"Documentation for Wagtail CMS" matching MCP servers:

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 coding assistants to browse Unreal Python API documentation, search classes and functions, and execute Python code in Unreal Editor.

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.

Enables AI agents to autonomously write, run, and debug NASA GMAT mission scripts, with tools for script execution, curated knowledge of common pitfalls, and semantic documentation search.

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.

Bridges Claude Desktop to local Windows 10 development environments to enable repository reading, documentation searching, and isolated code execution. It provides a secure interface for running allowlisted terminal commands and scripts directly through natural language.

Enables coding assistants to access Perplexity AI for quick fact-checking and in-depth research. Provides two tools: lookup for fast documentation queries and answer for comprehensive research with recommendations.

A secure MCP server for evaluating mathematical expressions with grammar validation, function whitelisting, and sandboxed execution. It provides tools for expression evaluation, variable management, and resources for grammar and function documentation.

Enables Claude Desktop to control FreeCAD for 3D CAD modeling, including creating, editing, and deleting objects, executing Python code, and running FEM analyses.

An MCP server that grants AI agents unrestricted file system, Python, and PowerShell access on Windows for real, unfiltered automation.

Wraps the TanStack CLI to provide programmatic access to documentation, library listings, and project scaffolding for the TanStack ecosystem. It enables AI assistants to search documentation and create new TanStack applications through the Model Context Protocol.

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

Automatically provides AI assistants with contextual, version-specific documentation for Python project dependencies by scanning pyproject.toml files. Eliminates manual package lookup and enables more accurate coding assistance through seamless integration with AI tools.

An MCP server that enables running CLI for Microsoft 365 commands through GitHub Copilot Agent, allowing users to interact with Microsoft 365 services using natural language.

A comprehensive Model Context Protocol server that provides advanced Node.js development tooling for automating project creation, component generation, package management, and documentation with AI-powered assistance.

A production-ready FastMCP server template with modular architecture for building MCP servers with organized tools, resources, and prompts, featuring container support and AI agent documentation system.

Provides a universal developer operations and diagnostics toolkit with sandboxed code execution, algorithm stress testing, security secret scanning, AST-based code fixes, and a visual dashboard for ERD, port/process inspection, and differential testing.

A server that enables Claude Desktop to generate images using Google's Gemini AI models through the Model Context Protocol (MCP).

Enables integration of Perplexity's AI API with LLMs, delivering advanced chat completion by utilizing specialized prompt templates for tasks like technical documentation, code review, and API documentation.