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    Enables structured extraction of methods and reproducibility heuristics from academic papers, allowing AI agents to obtain metadata, full text, structured methods, code repository discovery, and a no-clone reproducibility verdict from a paper URL.
    8
    35 PyPI
    MIT
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    Provides MCP tool adapters for Bioconductor methods like limma, DESeq2, and fgsea, enabling statistical analysis of omics data through containerized R execution. It serves as a bridge between MCP clients and bioinformatics tools for reproducible research workflows.
    Apache 2.0
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    Enables MCP agents to retrieve Japanese voice presets and synthesize anime-style speech, including reference-conditioned voice cloning, using the CPU of the computer running the local Gradio app.
    MIT
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    MCP server that provides OpenRouter model pricing data, enabling price lookups, trending/cheapest lists, and model searches without an API key.
    -
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    Analyzes a codebase to extract its coding conventions and exposes tools via MCP for AI agents to retrieve live style rules, ensuring generated code matches the project's unwritten style.
    1
    MIT
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    A Model Context Protocol server that enables AI-powered image generation through Stability AI and Black Forest Labs APIs, allowing users to create images from detailed text prompts with customizable settings and comprehensive metadata tracking.
    MIT
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    Provides a catalog of curated author writing styles and tools to blend or analyze them across eight dimensions for text and image prompt generation. It enables users to apply structured literary patterns through deterministic style modeling and coordinate-based interpolation.
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    Converts any Python Click or Typer CLI into an MCP server automatically — zero-code transformation that introspects CLI commands and exposes them as MCP tools.
    8
    Apache 2.0
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    Enables agents to fetch public URLs as noise-free Markdown (via Jina Reader with a local HTML fallback) protected by SSRF and indirect prompt-injection defenses, while capturing each article's hook, heading rhythm, and sentence-ending style as a reusable writing recipe in a local DuckDB style vault so that recipe can later drive automated manuscript generation.
    MIT
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    MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to: Submit and validate constraint models Set model parameters Solve constraint satisfaction and optimization problems Retrieve and analyze solution
    22
    MIT
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    Educational tools agent by Birkan Yavuz — an A2A + MCP server for classroom tools, with creator attribution in every result. It offers a catalog of 24 real classroom activities, including math visualizers and reading and sight-word tools.
    4
    CC BY-4.0
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    Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.
    3
    39 PyPI
    29
    Apache 2.0
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    license
    A
    quality
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    maintenance
    Provides five safe tools (calc, search, model_drift, compare_runs, grade_answer) for arithmetic, keyword search, model drift monitoring, eval comparison, and answer grading against sources, all implemented directly from the MCP spec with zero dependencies.
    5
    1
    MIT
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    An MCP server that provides a persistent sandbox for AI coding agents to explore codebases server-side, returning only compact summaries to reduce context consumption.
    3
    8
    MIT
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    Enables extraction of recipes from PDFs or JPG files and conversion into structured HTML, with interactive region selection and OCR via a web GUI.
    6
    MIT
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    Enables users to turn any API's documentation into a tested MCP server whose tools expose the API's own operations, with linting, contract tests, and live verification. It accepts OpenAPI/Swagger, Postman, RAML, WSDL, GraphQL, RSS, and HTML docs.
    14
    Apache 2.0
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    Exposes AWS Palace finite-element electromagnetic simulation as a set of JSON-in/JSON-out tools, so an agent can build geometry and meshes, generate and lint configs, estimate cost, guard and launch runs, and read back S-parameters, eigenmodes, Q and energy results. Results return as JSON text plus structured content over a dependency-free stdio JSON-RPC connection.
    13
    1
    Apache 2.0
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    MCP server for compressing AI embeddings by 5-7x using TurboQuant (PolarQuant + QJL), with tools to compress, decompress, estimate savings, and embed+compress vectors.
    MIT