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    A Model Context Protocol (MCP) server for developing Django applications. It exposes Django project information through MCP tools, enabling AI assistants to better understand and interact with Django codebases.
    Last updated
    107
    MIT
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    Bridges Django applications with AI assistants by implementing the Model Context Protocol, enabling AI to interact with Django data and functionality through simple decorators.
    Last updated
    16
    Apache 2.0
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    A minimal MCP server with get_weather and create_ticket tools, used for testing MCP servers across protocol, unit, eval, transport, and auth layers.
    Last updated
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    Unit converter for AI agents, powered by the GNU units database — convert 3000+ units of measurement, evaluate compound unit expressions, reduce to SI base units, dimensional analysis. Offline, deterministic.
    Last updated
    6
    1
    GPL 3.0
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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.
    Last updated
    3
    27
    Apache 2.0
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    An MCP server that provides deterministic unit conversions backed by Pint, enabling exact unit conversions, compatibility checks, and parsing of quantities for LLMs.
    Last updated
    5
    MIT
  • F
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    An MCP server that sends plain-text Gmail messages only to a predefined allowlist, using generated recipient IDs instead of email addresses to enforce security.
    Last updated
    2
    1
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    An MCP server that wraps DrissionPage to provide comprehensive browser automation tools, including tab management, element interaction, network capture, and more, with AI-friendly tool descriptions and 255 unit tests.
    Last updated
    55
    3
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    One-pass agentic inbox triage as an MCP server: fetch unread Gmail → classify (action_needed/fyi/newsletter/noise) → summarize → extract tasks → draft replies as Gmail DRAFTS (never sends) → flag calendar → write a triage report. Four stdio tools (fetch_emails, save_gmail_draft, append_tasks, write_report); the host is the LLM, so it runs keyless in Claude Code. Gmail scopes: readonly + compose
    Last updated
    4
    4
    MIT
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    Deterministic time-series statistics for AI agents. This MCP server gives any LLM agent unit-tested statistical tools — anomaly detection, changepoint detection, seasonal decomposition, stationarity/trend tests, data-quality audits, baseline forecasts — with schema-validated structured output and no arbitrary code execution.
    Last updated
    17
    MIT