"Chain MCP Experimental Results" matching MCP servers:

An MCP Server that provides access to Google's Cloud Tool Results API, enabling applications to programmatically interact with test results from Firebase Test Lab and mobile app testing through natural language.

MCP server for autonomous end-to-end testing with Wopee.io. Analyzes web applications, generates and executes Playwright-based functional tests, and validates results — all driven by natural language commands.

Enables coding agents to read Squally CI data, including test results, flakiness, and failure diagnostics.

An MCP server that gives coding agents hands and eyes on an Android device, providing 19 tools for building, testing, installing, UI inspection, input, logs, and toolchain diagnosis. It returns concise, structured results to make the build-debug loop efficient.

MCP server for managing test cases, cycles, and results in Zephyr Scale on self-hosted Jira. Enables AI agents to create, search, update, and delete test artifacts through natural language.

Run the requests in a Postman collection folder and get structured, assertion-level results back straight from your AI assistant.

An MCP server that grades prompts against a validated rubric, tracks real outcomes, and provides guidance grounded in research on what predicts good results.

An MCP server that lets an agent read its own eval results, run suites, explain failures, check drift, and view judge calibration status.

Enables testing how different MCP clients handle tool results containing both content and structuredContent, including outputSchema enforcement and mismatch scenarios.

MCP server exposing SuperAudit’s free website audit as a callable tool, enabling AI agents to audit any public URL and receive scores across SEO, security, legal, performance, and more. No API key required; respects rate limits and caches results.

Exposes a set of honesty SDK TypeScript libraries as MCP tools so a coding agent can check grounded citations, corroborate evidence, test payout and mutation invariance, score trust and anonymous authenticity, validate provenance claims, track a claims registry and tamper-evident audit chain, and grade recommendations against outcomes. It also scaffolds two runtime kits for agent authorization receipts and pre-call cost governance.

Enables evaluation of patent feature-separation results by listing records, checking alignment with claims and original text, and running deterministic quality gates plus a Judge audit.

Lightweight Node.js dependency vulnerability audit tool with CLI and MCP Server modes. Supports npm/pnpm, full dependency chain tracing, remote GitHub repo auditing, and generates Markdown/HTML reports.

MCP server that integrates with Testmo to let AI assistants read projects, runs, results, and test cases, and create or update runs, results, and cases via natural language.

Enables AI coding agents to discover, generate, and run Cocotb co-simulation testbenches against Verilog/SystemVerilog designs, returning structured pass/fail results and tracebacks without manual simulator or Makefile setup.

Analyzes Playwright test results to provide structured QA insights, including test metrics, failure analysis, bug report drafts, and release-quality recommendations.

Enables AI agents to audit web surfaces for conformance and generate findability and delivery metadata, including meta tags, JSON-LD, sitemaps, robots.txt, image markup, and contrast-checked palettes, with provenance-stamped results.

Connects AI coding assistants to PyCharm's code quality inspections and optionally SonarQube for IDE, providing unified, de-duplicated code analysis results without uploading source code.

Provides three AI security tools for Claude: scanning MCP servers for security risks, validating HDP delegation chains against IETF standards, and triaging security alerts with kill-chain analysis.

An MCP server for running Playwright tests and reading structured results, failed test details, and attachment content, designed for AI agents doing test failure analysis.