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.

The bioRxiv MCP Server provides a bridge for AI assistants to access the bioRxiv pre - print library, supporting functions such as paper search and metadata retrieval, and facilitating biological scientific research.

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.

NeoCoder is an AI programming assistance system based on the Neo4j knowledge graph. It enables the interaction between AI assistants and the knowledge graph through an MCP server, providing standardized coding workflows, dynamic instruction manuals, and project memory functions. The system supports multiple operation modes (incarnations), including basic programming, scientific research, decision - making analysis, complex system modeling, knowledge graph management, and code analysis. It stores workflow templates and execution records in Neo4j to ensure the traceability and standardization of the coding process.

MCP.science is an open - source project that provides a variety of MCP servers designed specifically for scientific research applications, enabling AI models to interact with scientific data, tools, and resources through a standardized protocol.

MCP.science is an open - source project that provides a variety of MCP servers specifically designed for scientific research, enabling AI models to interact with scientific data, tools, and resources through standardized protocols.