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    A simple MCP server that exposes datetime information to agentic systems and chat REPLs
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    MIT
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    An MCP (Model Context Protocol) server that gives AI agents live, structured ad intelligence across Facebook, Google, and Instagram — data that no base model can produce from training alone. Powered by Apify actors. Works with any MCP-compatible client: Cursor, Claude, etc.
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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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    Search and retrieve detailed information about Swiss companies from the official Zefix register, including company profiles, corporate structures, and SHAB publications.
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    MIT
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    An MCP server that provides information about Utkarsh, including bio, skills, work experience, and portfolio projects, accessible via local stdio or remote HTTP with OAuth.
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    Provides comprehensive GDPR compliance assessment tools for AI/ML systems, including lawful basis determination, DPIA generation, and data subject rights handling. It also crosswalks GDPR requirements to EU AI Act obligations with AI-specific considerations throughout.
    6
    4 npm
    321 PyPI
    MIT
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    Connects DHIS2 health information systems to AI assistants via the Model Context Protocol, enabling natural language queries for analytics, metadata, and tracker data.
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    MIT
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    Enables AI coding agents to discover, compare, select, and enforce design systems and component libraries, with installation guidance, component APIs, and strict adherence directives to prevent default substitutions.
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    MIT
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    Enables AI systems to search, retrieve, and analyze Korean legal information from the National Law Information API (law.go.kr), including laws, administrative rules, English translations, and law-ordinance linkages.
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    Enables large language models to retrieve up-to-date and correct information about dlt pipelines, datasets, and schemas, improving AI-assisted development.
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    235 PyPI
    10
    Apache 2.0
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    Enables users to ask natural-language questions about a local folder's contents, including file names, sizes, and timestamps, with rollups by type and age and cleanup suggestions for stale or large files. It returns metadata only and cannot read, move, or delete files.
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    MIT