"Understanding HTTP Requests" matching MCP servers:

An integration tool that enables AI assistants like Claude to directly access and interact with Bitbucket repositories, pull requests, and code without requiring copy/paste operations.

An MCP server implementing AI-user confirmation protocols, providing tools for LLMs to seek user confirmation when uncertain through yes/no questions, action confirmations, intent clarification, understanding verification, and satisfaction ratings.

A lightweight stdio-only MCP server that allows AI agents to run multiple tasks (e.g., Python code, HTTP requests, shell commands) in parallel or with dependencies, returning structured results in a single call.

MCP server for agentic interaction with the Lean theorem prover via LSP, providing tools for understanding, analyzing, and interacting with Lean projects.

A minimal reference implementation of an MCP server that responds with "Hello, World" via Streamable HTTP. Serves as a baseline for integration testing and MCP client development with production-ready features including health checks, metrics, and containerized deployment.

A lightweight server implementation that exposes Python functions as discoverable tools via HTTP using the Machine-to-Machine Communication Protocol (MCP). Enables remote execution of Python functions through a JSON-RPC interface with async support and type safety.

A Mathematical Computation Protocol server providing 286 mathematical functions across multiple domains with flexible transport options (STDIO/HTTP) and streaming capabilities.

This project aims to build a Claude Code MCP server and implement its associated tools (explain\_code, review\_code, fix\_code, edit\_code, test\_code, simulate\_command, your\_own\_query). The server is implemented using Node.js and the MCP SDK. It receives tool requests from clients via Stdio, dynamically

Provides AI assistants with deep semantic and runtime understanding of Jupyter notebooks.

An MCP server for securely executing Python code, supporting STDIO, Streamable HTTP, and SSE transports, with easy deployment on Heroku.

A local-first skill runtime for AI coding agents that defines skills as verifiable, composable units with sandboxed execution, and exposes them as MCP tools over HTTP.

Minimal MCP server allowing Python functions to be served as MCP tools over stdio or HTTP, with a built-in client for connecting to MCP servers.

Enables agents to self-provision tenancies via a single tool call and then publish, list, inspect, call, and remove their own echo, HTTP, and Python tools at runtime, with per-tenant namespaces, stateless streamable-HTTP transport, and admin metering.

An intelligent codebase processing server that provides agentic RAG capabilities for code repositories, enabling semantic search and contextual understanding through self-evaluating retrieval loops.

Enables execution of Python and MaxScript code inside Autodesk 3ds Max 2021 from Cursor or other MCP clients via HTTP+TCP bridge.

Exposes Jupyter notebook operations as MCP tools over plain HTTP, allowing AI agents to explore, edit, run, and debug notebooks in a live VS Code session using local or remote kernels.

An MCP server that exposes your local Claude Code CLI over HTTP+SSE, enabling any MCP-compatible client to use your Claude Code MAX/PRO subscription remotely.

A basic MCP server that implements a calculate tool for arithmetic operations (add, subtract, multiply, divide). It handles requests via stdio.

A sample MCP server implementation for Next.js projects that uses the Vercel MCP Adapter to handle protocol requests across different transport methods.

Streamable HTTP MCP bridge that allows ChatGPT to delegate code execution requests to a local official Codex MCP server with configurable safety policies.