MCP Firebird is a service that implements the Anthropic Model Context Protocol (MCP) for Firebird databases, allowing LLMs to securely access and manipulate databases.

This project compiles a list of popular Model Context Protocol (MCP) servers based on Smithery.ai usage data. MCP is an open-source standard developed by Anthropic for establishing secure two-way connections between data sources and AI tools.

The Oxylabs MCP Server provides web data crawling services for AI assistants, supporting dynamic rendering, structured extraction, and anti - blocking functions.

The Storm MCP server is an open protocol that implements the Anthropic Model Context Protocol, supports the integration of LLM and RAG data sources, and provides functions such as context sharing, tool system, file management, and API integration.

Academia MCP is an MCP server designed for academic research. It provides tools for searching, retrieving, analyzing, and reporting scientific papers and datasets. It supports platforms such as ArXiv, ACL Anthology, and Hugging Face, and includes functions like web page crawling, LaTeX compilation, PDF reading, and LLM enhancement.

MCP Firebird is a service that implements the Anthropic Model Context Protocol (MCP) for the Firebird database, allowing large language models such as Claude to securely access and analyze database content.

Chakra MCP Server is a tool that natively integrates with Anthropic's Model Context Protocol (MCP), allowing users to interact with databases and subscribed data shares through natural language. It supports natural language queries, data share interactions, and database management functions.

The Model Context Protocol (MCP) is an open - source protocol released by Anthropic, aiming to solve the standardization problem of connecting large language models (LLMs) with external data sources and systems. It provides a structured framework that enables models to integrate and utilize external context, thereby expanding their capabilities and improving response accuracy. MCP supports functions such as knowledge expansion, external tool calls, and pre - written prompts.

An MCP server providing access to the QAnon posts dataset for anthropological/sociological research and analysis

A LinkedIn data crawler tool that supports various data extractions such as personal profiles, company information, and post searches. It provides three usage methods: Python library, command line, and MCP server, and has a built-in anti-detection mechanism.

MCP-Undetected-Chromedriver is an MCP service based on undetected-chromedriver, providing browser automation control interfaces that bypass anti-scraping detection. It is suitable for web page automation testing and data collection scenarios.

This project is a Model Context Protocol (MCP) server implemented for the Wrike project management platform, allowing interaction with the Wrike API through an MCP client (such as Anthropic's Claude desktop app), supporting queries and operations on data such as tasks, projects, spaces, and comments.

Awesome MCP Servers is a curated list of Model Context Protocol (MCP) servers and tools. MCP is an open standard introduced by Anthropic that enables AI models to connect to external data sources and tools through standardized interfaces, enhancing their capabilities.

A Python-based MCP server project for obtaining data from LinkedIn profiles and integrating it with the Anthropic API for analysis. The project is built with FastAPI, supports Docker containerization, and includes a complete development toolchain configuration.

An MCP server project based on Docker and MCPHost, supporting data retrieval from the database via curl and integrating Anthropic's LLM services.

This is a Model Context Protocol (MCP) server implemented for Amazon Redshift, written in TypeScript. It follows Anthropic's implementation pattern and provides rich Redshift data warehouse context information for Cursor IDE and other MCP-compatible clients, enabling LLMs to examine the database schema and execute read-only queries.

This is an MCP server implemented for Amazon Redshift, developed in TypeScript and following Anthropic's implementation pattern. It provides rich context information of the data warehouse for MCP-compatible clients such as Cursor IDE, supporting database schema inspection and read-only query execution.

MCP is an open - source protocol developed by Anthropic, aiming to provide a standardized way for AI models to interact with external data sources and tools. The project implements functions such as weather queries, Google automatic searches, and camera control. It is highly configurable and suitable for scenarios such as intelligent assistants and automated workflows.

This project is an AWS cost analysis tool based on the Anthropic MCP protocol, providing a natural language interaction interface through the Claude model. It can query AWS Cost Explorer and Bedrock model call log data, and supports local and remote deployment.