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    An MCP (Model Context Protocol) server that gives AI agents live, structured ad intelligence across Facebook, Google, and Instagram — data that no base model can produce from training alone. Powered by Apify actors. Works with any MCP-compatible client: Cursor, Claude, etc.
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    Enables AI assistants to search, compare, and get detailed information about MCP servers from the mcpcatalogs.com directory.
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    MIT
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    Provides professional cycling data from FirstCycling, allowing users to retrieve comprehensive information about cyclists, race results, historical cycling data, and team information through natural language queries.
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    MIT
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    Enables users to interact with container registries through the ORAS CLI, providing information about container images, platforms, and signatures via natural language queries.
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    Apache 2.0
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    Provides comprehensive information about Colombia including departments, regions, cities, tourist attractions, and general country data through the API Colombia service. Enables users to query Colombian geographical and administrative information through natural language.
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    Enables phone number lookup through the Truecaller Data2 API, allowing users to search and retrieve information about phone numbers for identification and verification purposes.
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    MIT
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    Implements a Model Context Protocol server that enables natural language interactions with SQLite databases, providing tools to list tables, retrieve schemas, count rows, and execute read-only SQL queries.
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    MIT
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    Enables natural language interaction with local SQLite databases through Claude Desktop, translating plain English queries into SQL for data analysis and exploration.
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    MIT
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    An open-source MCP server that imports HR CSV data into an in-memory SQLite database for structured querying and metadata retrieval. It enables users to perform read-only SQL queries and structured searches on employee data through natural language.
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    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.
    Last updated
    MIT