) server implementation that provides a foundation for MCP server development. The README doesn't specify particular functionality, suggesting it may be a template or starting point for building custom MCP servers.

A framework to use with AI to easily create a server for any service. Just drop the API Documentation in it and ask to create the MCP.

Enables cost-effective repository analysis, code search, file editing, and task planning by wrapping the cursor-agent CLI through focused tools. Reduces token usage by offloading heavy thinking tasks from Claude to specialized operations with configurable output formats.

Provides project-local, reproducible Stata execution for humans and AI agents, with immutable run artifacts, provenance tracking, planning gates, and a shared dashboard.

Enables Claude Desktop to act as a planning agent while delegating coding tasks to OpenCode CLI, returning execution status, file diffs, and output, with support for continuing sessions and opening workspaces in IDEs.

A sample MCP server implementation in TypeScript that demonstrates tool creation with a mock AI completion endpoint. Provides a basic example for developers to learn MCP server development patterns and tool registration.

A simple TypeScript library for creating Model Context Protocol (MCP) servers with features like type safety, parameter validation, and a minimal code API.

Enables graph pathfinding and network analysis through MCP, including Dijkstra/A* shortest paths, topological dependency resolution, maximum flow, minimum spanning trees, and PageRank centrality for agent planning.

GenAIScript is a JavaScript runtime dedicated to build relaible, automatable LLM scripts. Every GenAIScript can be exposed as a MCP server automatically.

Model Context Protocol server to run Python code in a sandbox.

A boilerplate project for quickly developing Model Context Protocol (MCP) servers using TypeScript SDK, with examples of tools (calculator, greeting) and resources (server info).

A TypeScript template for building Model Context Protocol servers that provides a structured foundation with automated tools, testing, and synchronization capabilities.