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    Enables finding information online, reading web pages, finding images, capturing screenshots, and performing multi-source research with per-answer confidence.
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    AGPL 3.0
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    Enables MCP-aware agents to estimate, submit, monitor, cancel, and retrieve artifacts from Jungle Grid workloads, supporting asynchronous AI execution, batch processing, training, fine-tuning, and access to logs and managed outputs.
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    9 npm
    MIT
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    Jungle Grid MCP Server lets AI agents submit, estimate, monitor, and retrieve logs for GPU workloads through Jungle Grid. It enables agentic execution for inference, training, fine-tuning, and batch jobs without manually choosing GPU providers or infrastructure.
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    MIT
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    A privacy-first MCP server for locally managing job, fellowship, and graduate-school applications. It offers tools for tracking application status, analyzing role fit, generating LaTeX CV/cover letters, interview prep, and discovering public jobs from ATS APIs.
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    MIT
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    Provides real-time electricity grid data including CO2 intensity, power mix, and wholesale prices, plus optimal green time windows for energy-intensive AI tasks. Supports UK, Germany, and global regions with optional API keys.
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    MIT
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    Search 47,000+ marketing agencies and get AI-matched with fitted agencies, from Pick an Agency.
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    MIT
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    Converts a Figma file into a React project using Ant Design, AG Grid, ApexCharts, and Tailwind CSS, with optional export of mobile screens as a React Native (Expo) app.
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    44 npm
    MIT
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    Enables an MCP-compatible AI client to author Blender Python, run Blender, import the resulting asset into Unity with materials and a prefab, place it in the active scene, verify the import, and revise the same asset using stable IDs.
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    MIT
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    Enables AI agents to debug and repair historical Solaris/SPARC systems by providing an out-of-band control plane with guest DTrace, QEMU monitor access, SPARC-aware GDB, host eBPF/perf tracing, and an immutable evidence ledger for cross-layer hypothesis testing.
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    MIT
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    Fetches a URL and returns the main content as clean Markdown, using plain HTTP when possible and headless Chromium for JavaScript-rendered or bot-protected pages.
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    24 PyPI
    MIT
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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.
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    Apache 2.0
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    Enables agents to convert Markdown into WhatsApp-compatible formatting, including styled text, lists, and tables that fit a phone's monospace width.
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    59 npm
    MIT