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    Enables editorial content QA over the Model Context Protocol with four local tools that analyze readability, AI-sounding language, SEO on-page factors, and produce full reports where every finding includes an actionable fix.
    4
    1
    MIT
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    Enables generating NBT structures, placing them in superflat worlds, capturing labeled screenshots, and exporting clean datapacks through MCP.
    13
    1
    MIT
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    Enables AI agents to hire real human operators for tasks requiring physical presence, human perception, or judgment, such as verification, testing, data collection, and physical-world tasks.
    4
    58 npm
    1
    MIT
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    Enables recurring website maintenance checks — domain registration, SSL certificates, uptime, technical SEO and accessibility — across a portfolio of client sites, using publicly available information. Results are returned as structured data and can be sorted by urgency into a client-ready report.
    8
    71 npm
    MIT
  • A
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    quality
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    maintenance
    A thin MCP server that wraps provenance-receipts and quality-gate services as tools, enabling AI agents to certify content origin and score quality via Ed25519-signed receipts.
    5
    55 npm
    MIT
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    Enables AI agents to hire verified human operators for tasks requiring physical presence, human perception, or judgment, such as real-world verification, product testing, and data collection.
    6
    MIT
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    Enables agents to measure a live page or Figma frame against a reference design, reporting exact numerical deviations in layout, spacing, typography, colors, states, and animations before any baseline exists.
    4
    17
    MIT
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    MCP server for verifying AI agent claims vs reality — single-transcript inline grounding-check that flags when an agent's response states facts not in the input context, when its code silently swallows exceptions and substitutes mock data, or when its multi-turn transcript contains contradictions or unverified completion claims. Sub-second, local, free, no API calls.
    4
    41 PyPI
    1
    MIT
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    Enables AI agents to drive the 1C:Enterprise test client directly, opening forms, reading and modifying data, working with tables, and recording or replaying action scenarios. Connects to local or remote test clients over their network protocol without a testing manager.
    10
    55
    AGPL 3.0
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    Enables AI coding agents and IDEs to prove SystemVerilog assertions with SymbiYosys (smtbmc+z3) and lint SVA syntax, returning honest verdicts such as PROVEN, FAILED, UNKNOWN, ERROR, or TIMEOUT.
    3
    10 npm
    Apache 2.0
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    Enables driving an iOS Simulator from a model: taking screenshots, reading the UI tree, tapping, swiping, typing, managing app lifecycle and device state such as appearance, permissions, location, and notifications, without code signing or a physical device.
    21
    337 npm
    MIT
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    Open behavioral litmus for MCP servers — grades A–F across tool-output injection, egress, sensitive-data, and adversarial-input, with reproducible, content-addressed evidence. Tools: run_litmus, verify_attestation.
    4
    269 npm
    8
    Apache 2.0
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    Enables LLMs to read existing PageSnap session packs and map locators to Playwright, Selenium, or Cypress without capturing or opening a browser.
    4
    MIT
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    quality
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    maintenance
    Generates realistic, referentially-coherent test data (SQL INSERTs, JSON, or CSV) from your database schema, resolving foreign keys and respecting constraints. Paste CREATE TABLE DDL or a JSON schema and get ready-to-run seed data with valid relationships.
    2
    50 npm
    MIT