The NASA MCP Server is a server that follows the Model Context Protocol specification, providing a standardized interface for AI models to access more than 20 public API data sources of NASA, including astronomical photos, Mars exploration data, Earth observation images, etc. The project provides unified data format conversion, parameter validation, and rate limit management, and supports multi - platform operation.

The Azure Impact Reporting MCP Server is a tool that allows large language models to automatically parse user requests and submit reports on Azure resource issues. It supports multiple impact categories and automatically handles authentication and parameter extraction.

An MCP server implementation for the Deepseek R1 language model based on Node.js, supporting an 8192-token context window, providing stable Claude Desktop integration and model parameter configuration.

An image generation server based on the MCP protocol, using the Replicate flux-schnell model, supporting image generation through text prompts and configurable with various parameters.

The Gemini MCP Server is a middleware designed for the Claude desktop application, enabling image generation through Google's Gemini AI model. This project provides a convenient installation and configuration wizard, supports Docker containerized deployment, and allows users to customize generation parameters.

SearXNG MCP is a model context protocol server based on the SearXNG privacy-protecting metasearch engine, providing web search functionality for AI assistants. It supports zero-configuration use of public instances or connection to private instances, with features such as customizable search parameters, multi-search engine support, and privacy-first.

The AI Video Generation MCP Server supports text and image input to generate dynamic videos, providing multiple parameter controls and model selections.

The Ideogram MCP Server is an image generation service based on the Ideogram API, providing a variety of customizable image generation parameters, including ratio, model, style, etc.

The MedixHub MCP Server is a model context protocol service based on JavaScript, integrating medical and health API access functions, providing standardized function execution, parameter verification, and LLM integration, and supporting various medical data queries such as OpenTarget, FDA drug labels, and Monarch databases.

The RevitMCP project introduces natural language interaction capabilities to Revit, realizes BIM modeling automation through the MCP protocol, adopts a hierarchical architecture design, supports multi - turn dialogue and parameter completion, and significantly improves modeling efficiency.

A Node.js tool for generating images from text through the fal.ai API and MCP protocol, supporting multiple models and parameters, suitable for developers and creators to quickly generate images.

An image generation MCP server based on the FastMCP framework and Volcano Engine API, supporting high-quality image generation through the Doubao model, providing functions such as multi-resolution, parameter control, and local storage.

An Image Generation MCP Server based on the OpenAI API, providing functions to create, edit, and combine images through text prompts. It supports multiple models and parameter configurations and can be integrated into compatible MCP clients for use.

An MCP server based on the Tavily API that provides real-time web search functionality for AI models and supports configuration of multiple search parameters.

The Locust-MCP-Server is a load testing server based on the Model Context Protocol framework, supporting seamless running of Locust performance tests through an AI development environment, providing configurable test parameters and real-time execution output.

An MCP server implementation based on Flask, used to enhance the capabilities of large language models through external tools, supporting tool invocation, parameter parsing, and result injection.

An image generation MCP server based on the Flux.1 Schnell model, providing high-quality image generation services through Together AI, supporting customizable parameters and standardized interfaces.

Prompt Cleaner is an MCP server based on TypeScript, providing prompt cleaning tools and health check functions. The main functions include sensitive information desensitization, structured output, client-friendly content standardization, support for configuring LLM parameters through environment variables, and following the single model strategy to ensure behavior determinacy.

An MCP server for image generation based on the Ideogram API, providing customizable parameter configuration and multiple model selections

An image - generating MCP server based on the FLUX model, providing functions such as text - to - image conversion, batch generation, and custom parameters

The PyGithub MCP Server is a model context protocol server that interacts with the GitHub API through PyGithub. It provides a modular tool architecture, supporting complete GitHub issue management, intelligent parameter handling, and robust implementation.

A k6 load testing server implementation based on the Model Context Protocol framework, supporting custom test parameters and real-time output.

The WatchBase MCP Server is a middleware service that provides access to the WatchBase data API for querying watch metadata, including brand, collection, model, technical parameters, and other information.

MCP TAVILY SEARCH is a service based on the Model Context Protocol (MCP) that provides search functionality through Tavily. It supports quick installation and configuration, can be run via the command line or Docker, and provides debugging tools. The main functions include news search, supporting parameter configuration such as keywords, time ranges, and quantity limits.

The MCP Perplexity Server is a server that provides an API interface for asking questions to the model through the Perplexity API. It supports rapid Docker deployment and local Node.js operation, and multiple parameters can be configured.

This is a YCloud WhatsApp API server based on the MCP protocol. It can automatically generate tools to enable AI models to directly interact with the WhatsApp API, support all YCloud API endpoints, and handle authentication and parameter verification.

MCP is a standardized tool invocation protocol introduced by Anthropic, which provides a unified framework for large language models to interact with external tools, supporting dynamic tool discovery, structured parameter invocation, and composite task flows.

The DeepSeek MCP Server is an intermediate service used to connect the DeepSeek API with MCP-compatible applications (such as Claude Desktop), supporting various model parameter configurations and chat functions.

MCP-Collection is a Docker image project that integrates multiple Model-Context-Protocol (MCP) servers and provides access through a unified entry point. The project supports selecting the required MCP server at runtime through a single parameter, has a built-in supergateway for remote access, is suitable for Kubernetes environments, and emphasizes security and deterministic builds.

GNNEPCSAFT MCP Server is an implementation based on the Model Context Protocol (MCP) for thermodynamic calculations of the GNNePCSAFT tool. It predicts ePC - SAFT parameters through Graph Neural Networks (GNNs), supports the calculation of thermodynamic properties such as density and vapor pressure for pure substances and mixtures, and can automatically obtain molecular data from PubChem.

The Gemini MCP Server project implements the Model Context Protocol (MCP) service, enabling Claude Desktop to interact with Google's Gemini AI model. It provides full MCP protocol support, real - time response streaming, secure API key handling, and configurable model parameters, and is implemented in TypeScript.

This is an MCP server project based on Node.js. It integrates AI assistants with the Bouyomi-chan voice synthesis software through the Model Context Protocol, providing text-to-speech function and supporting parameter adjustment such as voice type, volume, and speed.