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"Information about 飞书 (Feishu or Lark)" matching MCP servers:

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    Enables AI agents to use Feishu (Lark) spreadsheets as long-term memory and personal knowledge base with retrieval-augmented generation (RAG) via the Model Context Protocol.
    MIT
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    Enables access to the Hugging Face Hub API to search and retrieve information about machine learning models, datasets, and their metadata. Provides comprehensive tools for exploring the Hugging Face ecosystem including model details, dataset information, and parquet file access.
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    A Model Context Protocol server that allows AI agents to perform WHOIS lookups, enabling users to directly ask the AI about domain availability, ownership, registration details, and other domain information.
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    MIT
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    Provides LLMs with specialized knowledge about fountain pen inks, enabling intelligent ink search, color matching, and recommendations through various tools.
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    GPL 3.0
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    A Model Context Protocol server that provides knowledge graph-based persistent memory for LLMs, allowing them to store, retrieve, and reason about information across multiple conversations and sessions.
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    MIT
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    Enables web search functionality through Perplexity AI's API with time-based filtering options. Allows users to search the web for recent information within specified time periods (day, week, month, or year).
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    MIT
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    IMCP - Insecure Model Context Protocol The DVWA for AI Security! Welcome to IMCP – a deliberately vulnerable framework that exposes 16 critical security weaknesses in AI/ML systems. Whether you're a security researcher, developer, or educator, IMCP is your playground for hands-on learning about real
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    JavaScript
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    A server that connects MCP clients (Claude, Cursor, Windsurf, etc.) to EventCatalog instances, allowing users to ask questions about their event-driven architecture and get insights about domains, services, and message schemas directly within their development tools.
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    MIT
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    A Model Context Protocol server that provides natural language access to Cortex API, enabling users to query information about their system's structure and make faster decisions about services, incidents, and team responsibilities.
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    MIT
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    Exposes a personalized AI agent that reads your resume and provides intelligent responses about your professional background through a standardized MCP server interface with RAG capabilities.
    MIT
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    Enables semantic search over Omarchy, Arch Linux, and Hyprland documentation, allowing users to query configuration and usage information via natural language in Cursor, OpenCode, or Claude Code.
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    GPL 3.0
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    MCP Memory is an MCP Server that gives MCP Clients the ability to remember information about users across conversations. It uses vector search technology to find relevant memories based on meaning, not just keywords.
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    MIT
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    MCP server for local-first RAG over Obsidian vaults, enabling AI agents to search and ask questions about notes with grounded citations.
    MIT
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    Enables users to query information about LPDP scholarship financial disbursement using RAG with Pinecone vector search and Gemini 2.0 Flash, answering questions about funding components, deadlines, living allowances, and required documents.
    MIT
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    A Model Context Protocol (MCP) server that enables LLMs to interact directly the documents that they have on-disk through agentic RAG and hybrid search in LanceDB. Ask LLMs questions about the dataset as a whole or about specific documents.
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    MIT