"Automatic detection of HTTP method (GET vs POST) for web crawling" matching MCP servers:

A bridge that enables AI assistants to connect to VS Code's debugger, allowing them to interact with and control debugging sessions through websocket connections.

Enables AI assistants to interact with VS Code for language intelligence, debugging, and code execution.

A meta-server that aggregates multiple MCP servers into a single interface, reducing token usage by 98%+ through progressive tool discovery and direct code execution that processes data between tools without consuming context window space.

Chain of Draft Server is a powerful AI-driven tool that helps developers make better decisions through systematic, iterative refinement of thoughts and designs. It integrates seamlessly with popular AI agents and provides a structured approach to reasoning, API design, architecture decisions, code r

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.

An MCP server that uses Groq's API to expose raw chain-of-thought tokens from Qwen's qwq model, enabling LLMs to think step-by-step before responding.

Enables a browser-based AI assistant to read code, edit files, run tests, inspect failures, and keep task checkpoints on a local project.

Enables local code execution via Codex (Luna) through MCP, using ChatGPT Web conversations as a planner. Provides file, terminal, and code execution tools while keeping long-running jobs manageable.

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.

Enables external agents to run, edit, create, and manage the Jupyter notebook the user is actively editing in VS Code, headlessly and without approval dialogs. Works with any MCP client and is Jupyter-optional for document operations.

Enable Claude (or any other LLM) to interactively debug your code (set breakpoints and evaluate expressions in stack frame). It's language-agnostic, assuming debugger console support and valid launch.json for debugging in VSCode.

A Model Context Protocol server that enables LLMs to interact with VS Code's Simple Browser, allowing for browser control, JavaScript execution, console monitoring, and navigation through natural language.

A server that enables browser-based local LLM inference using Playwright to automate interactions with @mlc-ai/web-llm, supporting text generation, chat sessions, model switching, and status monitoring.

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

Enables AI assistants to execute Python functions and system commands via Streamable HTTP, including bash, Python code execution, file operations, and text searching.

A TypeScript boilerplate for building Model Context Protocol servers using the Streamable HTTP transport and session management. It serves as a foundational template with pre-configured development tools to help developers quickly build and deploy streamable MCP services.

Enables AI assistants to operate directly inside a running Unity Editor project, using built-in tools for scene creation, script generation, play mode automation, input simulation, and performance analysis.

Enables AI clients to interact with and control the Unity Editor through a Python MCP server bridge, allowing natural language-based Unity project manipulation.

stateless MCP server — fresh instance per request, infinite horizontal scaling

Enables Windows users to connect Antigravity CLI as an MCP subagent for coding tasks such as file reading, code execution, edits, and terminal commands, with model selection, conversation continuity, and streaming progress.