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    MCP server exposing content contract validators (SEO.md, PRODUCTHUNT.md, LINKEDIN.md) as tools so AI agents can verify generated content against concrete rules without maintaining linters. It provides linting and JSON-LD export tools with config and content passed as parameters, not file paths.
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    MIT
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    Deterministic SNAP eligibility logic, exposed as auditable Model Context Protocol tools. An AI agent can read, reason, and orchestrate, but the eligibility determination itself is made by versioned, tested, cited code that a caseworker, an auditor, or a court can inspect.
    5
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    Licensed, rights-cleared content for AI agents, 17 tools to discover, license, retrieve, and verify expert content with on-chain proof and EU AI Act Article 53 support.
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    MIT
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    Enables reading and verifying C2PA Content Credentials from images and videos through both embedded manifests and invisible watermarks. Supports direct filesystem access, URL checking, and provides structured provenance data including creator identity, AI generation info, and content authenticity.
    2
    MIT
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    Dynamic QR code platform for AI agents. Create, customize, and track QR codes without regenerating images. 37 tools covering 11 QR types (URL, vCard, WiFi, event…).
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    MIT
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    Enables AI agents to extract clean, structured web content (articles, tables, links, visual layouts) optimized for LLM token efficiency, with fast response times and optional JavaScript support.
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    64
    MIT
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    Extract content from URLs, documents, videos, and audio files using intelligent auto-engine selection. Supports web pages, PDFs, Word docs, YouTube transcripts, and more with structured JSON responses.
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    MIT
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    Enables AI clients to browse instruments, items, dimensions, expert assignments, and calculate Content Validity Index (CVI) via a standard MCP interface.
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    MIT
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    Provides access to over 140 articles from the AntiEntropy Resource Portal covering nonprofit governance, compliance, and HR policies. It enables users to search, browse categories, and read full article content through an MCP-compatible client.
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    An MCP server that uses AI to generate structured Asana project plans from diverse sources like text, PDFs, and meeting transcripts. It enables users to preview, generate, and directly sync detailed task lists, subtasks, and dependencies into Asana.
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    Manage Job using MCP: Manage Job, Candidates, Resumes, Salaries all within this one MCP tools It can solve problems like: You have 50 resumes to screen. Your AI assistant can reason about candidates, but it can't: Read PDFs/DOCX — The AI can't open binary files Extract structured data — Copy-pasting loses formatting, metrics, and context Compare at scale — No consistent scoring across candida
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    Enables direct access to raw Markdown content from files or directories without processing. Perfect for providing AI models with business rules, documentation, or knowledge bases exactly as written.
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