The Prometheus MCP Server provides a standardized interface for AI assistants to interact with Prometheus metrics. It allows execution of PromQL queries, metric discovery, and metadata retrieval. The server supports authentication, Docker containerization, and configurable tools for AI interactions, making it ideal for integrating Prometheus data with AI workflows.

The Claude Deep Research MCP Server is designed to assist in conducting in-depth research on complex topics. It helps users explore questions in depth, find relevant sources, and generate structured research reports. The server integrates with Claude's built-in web search capabilities, performs targeted searches, evaluates information quality, and creates well-structured, comprehensive reports with proper citations.

Roo Code is an AI-powered autonomous coding agent designed to live within your code editor. It assists developers by generating code, refactoring, debugging, writing documentation, and automating repetitive tasks. It integrates with OpenAI-compatible APIs and supports custom modes for specialized tasks, making it a versatile tool for software development. Roo Code also includes features like file handling, terminal command execution, and browser automation, all powered by the Model Context Protocol (MCP).

This Python package facilitates interaction between LLM models and the Memos server using the Model Context Protocol (MCP). It supports searching, creating, retrieving, and managing memos, along with secure authentication. The package is designed to integrate seamlessly into existing MCP workflows, providing tools for memo management and enhanced functionality for LLM applications.

The Multi-Model Advisor MCP Server integrates with Ollama models to provide a 'council of advisors' approach, where multiple AI models offer diverse perspectives on a single question. It allows users to assign different roles or personas to each model, customize system prompts, and seamlessly integrate with Claude for Desktop. This implementation enhances decision-making by synthesizing responses from various AI models, ensuring comprehensive and well-rounded answers.

The Symbolica MCP Server is designed for scientific and engineering applications, enabling AI tools like Claude to perform symbolic computing, mathematical calculations, and data analysis. It supports libraries such as NumPy, SciPy, SymPy, and Pandas, and offers features like linear algebra operations, quantum computing analysis, and data visualization. The server is containerized using Docker, ensuring cross-platform compatibility for Windows, macOS, and Linux systems.

BlenderMCP integrates Blender with Claude AI using the Model Context Protocol (MCP), allowing users to control Blender through AI prompts. It supports two-way communication, object manipulation, material control, scene inspection, and Python code execution in Blender. The system includes a Blender addon and an MCP server, enabling seamless interaction between AI and 3D modeling workflows.

The Tung Shing Chinese Almanac MCP Server is a service based on the Model Context Protocol (MCP) that calculates and provides traditional Chinese calendar information. It supports conversion between Gregorian and Lunar calendars, offers daily auspicious and inauspicious activities, and includes detailed information about Five Elements, Gods, and Stars. This server is designed to integrate seamlessly with MCP configurations, providing historical and cultural calendar data for specific dates and times.

The Fibery MCP Server facilitates integration between Fibery and LLM providers supporting the Model Context Protocol (MCP). It allows users to query Fibery entities, manage databases, and create or update entities using natural language. This server is particularly useful for enhancing productivity by enabling conversational interfaces with Fibery workspaces.

The Databricks MCP Server integrates with Databricks API, allowing Large Language Models (LLMs) to execute SQL queries, list jobs, and retrieve job statuses. It provides a seamless interface for natural language interactions with Databricks, enabling tasks like querying databases and managing jobs through LLMs. The server requires Python 3.7+ and Databricks credentials, and it supports features like SQL query execution, job listing, and job status retrieval.

This project provides a Node.js package that adapts the MCP TypeScript SDK to work with AWS Lambda, supporting Server-Sent Events (SSE) through Lambda response streaming. It handles CORS, HTTP method validation, and includes TypeScript support. The package is designed to integrate seamlessly with AWS Lambda, enabling developers to implement MCP server functionality in a serverless environment.

The MCP Server Logger is a tool designed to handle logging in MCP (Model Context Protocol) servers that use stdio transport. It patches console methods like log, warn, error, and debug to redirect logs to a separate terminal, preventing interference with protocol communication. This is particularly useful during development when console.log can disrupt the MCP inspector.

The PocketBase MCP Server is designed to accelerate the development of PocketBase applications by providing sophisticated tools for database interactions, schema management, and data manipulation. It supports advanced features like collection management, CRUD operations, user authentication, and database backups. Built on the Model Context Protocol (MCP), it integrates seamlessly with PocketBase, offering a streamlined workflow for developers.

The Swift MCP GUI Server is a Model Context Protocol (MCP) implementation designed to control macOS through programmatic commands. It integrates with SwiftAutoGUI to provide tools for mouse movement, clicks, keyboard input, and scrolling. This server is particularly useful for automating tasks and controlling macOS environments remotely via MCP clients.

This project implements a server that allows AI models to interact with Kafka topics through a standardized interface. It supports publishing and consuming messages from Kafka topics, making it suitable for LLM and agentic applications. The server can be configured to work with various transport options and integrates seamlessly with tools like Claude Desktop.