Model Context Protocol
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A Model Context Protocol server for Excel file manipulation. This server enables workbook creation, data manipulation, formatting, and advanced Excel features.
mcp-golang
23
Write Model Context Protocol servers in few lines of go code. Docs at https://mcpgolang.com
Go server implementing Model Context Protocol (MCP) for filesystem operations.
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A MCP (model context protocol) server that gives the LLM access to and knowledge about relational databases like SQLite, Postgresql, MySQL & MariaDB, Oracle, and MS-SQL.
Enables cloud-based AI services to access local Stdio based MCP servers.
simple web ui to manage mcp (model context protocol) servers in the claude app
A Model Context Protocol server that provides access to MongoDB databases. This server enables LLMs to inspect collection schemas and execute MongoDB operations.
This Model Context Protocol server implementation of Asana allows you to talk to Asana API from MCP Client such as Anthropic's Claude Desktop Application, and many more.
A secure shell command execution server implementing the Model Context Protocol (MCP). This server allows remote execution of whitelisted shell commands with support for stdin input.
Simple solution to give Claude ability to check current time via MCP
A Model Context Protocol (MCP) server that provides line-oriented text file editing capabilities through a standardized API. Optimized for LLM tools with efficient partial file access to minimize token usage.
A middleware to provide an openAI compatible endpoint that can call MCP tools
Understanding Model Context Protocol (MCP)
Model Context Protocol (MCP) is a groundbreaking open-source protocol developed by Anthropic that revolutionizes how AI systems interact with external data sources. As the foundation for next-generation AI interactions, MCP enables AI assistants like Claude to establish secure and standardized connections with various data sources and tools.
Key Features of MCP
- Universal Standard: Provides a unified framework for AI systems to access external data, tools, and prompts
- Client-Server Architecture: Implements a robust and scalable architecture for seamless AI interactions
- Security-First Design: Ensures secure data transmission and access control between AI systems and data sources
- Tool Integration: Enables AI assistants to interact with various external tools and services
- Standardized Communication: Establishes consistent protocols for data exchange and interaction patterns
Benefits for AI Development
MCP represents a significant advancement in AI infrastructure, offering developers and organizations a standardized way to build and deploy AI applications. By providing a common protocol, MCP reduces implementation complexity and ensures compatibility across different AI systems and data sources.
Whether you're developing AI applications, managing data infrastructure, or implementing AI solutions, MCP provides the foundation for secure, efficient, and standardized AI interactions. Explore our directory to find MCP servers that match your specific needs and requirements.