"Traditional Chinese Medicine or TCM Overview" matching MCP servers:

A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.

MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to: Submit and validate constraint models Set model parameters Solve constraint satisfaction and optimization problems Retrieve and analyze solution

An MCP server that plays notification sounds when AI coding assistants like Windsurf or Cursor require user attention, such as when coding is complete or when user approval is needed.

This server implements the Model Context Protocol to provide sentiment analysis of text, returning polarity, subjectivity, and overall assessment (positive, negative, or neutral).

A modular calculator server built with the MCP SDK that provides basic arithmetic operations (addition, subtraction, multiplication, division) with Chinese language support. Features include calculation history tracking, configuration resources, and decimal calculation prompts with comprehensive error handling.

Ephemeral MicroVM-isolated code execution for AI agents. Run Python, Node, or bash — fresh hardware-isolated VM per call, hard-purged after. No state persists between calls.

MCP server that gives AI assistants a secure gVisor-isolated sandbox to run Python or JavaScript code, returning stdout, stderr, and exit codes without local access.

Sandboxed Python execution with automatic dependency management. Executes Python scripts in isolated environments (bubblewrap or Docker) with PEP 723 inline dependencies, preventing host pollution.

An MCP server that preserves LLM context by intercepting large data outputs and returning only concise summaries or relevant sections. It enables efficient sandboxed code execution, file processing, and documentation indexing across multiple programming languages and authenticated CLIs.

Enables an LLM or agent to drive a VUnit HDL unit-testing project end to end: list tests, compile, run, and inspect reports and per-test logs.

MCP server for LLM quantization. Compress any HuggingFace model to GGUF, GPTQ, or AWQ format. 6 tools: info, check, recommend, quantize, evaluate, push. Self-contained Python server — no external CLI needed.

A FastMCP server that turns JSON data into Plotly figures, deployable as an isolated service on Modal. Data goes in as JSON; a validated Plotly figure (JSON) or a rendered PNG comes back over the Model Context Protocol.

Lets an agent load a design once into a long-lived OpenSTA session and then run static timing and power analysis through dedicated tools or arbitrary Tcl commands. Enables setup/hold slack, TNS/WNS, fmax, DRV, and power queries against the live session.

Enables coding agents to run multiple approaches or tasks in parallel on isolated Daytona sandboxes, returning tested diffs and benchmark rankings so the best outcome can be applied.

A professional implementation of a Model Context Protocol server that enables integration between DaVinci Resolve video editing software and AI assistants like Claude Desktop or Cursor.

Enable Claude Code, Cursor, or your favorite LLM to interact with Xcode, building your projects the same way you do, and seeing the same errors. Greatly increases productivity when working on iOS, iPadOS, macOS, visionOS, tvOS projects & Swift packages - or any time you might use Xcode.

Provides a set of read-only Kubernetes functions via an MCP server, enabling interaction with Kubernetes clusters through agents or coding assistants like GitHub Copilot.

Provides a headless session runtime for reactive compute graphs, enabling MCP-driven cell operations without a DOM or browser.

Enables AI coding agents to discover, generate, and run Cocotb co-simulation testbenches against Verilog/SystemVerilog designs, returning structured pass/fail results and tracebacks without manual simulator or Makefile setup.

An MCP server that provides tools for getting second opinions or detailed code reviews from Gemini 2.5 Pro by embedding file contents in prompts, allowing it to handle large codebases with extensive context.