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    Provides AI assistants with token-efficient access to Google Play Android Vitals, enabling them to diagnose ANRs, track crashes, analyze startup performance, and compare app versions for release optimizations.
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    19
    MIT
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    Enables AI assistants to query the Google Play Developer Reporting API for Android production stability data, including crash and ANR issue clusters, de-obfuscated stack traces, release track discovery, startup and crash metric trends, version-to-version comparisons, and anomaly alerts. It also provides guided prompts for incident triage, baseline profile verification, and weekly stability reporting with built-in token compression and caching.
    10
    MIT
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    Enables AI agents to play, test and QA Twine / interactive-fiction HTML games by reading passages as Markdown, clicking numbered choices, inspecting story variables, screenshotting, and saving or restoring state to explore branches. It provides a small, token-friendly semantic tool surface with format detection for SugarCube, Harlowe, Snowman and Chapbook games, plus live viewing, console error capture and journal tracking for clean playtesting.
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    34 npm
    MIT
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    Enables AI coding agents to query a local code graph over stdio, so they can see what a Git change may affect, find related tests, routes and nodes, and cite evidence paths — read-only and fully on-machine.
    6 npm
    MIT
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    Enables AI agents to safely run test suites over MCP, returning concise JUnit-based results, trimmed tracebacks, rerun-failed support, and flaky-test detection while handling timeouts, process cleanup, and bounded output.
    MIT
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    Simulates EVM transactions against forked chain state and explains why they revert, using Tenderly's free-tier API with decoded traces and source-mapped errors. Provides tools to simulate single transactions or bundles and inspect saved simulations, all with output size controls to keep responses affordable.
    MIT
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    Free, MIT-licensed MCP testing harness with Jay: risk-based testing workflows, exploratory and regression checks, accessibility investigation, bug triage, disposable demos, and protected local evidence reports. Runs locally via @testers-ai/carbon-mcp; the coding agent supplies model, browser, and shell access, and analytics defaults off in the npm edition.
    2
    MIT
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    Enables an AI to statically lint Dockerfiles and compose files without Docker by parsing their true structure, reporting line-numbered findings with concrete fixes, and analyzing cache order, .dockerignore matching, and safe fix previews as diffs.
    MIT
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    Enables agents to lint OpenAPI specifications and detect breaking changes between two versions of an API, normalising Swagger 2.0 and OpenAPI 3.0/3.1 into a single model with safe $ref resolution. It exposes schema-walking and example-validation tools over stdio, classifying each change as breaking, potentially breaking, or safe based on request-versus-response variance.
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    MIT