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    Enables AI agents to analyze a piece of content across 11 dimensions and receive ranked, scored recommendations among six cross-media output formats (PPT, infographic, comic, short video script, newsletter, reusable skill), then generate dispatch prompts for the chosen format. It also exposes the format catalog and profile schema as read-only tools, supporting batch routing of an entire content library.
    1
    MIT
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    quality
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    AutomateLab Content Distribution publishes content across DEV.to, Hashnode, GitHub Discussions, Reddit and Bluesky, with browser workflows for LinkedIn, Medium and X. Tracks publishing state and adapts content per platform. Product and documentation: https://automatelab.tech/products/mcp/content-distribution-mcp/
    8
    283 npm
    4
    MIT
  • A
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    quality
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    maintenance
    Google Search Console for Claude and other MCP clients. Sign in with Google in one click, then ask about clicks, queries, rankings and indexing, export every GSC report as CSV (beyond the 1,000-row UI limit), inspect URLs, submit sitemaps and verify sites. Includes a local SEO dashboard. Free, open source, runs on your computer.
    18
    132 npm
    MIT
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    Enables users to audit personal reading streams by quantifying category diversity with Shannon entropy, detecting lexical redundancy and echo chambers via Jaccard similarity, and ranking content sources by decibel signal-to-noise ratio for pruning recommendations.
    7
    MIT
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    quality
    B
    maintenance
    Plan SEO pages in an SEO Content Machine Workspace, then have its page agents research, write and review each page as a draft. A stdio bridge to the SCM desktop app, which must be running on the same machine.
    MIT
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    Lets Claude Code and other MCP clients drive the SEO Content Machine desktop workspace on the same machine: starting and running tasks that scrape search results, crawl a site's internal links, pull Google Maps listings with ratings and reviews, download archive.org copies, extract page values into CSV, and add or update SEO Workspace pages, then read their results.
    MIT
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    quality
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    Enables finding information online, reading web pages, finding images, capturing screenshots, and performing multi-source research with per-answer confidence.
    5
    AGPL 3.0
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    Enables AI agents and their users to retrieve scored news sentiment, narratives, historical readings, and cited sources for Bitcoin, gold, and oil, with tamper-evident, time-stamped data for trading decisions.
    5
    MIT
  • A
    license
    A
    quality
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    maintenance
    Free multi-source search for AI agents with multi-source verification, token savings, and MCP native support.
    7
    164 npm
    112
    Apache 2.0
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    Job search mechanics for an AI assistant: search Arbeitnow/Adzuna/JSearch, fetch a single job posting, render a CV to PDF, lint it against your own configurable anti-fabrication rules, and log the outcome to your application registry. Never auto-applies.
    7
    108 PyPI
    MIT
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    quality
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    Free web search, web-page reading as Markdown, and llms.txt documentation retrieval for MCP clients. Runs locally with Node.js over stdio using @alkasima/alka-search-mcp. Searches DuckDuckGo, Mojeek, and Brave; default providers require no API key. Website and provider availability may vary.
    8
    3
    39 npm
    MIT
  • A
    license
    A
    quality
    F
    maintenance
    Free multi-source web search server for AI agents, with confidence scoring and token optimization.
    3
    164 npm
    Apache 2.0
  • A
    license
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    quality
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    Provides a unified web search tool for AI agents by running multiple search providers concurrently and returning normalized results. It integrates with Claude Code, Codex CLI, OpenCode, and Hermes.
    1
    142 PyPI
    12
    MIT
  • A
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    quality
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    maintenance
    Provides a pay-per-query web search tool for AI agents via Lightning Network sats, enabling no-KYC, account-free searches through the MCP protocol.
    2
    102 npm
    MIT
  • A
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    quality
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    Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.
    25
    180 PyPI
    3
    MIT
  • A
    license
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    quality
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    Odds are, most of what you want to build is already open source. Tell your AI agent what you're making, and it finds it: which repos to use as they are, which to adapt, and what's left for you to write. Every repo it names is real, licensed for your use or flagged, and checked live.
    3
    480 npm
    1
    MIT