Enables runtime registration and live updating of MCP tools through a NETCONF/YANG-inspired candidate/running datastore, with schema sanitization, rollback, audit logging, and drift detection.
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.
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.
Local MCP server that registers restricted Python filters and runs them against local JSON, YAML, and TXT files, enabling safe data filtering and file conversion.
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 an agent to build and reuse a persistent library of tested scripts, listing and running saved helpers and saving new ones only after their tests pass.
A Model Context Protocol server that enables Claude to load CSV files and execute JavaScript data analysis scripts for advanced data exploration and insights generation.
Enables agents to synthesize typed MCP tool schemas at runtime, validate Python ASTs for unsafe imports, compile sandboxed callable handlers, and hot-plug them into an active MCP runtime. It provides a zero-dependency, standard-library-only MCP server for safe just-in-time tool creation and execution.
Enables agents to dynamically generate typed MCP tool schemas, validate Python execution ASTs against unsafe imports, and hot-plug sandboxed callable handlers into an active runtime. This allows new tools to be synthesized and safely executed on demand.
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 LLMs to drive Blender through socket-based two-way communication, letting them create and modify 3D objects, apply materials, run Blender Python, and fetch or generate assets while visually verifying results. Supports prompt-assisted 3D modeling, scene creation, and 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.
Enables Claude Code to work with personal data that stays on the local machine, running SQL, Python, and file/schema inspection in a sandboxed compute-to-data setup that returns only aggregates, schemas, synthetic fixtures, and pseudonymized results. Raw records, file names, and protected values never reach the Anthropic API, so Auto mode can stay hands-off.
A Python server implementing the Model Context Protocol to provide customizable prompt templates, resources, and tools that enhance LLM interactions in the continue.dev environment.
This MCP server integrates AI assistants with Unity Editor, allowing them to create scenes, generate scripts, simulate input, and automate workflows using 91 built-in tools.
An MCP server that provides data bridging from Spring Boot interfaces and a lightweight Python sandbox for script execution. It enables agents to fetch data as Markdown or Parquet files and perform automated data analysis within a controlled environment.
An embedded MCP server for Cocos Creator that enables AI assistants to inspect and operate running Cocos projects through tools like execute_javascript, get_project_info, and screenshot capture.
Enables AI assistants to operate directly inside a running Unity Editor project, creating scenes, generating scripts, simulating input, capturing screenshots, inspecting performance, and automating editor tasks through its built-in tools and resources.
A production-ready foundation template for building Model Context Protocol (MCP) servers with FastAPI, featuring modular tools, comprehensive testing, and OpenShift deployment configurations. Includes automated transformation scripts to create custom domain-specific MCP servers.
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 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.
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 Claude Desktop to control FreeCAD for 3D CAD modeling, including creating, editing, and deleting objects, executing Python code, and running FEM analyses.