This project provides a series of Model Context Protocol servers based on Quarkus/Java to extend the capabilities of MCP-enabled LLM applications, including various services such as JDBC database interaction, JVM monitoring, and file system operations.

Media Gen MCP is a server that strictly follows the TypeScript and MCP specifications, focusing on generating and editing images and videos using OpenAI and Google's AI models. It provides a series of tools, including image generation/editing, video creation/remixing, file acquisition and processing, and supports intelligent resource linking and inline output. It is suitable for various MCP-compatible clients.

DiffuGen is an advanced local image generation tool that integrates the MCP protocol, supports multiple AI models (including the Flux and Stable Diffusion series), and can directly generate high-quality images in the development environment. It provides flexible configuration options, multi-GPU support, and can be integrated with multiple IDEs through the MCP protocol. It also provides an OpenAPI interface for external calls.

dicom-mcp is a DICOM-based model context protocol server that provides tools for large language models to query and interact with medical imaging metadata. It supports the retrieval of patient information, examinations, series, and instances, as well as the extraction of text from DICOM-encapsulated PDFs.

This is an MCP server project for accessing Zoom API functions without direct authentication from end - users. It handles the OAuth process and provides a series of tools to interact with Zoom recordings and transcripts.

The FRED MCP Server is a Node.js-based implementation for accessing the Federal Reserve Economic Data (FRED) API via the Model Context Protocol, providing search and retrieval functions for economic data series.

The Model Context Protocol (MCP) is an open-source protocol that provides a series of reference implementations and community-built servers, enabling large language models (LLMs) to access tools and data sources securely and controllably. The project includes implementations of various functional servers, covering areas such as file systems, databases, search, and API integration, and supports development with TypeScript and Python SDKs.

This project provides a series of example modules using the AWS Model Context Protocol (MCP), covering multiple languages and technology stacks, including TypeScript, Python, Spring AI, etc., demonstrating the application of MCP in scenarios such as client-server communication, ECS deployment, and RAG integration.

This code repository contains a series of example projects using the MCP protocol, including a Node.js weather service and a Python file system server, to demonstrate how to build MCP applications.

The Model Context Protocol (MCP) is an open-source protocol that provides a series of reference implementations and community-built servers, enabling large language models (LLMs) to access tools and data sources securely and controllably. This project includes various types of server implementations, covering multiple domains such as file systems, databases, Git, and Slack, and supports TypeScript and Python SDKs.

This project provides a series of Model Context Protocol (MCP) server implementations based on the Quarkus framework, used to extend the capabilities of large language model (LLM) applications that support MCP. It includes various services such as JDBC databases, file systems, JavaFX drawing, Kubernetes, and containers.

Model Context Protocol (MCP) is an open - source protocol that provides a series of reference implementations and community - developed servers, enabling large language models (LLMs) to securely and controllably access tools and data sources. The project includes server implementations with various functions, such as file system operations, database access, Git management, Slack integration, etc., and supports TypeScript and Python SDKs.

yardmcp is a programmable server based on the FastMCP protocol for exploring and querying Ruby gem documentation through YARD. It provides a series of tools to list gems, browse classes/modules, get documentation, search for content, etc., and is suitable for building documentation browsers or code assistants.

This project provides a series of Model Context Protocol (MCP) servers for enhancing the external capabilities of AI assistants, including independent implementation modules for specific functions such as educational course queries.

ONLYOFFICE DocSpace MCP Server is a service based on the Model Context Protocol (MCP) for managing the context interaction between large language models (LLMs) and ONLYOFFICE DocSpace. It is configured through environment variables, supports multiple authentication methods, and provides a series of file management tools, such as creating folders, uploading files, and getting folder contents.

This project provides a series of Model Context Protocol (MCP) servers for integration with the Cursor IDE, extending the capabilities of the AI programming assistant, including file system access, memory storage, web search, etc.

Model Context Protocol (MCP) is an open - source protocol that provides a series of reference implementations and community - developed servers for providing large language models (LLMs) with secure and controlled access to tools and data sources. The project includes various functional servers, such as file system operations, Git integration, database access, etc., and supports rapid development of new services through TypeScript and Python SDKs.

This project provides a series of OpenMCP services contributed by the community, supporting collaboration with any MCP-compatible LLM application or framework. It includes quick start examples, a GitHub PR review tool, and a text-to-podcast video generation tool.

MCP Loki is an MCP server for querying Grafana Loki logs. It enables LLMs to search and analyze logs through the model context protocol, supporting functions such as LogQL querying, label discovery, series exploration, and index statistics.

This project provides a series of MCP servers and dedicated AI agents to extend Claude's capabilities, including package management, knowledge graphs, reasoning engines, and integration capabilities with multiple platforms.

This is an MCP server project aimed at helping developers quickly integrate a self - hosted Payram payment stack. It provides a series of tools to MCP clients such as GitHub Copilot to achieve one - click evaluation of existing codebases, generation of multi - language code snippets, construction of new applications, access to localized documentation, and verification of the connection with the Payram server, thereby accelerating the development process.

Model Context Protocol (MCP) is an open-source protocol that provides a series of reference implementations and community-developed servers, enabling large language models (LLMs) to securely and controllably access tools and data sources. The project includes various types of server implementations covering multiple domains such as file systems, databases, Git, and Slack, demonstrating the diversity and scalability of MCP.

The MCP Server for ServiceNow is a modular and extensible solution that integrates with ServiceNow via the Model Context Protocol (MCP). It provides a series of API tools covering various use cases such as ITSM, ITOM, SAM, HAM, enhanced CMDB, PPM, employee experience, reporting and analysis, dynamic tool registration, and workflow orchestration. This solution is suitable for integration with AI agents or other external systems to automate processes such as access provisioning, incident management, and asset lifecycle management.