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    Enables an agent to run ten ready-made research and monitoring workflows — competitor digests, cited reports, paper alerts, market maps, regulatory and due-diligence watches — pulling from Firecrawl, Tavily, GitHub and landing results in Notion, Slack, Google Docs, Sheets and Linear. Fields are filed with the user's own keys held in the operating system keychain, and every action that creates, sends or changes anything is shown and approved first.
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    Apache 2.0
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    This project implements a Model Context Protocol (MCP) server providing Formula One racing data using the Python FastF1 library. Inspired by an existing TypeScript server, it offers similar F1 data functionalities natively in Python via FastF1.
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    MIT
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    Provides AI assistants with access to University of Alabama at Birmingham's Research Computing documentation, enabling users to search and retrieve information about the Cheaha HPC cluster, SLURM job scheduling, storage systems, and available software tools.
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    MIT
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    Enables searching live job postings, aggregating labour-market slices, and reporting how long listings have been open, with filters for titles, location, salary, and more.
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    28 npm
    MIT
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    An MCP server for searching and downloading books from Library Genesis, supporting EPUB, MOBI, PDF, and more through natural language queries.
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    14 npm
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    MIT
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    Provides free Google Trends data (interest over time, term comparison, related queries, trending now, regional breakdown) to MCP-compatible AI clients without needing an API key.
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    138 npm
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    MIT
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    Enables natural language interaction with rasdaman multidimensional databases by translating tool calls into WCS/WCPS queries. It allows users to list coverages, retrieve metadata, and execute complex queries on datacubes through an LLM.
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    MIT
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    Real-time SEC Form 4 insider trading data — transactions with post-trade returns, cluster-buy signals, Form 144 early warnings, and 13F institutional holdings. 27 tools + 6 research prompts; free tier available.
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    339 npm
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    MIT
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    Simulate hundreds of AI agents to predict how communities react to events and policies. Upload any document (PDF, Markdown, text) and DeepMiro spawns a diverse swarm of AI agents that debate, share, and form opinions — then delivers a calibrated prediction report. Free and open-source.
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    AGPL 3.0