Awesome MCP Servers is a comprehensive collection of Model Context Protocol (MCP) servers, covering 7,158 MCP servers divided into 33 categories, including AI integration, art and media, browser automation, cloud services, databases, developer tools, file systems, finance, gaming, hardware, healthcare, infrastructure, knowledge management, location maps, marketing, monitoring, multimedia processing, operating systems, project management, scientific research, security, social media, travel and transportation, utilities, and version control, etc.

Open Data MCP is an open - source project aiming to quickly connect public data sets to LLM applications through the MCP protocol. The project provides a CLI tool to achieve a 2 - minute connection (currently supporting Claude) and establishes a community collaboration framework that allows developers to easily contribute and publish public data sets. The core goal is to build an infrastructure that connects all LLM applications with millions of public data sets.

A high-performance MCP server implemented in Go language, providing AI agents and applications with the ability to query and access the Redfish API through natural language, enabling intelligent management and monitoring of data center infrastructure.

A basic project for developing custom MCP servers, providing a complete architectural pattern, example tools, and development infrastructure to support AI assistants in connecting to external data sources or APIs.

MCP Server Meraki is a standardized interface project for interacting with Meraki infrastructure through the MCP protocol, providing data validation, error handling, and a modular architecture.

The Linode MCP Server is a protocol server that connects an AI assistant to the Linode cloud infrastructure, supporting the management of cloud resources, including multiple services such as instances, databases, and networks, through natural language conversations.

A Python-based tool for obtaining infrastructure monitoring data through the Datadog API, providing monitoring status tracking and Kubernetes log analysis functions.

The Unified MCP Tool Graph is a research - driven project that provides an intelligent infrastructure layer for large language models (LLMs) and agent AI systems to dynamically retrieve the most relevant tools by aggregating and structuring tool APIs from different MCP servers into a centralized Neo4j graph database.

This project is part of the Model Context Protocol (MCP) ecosystem. It provides an MCP server that interacts with the Status Invest API for querying stock market data, such as stock prices, indicators, and payment dates. The project adopts a layered architecture design, including the domain layer, infrastructure layer, application layer, and interface layer, and supports data validation and external API integration.

A multi - agent AI infrastructure based on the Model Context Protocol (MCP), providing a standardized communication layer, supporting vector databases, tool integration, and multi - agent collaboration, including core components such as an inspector dashboard, Qdrant vector database, and Docker network.

The MCP server provides infrastructure connection services for LLM agents, supporting interaction with databases, file storage, Kafka, and web interfaces. It is deployed in a containerized manner and integrated with Gitlab Agent and LLM Chat to achieve automated data pipeline creation

A collection of 46 professional AI sub - agents to expand the functionality of Claude Code, covering multiple fields such as development, architecture, language, infrastructure, quality and safety, data AI, etc., and achieving task optimization through specific model allocation.

EVDI is an end - to - end verifiable data infrastructure that provides digital identity and credential management for the AI agent ecosystem. It enables the authentication and trust establishment of AI agents through the Self - Sovereign Identity (SSI) model. The MCP Server, as an adapter for the SSI issuance service, exposes SSI operations as tools that can be called by AI models, supporting credential management and verification functions.

The NetBox MCP Server is a bridge that connects NetBox and MCP - compatible LLMs, providing functions for querying and analyzing network infrastructure data.

The OCI Core Services FastMCP Server is a production-level management tool designed specifically for Oracle Cloud Infrastructure. It provides comprehensive compute instance lifecycle management, database operations, and network information query functions. Adopting the LLM-first design concept, it achieves high performance and reliability through the OCI Python SDK.

Openfort's MCP Server is an open - source wallet infrastructure solution that enhances the capabilities of AI assistants through a plug - in approach, enabling them to automatically create projects, manage configurations, and query data.

This is an MCP server project for Oracle Cloud Infrastructure, which allows LLMs to directly manage OCI resources and supports functions such as dynamic configuration file switching, management of computing instances, and database systems.