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    MCP server that generates ISO/IEC/IEEE 29119-3 compliant test plan drafts from project information, providing a structured resource for the standard's test plan outline and a tool for draft creation.
    1
    83 npm
    MIT
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    Not graded
    quality
    C
    maintenance
    Exposes 11 agent-native QA tools over stdio so coding agents can discover a project, analyze risk, select the smallest relevant test set, generate and dry-run tests, triage failures, propose tiered heals, analyze flakes, generate quality reports, and evaluate release readiness. Planning and healing tools stay read-only or propose-only, while execution defaults to dry-run, keeping agent actions safe and evidence-backed.
    MIT
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    Enables AI agents to submit npm, PyPI, Go, or Maven packages and manifests to the free OSV.dev database and receive per-package and per-advisory results with CVE mappings, CVSS scores, severities, and the versions that fix each issue. It also supports filtering by minimum severity, de-duplicating alias advisories, and machine-readable error/warning rows for CI gates and upgrade recommendations.
    3
    MIT
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    MCP server for the Ghost Inspector API that lets agents inspect and manage end-to-end browser tests, offering read-only tools for inventory, module usage, and stale test analysis, plus opt-in guarded write operations.
    5
    88 npm
    MIT
  • A
    license
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    Read visual bug reports from Feedbug in your AI coding agent: screenshot, console logs, failed network requests, session replay and the DOM context of the element the tester clicked. Trace the bug to its source file, comment and resolve without leaving the editor.
    7
    4 npm
    MIT
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    quality
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    Fail-closed merge gate for AI coding agents: verify_repo runs the tests that existed before the change against a git working tree and answers MERGE, BLOCK or INCONCLUSIVE. The agent names what to judge; the operator pins the baseline and the floors.
    2
    1,384 PyPI
    4
    AGPL 3.0
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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
    29 npm
    1
    MIT
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    Audits a module against its test suite and reports the cases the tests are structurally unable to see, then proves each gap with a real failing test rather than a warning. Covers Python, TypeScript, JavaScript, Java, Rust and Go.
    4
    3
    Apache 2.0
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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
    62
    AGPL 3.0
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    Provides instant GDScript syntax validation and diagnostics by bridging Godot's native Language Server Protocol to MCP clients. Enables real-time syntax checking in AI assistants without requiring custom plugins or context switching to the Godot editor.
    4
    44 npm
    48
    MIT
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    A
    quality
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    maintenance
    Give AI agents 10 offline tools for market observations, repeated headlines, forecast evaluation, correlation risk and statistical checks. Preserve source clocks, missing data and stated assumptions. Python, CLI and MCP share the same zero-dependency core; no feed collection or trade execution.
    2
    10
    344 PyPI
    MIT
  • A
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    quality
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    maintenance
    Email inboxes for AI agents: create a throwaway inbox, then block until the OTP or magic link arrives and get it back as a field. 7 tools, stdio, Python.
    8
    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
    58 PyPI
    1
    MIT