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    MCP server that enables Claude to control Altair AI Studio for data mining and machine learning tasks, including data import, cleaning, transformation, model training, clustering, association rules, and executing saved processes.
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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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    MIT
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    Python-first MCP server for CST Studio Suite (2024–2026) that lets AI assistants drive CST from Windows: open projects, build geometry, set materials and ports, run solvers, read S-parameters and farfield metrics, and generate design reports.
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    MIT
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    MCP server for BIOVIA Materials Studio 2023 on Windows, providing controlled preparation of Forcite and CASTEP inputs, model building, and LAMMPS/VMD pre-processing with reproducible, auditable workflows and strict scientific boundaries.
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    Read-only MCP server for the July 2026 survey of AI in open-source design systems, enabling agents to query 19 systems' affordances, coercion techniques, and platform data via 9 tools, 2 resources, and 2 prompts.
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    Provides tools to search and execute Code Ocean capsules and pipelines while managing platform data assets. It enables users to interact with Code Ocean's computational resources and scientific workflows directly through natural language interfaces.
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    Real human judgment as agent tools -- an AI agent can ask a question and get back a structured, schema-validated JSON answer from a real quality-scored human. 16 response types (yes/no, ratings, rankings, A/B tests, sentiment, image/video/audio review, voice/video/photo capture). Fully programmatic signup with a $5 free trial credit, no card required.
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    MIT
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    Provides professional market data access via DataBento API, including real-time futures quotes, historical timeseries, batch downloads, symbol resolution, metadata discovery, and reference data.
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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 searching and discovering machine learning papers, state-of-the-art benchmarks, tasks, datasets, methods, and leaderboards from Papers with Code. Supports mapping papers to their benchmark results and browsing evaluation tables.
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    A read-only reference server for 303 curated generative art algorithms implemented in Python (py5), spanning physics, fractals, cellular automata, shaders, and more. Agents can search by keyword, visual mood (ethereal, chaotic, crystalline…), or multi-layer artistic intent to discover algorithms, read structured summaries, and fetch bounded source snippets.
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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