mcp-server-rabbitmq

Wanaku MCP Router serves as a middleware router facilitating standardized context exchange between AI-enabled applications and large language models via the Model Context Protocol (MCP). It streamlines context provisioning, allowing seamless integration and communication in multi-model AI environments. The tool aims to unify and optimize the way applications provide relevant context to LLMs, leveraging open protocol standards.

• ⭐ 87
• MCP
• wanaku-ai/wanaku

MyMCP Server is a robust Model Context Protocol (MCP) server implementation that integrates with services like GitLab, Jira, Confluence, YouTube, Google Workspace, and more. It provides AI-powered search, contextual tool execution, and workflow automation for development and productivity tasks. The system supports extensive configuration and enables selective activation of grouped toolsets for various environments. Installation and deployment are streamlined, with both automated and manual setup options available.

• ⭐ 93
• MCP
• nguyenvanduocit/all-in-one-model-context-protocol

FastMCP is a production-ready framework for building Model Context Protocol (MCP) applications in Python. It streamlines the creation of MCP servers and clients, providing advanced features such as enterprise authentication, composable tools, OpenAPI/FastAPI generation, server proxying, deployment tools, and comprehensive client libraries. Designed for ease of use, it offers both standard protocol support and robust utilities for production deployments.

• ⭐ 20,201
• MCP
• jlowin/fastmcp

Provides a Model Context Protocol (MCP) server implementation for the Royal Spanish Academy API, facilitating integration with language models. Offers tools such as search and word information retrieval, exposing RAE’s dictionary and linguistic data to LLMs. Supports multiple transports including stdio and SSE, making it suitable for both direct and server-based LLM interactions.

• ⭐ 3
• MCP
• rae-api-com/rae-mcp

mcp-time is a Model Context Protocol (MCP) server that enables AI assistants and MCP clients to perform standardized time and date-related operations. It provides natural language parsing for relative time expressions, supports flexible formatting, and allows manipulation and comparison of times. The server offers multiple integration methods, including stdio, HTTP stream, Docker, and npx for compatibility with various clients. It is designed for robust time handling and easy integration with AI tools.

• ⭐ 8
• MCP
• TheoBrigitte/mcp-time

mcp-server-qdrant provides an official implementation of the Model Context Protocol for interfacing with the Qdrant vector search engine. It enables storing and retrieving contextual information, acting as a semantic memory layer for LLM-driven applications. Designed for easy integration, it supports environment-based configuration and extensibility via FastMCP. The server standardizes tool interfaces for managing and querying contextual data using Qdrant.

• ⭐ 1,054
• MCP
• qdrant/mcp-server-qdrant