"Automated App for Improvement, Auditing, Feature Management, and Planning" matching MCP servers:

Exposes the automated feature engineering LangGraph agent as MCP tools, enabling dataset profiling, feature planning, and feature code execution through MCP-compatible hosts.

A proxy server that allows LLM clients to use Databutton app API endpoints as tools through the MCP protocol over websockets.

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.

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

Enables running user-supplied scripts inside resource-limited, network-isolated Docker containers built from human-reviewed Dockerfiles, with jobs driven by an outbound-only worker.

Enables AI-powered video creation by writing React/Remotion code, compiling it in real-time, and rendering the result as a live video inline in the chat.

Enables AI-powered video creation by letting the model write React/Remotion code, compiling it in real-time, and rendering the video inline in the chat interface via an interactive widget.

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.

Production-oriented MCP gateway for managing Codex through a persistent codex app-server process, supporting threads, autonomous goals, approvals, and HTTP/stdio transports.

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 starter template for creating MCP servers that work with Puch AI, featuring ready-to-use tools for job searching and image processing. Includes examples for Bearer token authentication, OAuth integration with Google and GitHub, and demonstrates user-scoped data management.

Enables LLMs to safely execute pandas code for data analysis and generate interactive visualizations through MCP protocol.

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.

A Model Context Protocol server implementation that provides a simple interface to interact with PostgreSQL databases, enabling SQL queries, database operations, and schema management through MCP.

Lets AI assistants use MetaModel's formula engine for certified computation, turning published calculators, pricing tools, and engineering models into AI-callable tools with no hallucinated math.

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.

Connects Claude Desktop to a running FreeCAD instance, enabling document management, part creation and editing, direct Python execution, parts library insertion, FEM analysis, and 3D view screenshots.

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