Model Context Protocol
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A Model Context Protocol (MCP) server implementation that provides database interaction with Snowflake. This server enables running SQL queries with tools and interacting with a memo of data insights presented as a resource.
A Model Context Protocol (MCP) server that provides access to the Strava API. It allows language models to query athlete activities data from the Strava API.
A Model Context Protocol (MCP) server that provides programmatic access to the Supabase Management API. This server allows AI models and other clients to manage Supabase projects and organizations through a standardized interface.
An MCP server for Timeplus.
An MCP server to interact with a Tinybird Workspace from any MCP client.
Send requests to OpenAI, MistralAI, Anthropic, xAI, Google AI or DeepSeek using MCP protocol via tool or predefined prompts. Vendor API key required
Upsonic is a reliability-focused framework designed for real-world AI agent applications. It utilizes the Model Context Protocol (MCP) to leverage diverse tools and offers features for browser and computer use integration, as well as a secure runtime environment.
MCP Interface for Video Jungle
A Model Context Protocol (MCP) server for querying the VirusTotal API. This server provides comprehensive security analysis tools with automatic relationship data fetching. It integrates seamlessly with MCP-compatible applications like Claude Desktop.
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.