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    An MCP server implementing the ROBINS-I V2 framework for risk-of-bias assessment in non-randomized studies, with deterministic algorithms and full provenance. It enables users to parse study documents, specify target trial results, answer signalling questions with evidence-bound quotes, and compute or override domain judgements.
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    Apache 2.0
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    An MCP server that guides Copilot to version-correct documentation and source code for Industrial Ecology Python packages, enabling reliable, environment-aware coding assistance for LCA workflows.
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    BSD 3-Clause
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    Track how your brand appears in AI-generated answers across ChatGPT, Perplexity, and other AI models. Analyze visibility, sentiment, citations, and domain rankings with 31 tools — including analytics reports, chat inspection, query analysis, and full CRUD for brands, prompts, tags, and topics.
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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
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    MCP server exposing 40 best-practice product management skills plus workflows and lifecycle tools, instantly accessible to any AI via Model Context Protocol.
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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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    Enables AI assistants to programmatically create, read, validate, and modify Stella system dynamics models in the XMILE format. It supports building complex stock-and-flow diagrams and exporting them as .stmx files for use in Stella Professional.
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    MIT
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    Enables AI agents to interact with the AI-Archive platform for research paper discovery through semantic search, paper submission and management, peer review with structured scoring, and citation generation in multiple formats.
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    MIT
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    Enables AI assistants to create and manage content collections, perform web searches, and enhance data using Exa AI's websets capabilities with guided workflows for research and analysis.
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    MIT
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    Enables academic research through paper search across multiple databases (IACR, CryptoBib, Crossref, Google Scholar), PDF processing, and GitHub repository browsing. Features modular architecture with FastMCP-based proxy server routing to specialized academic tools.
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    Live data gateway for AI agents. 261 data sources, 961 tools — SEC filings, FDA adverse events, trade flows, mortgage rates, clinical trials, government contracts. Ask questions in plain English with ask_pipeworx.
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    MIT
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    Enables AI assistants to search, query, and manage ocean/environmental datasets from the Oceanum platform, and to read, write, and delete files in Oceanum cloud storage.
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    MIT