"Updated documentation for LangChain, Langraph, Node.js, Express, and FastAI frameworks" matching MCP servers:

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

Provides Node.js debugging capabilities with process management for AI agents, allowing them to start/stop Node.js processes, set breakpoints, step through code, and evaluate expressions.

A basic serverless MCP server example running on Netlify Functions using Express. Demonstrates how to deploy and run Model Context Protocol servers in a serverless environment.

A serverless implementation of the Model Context Protocol (MCP) that runs on Netlify Functions, allowing developers to build and deploy MCP-compatible services with minimal configuration.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.

Enables AI agents to invoke a local Stata installation, including a Windows Stata build under Wine on Linux and macOS, for regression analysis, econometrics, paper replication, and empirical research with command guards, resource monitoring, and automatic log capture.

Enables running arbitrary JavaScript code in isolated Docker containers with on-demand npm dependency installation, allowing for ephemeral script execution and long-running services with controlled resource limits.

Facilitates interaction with Microsoft SQL Server Express, supporting database operations such as querying, table management, and schema inspection via natural language MCP commands.

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 basic example MCP server deployed as a Netlify serverless function using Express. Demonstrates how to run Model Context Protocol servers in a serverless environment with proper routing configuration.

Enables running arbitrary JavaScript code in isolated Docker containers with on-the-fly npm dependency installation, supporting both ephemeral one-shot executions and persistent sandbox environments.

A basic example of developing and running serverless Model Context Protocol (MCP) using Netlify Functions, demonstrating how to deploy and access MCP functionality through customized URLs.

A modular Model Context Protocol server implementation using Express.js that provides example mathematical and echo tools with HTTP streaming support and easy extensibility for adding custom tools.

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.

This server facilitates the invocation of AI models from providers like Anthropic, OpenAI, and Groq, enabling users to manage and configure large language model interactions seamlessly.

A tool server that processes mathematical expressions via Multi-Chain Protocol (MCP), allowing LLMs to solve math problems through tool integration.

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.

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

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.

An MCP server that lets Large Language Models interact with Stata software to perform regression analysis and other statistical operations.