Model Context Protocol servers that extend AI capabilities
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Provides task management and coordination capabilities for distributed systems.
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A starter server template for building AI assistant tools.
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Store and recall persistent information across conversations to maintain long-term context and continuity. Organize knowledge into structured entities and relations for more coherent information retrieval. Enhance personalization by automatically accessing past interactions and preferences.
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Provide a simple and easy-to-run MCP server implementation that supports stdio and SSE transports. Enable seamless integration with MCP clients using Node.js or Docker environments. Facilitate quick startup and testing of MCP capabilities for development and experimentation.
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Interact with SingleStore databases using a standardized protocol. Execute queries, describe schemas, and generate ER diagrams effortlessly.
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Retrieve and list content from various knowledge bases effortlessly. Enhance your applications with semantic search capabilities to find relevant information quickly. Utilize a structured approach to manage and access knowledge efficiently.
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Extracts clean text, structured data, and metadata from any website. Captures full-page screenshots to visualize web content. Performs Google searches to find relevant information across the web.
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Interact with Descope's Management APIs to manage users, audit, and more.
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A Model Context Protocol (MCP) integration for Minecraft enabling AI assistants to interact with a Minecraft server.
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Enable AI assistants to perform web searches using Exa's powerful search API. Get real-time web information in a safe and controlled way, while caching recent searches for future reference. Simplify your search experience with customizable parameters and automatic live crawling.
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Primarily to be used as a template repository for developing MCP servers with FastMCP in Python, PyMCP is somewhat inspired by the official everything MCP server in Typescript.
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Explore Marinade documentation and get quick answers with direct links to official guides. Monitor real-time protocol state on Solana, including prices, rewards, and staking metrics. Manage liquid staking with mSOL, check balances, and send tokens between wallets.
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Tool to Prevent AI tunnel-vision in critical workflows. Vibe Check MCP v2.7 introduces Chain-Pattern Interrupts (CPI) to enhance your infrastructure stack. mitigates over-engineering, scope creep, and misalignment by injecting Socratic checkpoints into agent reasoning. - Supports Gemini API, OpenRouter and OpenAI models. - Logs errors for continuous improvement. - Trusted by 30k+ developers. - Strong CI and Security testing protocol built in. Integrate this metacognitive guardrail into your
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Manage your emails effortlessly with 60+ tools for drafting, sending, retrieving, and organizing messages. Streamline your email workflow with complete Gmail API coverage, including label and thread management. **Installation** Google API Client Setup (once per organization): 1. Go to the Google Cloud Console (https://console.cloud.google.com/). 2. Create a new project or select an existing one. 3. Enable the Gmail API for your project. 4. Go to Credentials and create an OAuth 2.0 Client ID. C
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Remember user details and preferences across conversations. Organize facts into connected profiles for richer, long-term context. Search, update, and automatically extract locations to keep memories accurate and actionable.
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Analyze your project to detect its language and deployment needs. Generate and validate Smithery-ready configuration, with the option to initialize files when you approve. Follow a guided workflow to convert existing setups and deploy with confidence.
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Enable powerful LLM-driven exploration and analysis of GitLab instances with comprehensive search, code browsing, and issue management tools. Seamlessly integrate with self-hosted or GitLab.com environments using flexible authentication modes. Optimize AI workflows with automatic GraphQL schema discovery and dynamic query capabilities.
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Dynamic QR code MCP server for AI agents. Create, retarget, and track QR codes
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Provide a test implementation of an MCP server to validate and demonstrate MCP protocol features. Enable developers to experiment with MCP interactions and verify tool, resource, and prompt handling. Facilitate integration testing for MCP clients and servers.
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Enable seamless integration of language models with external data sources and tools through a standardized protocol. Facilitate dynamic access to files, APIs, and custom operations to enhance AI capabilities. Simplify the development of intelligent applications by providing a robust bridge between models and real-world context.
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Provide a minimal MCP server implementation that enables LLM clients to connect and access example tools via HTTP or stdio transports. Facilitate integration with AI systems like Windsurf IDE and Claude by offering simple authentication and example tools such as greeting, version info, and system info. Extend the server easily by adding custom tools to enhance AI capabilities.
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Validate and experiment with Model Context Protocol server implementations supporting multiple transport mechanisms. Run the server locally, with STDIO transport, or deploy it to AWS Lambda for scalable MCP integrations. Use the MCP Inspector for easy testing and debugging of MCP tools and workflows.
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Provide a test implementation of the Model Context Protocol server to facilitate development and integration. Enable clients to interact with tools, resources, and prompts through a standardized JSON-RPC interface. Simplify testing and prototyping of MCP features in a controlled environment.
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Provide a basic MCP server implementation for testing purposes. Enable interaction with tools, resources, and prompts in a controlled environment. Facilitate MCP protocol compliance verification and development.
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