"A simple test or quiz" matching MCP servers:

. A good description should be concise and describe what the server enables users to do, e.g. * Enables to interact with WordPress sites...' Then a huge block? Actually the user message includes the README content inside tags, then after the readme, there is a large block of text starting with '{

Enables test execution and management through MCP clients, allowing retrieval of projects, listing tests, executing tests with browser selection, and monitoring results.

Enables AI clients to analyze software test results and defect records, producing explainable GO, CONDITIONAL_GO, or NO_GO release-readiness recommendations with deterministic risk scoring, failed-test retrieval, defect hotspot ranking, and regression test planning.

MCP server for end-to-end QA automation: generates test scenarios, discovers Playwright locators, creates TypeScript test code, executes tests, and creates GitHub issues for failures.

A test harness for MCP servers that validates server JSON, tool schemas, performs golden file diffing and schema drift detection, and generates signed test reports with Shields.io badges.

An end-to-end test MCP server built with FastMCP that exposes a REST API as a set of tools for AI agents. It enables LLMs to perform CRUD operations on an upstream API by mapping HTTP methods to MCP tools.

Enables automated analysis of test suite traces to identify timing races and state pollution, helping detect flaky test non-determinism in CI/CD workflows such as Datadog CI or Trunk.

Detects breaking changes in a TypeScript library's public API and recommends the semver bump, comparing two npm releases, git refs or a working tree. Each finding is graded proven or review-only.

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

Connects AI coding assistants to Gaffer test history and coverage data to analyze project health, debug failures, and identify untested code areas. It enables tools to track test stability, cluster failures by root cause, and monitor code coverage trends across projects.

Generates a daily standup note from GitLab merge request or GitHub pull request state: what is ready to merge, what is blocked, what is stale, and what is waiting on your review. When CI is red it opens the failed job's log and reports the error lines, so the note says why the pipeline failed rather than just that it did.

MCP server for publishing HTML or Markdown to a live hosted URL via htmldrop. Provides tools to publish, list, and delete hosted sites, with remote OAuth and API token authentication.

Enables AI assistants to summarize Playwright test runs, identify flaky tests, heuristically triage failures, generate Playwright test stubs, and retrieve recent GitHub CI status through MCP tool calls.

Provides MCP tools to get a single-call snapshot of git and GitHub Actions CI status across all repositories in a folder, flag missing or stale architecture docs, write doc files, and detect release drift between source and release repositories.

Enables AI coding tools to validate local projects and publish or update applications to Bedengan App Hub via API, with automated checks and live deployment without manual approval.

Enables scanning Python repos for dead code and automatically drafting a branch + PR for the safe subset (unused single-name imports) after running the repo's full test suite. All other findings are reported without modification, and a human always merges.

MCP server providing tools to verify task completion (tests pass and changes match claim) and confirm bug reproduction before fixing.

Record an agent's MCP tool-call workflow once, replay it deterministically for zero tokens, and get a receipt — a snapshot-testing and deterministic-execution layer for Agent Skills.

Stops your AI from re-introducing bugs, leaking provider keys, or weakening tests. Bug fixes become permanent regression guards; blocked mistakes become AI lessons the agent reads and learns from before its next edit.

Enables AI coding agents to compute a 0-1 diff risk score for the current branch or any pull request, exposing the driving signals, evidence, tier and resulting auto-approve or human-review policy decision. Agents can use it to decide whether a low-blast-radius, AI-reviewed PR is safe to merge automatically while flagging risky changes for a human.

Enables code-review gating by converting a git diff into a typed verdict with safety probabilities, severity, and recommended actions for auto-merge or human review.

Deploys and manages projects on Swigs Cloud from any MCP client, turning folders or git repositories into live HTTPS sites in about two minutes.

Compacts noisy test, build, and cloud-log output before an AI agent reads it — dedupes repeats, collapses stack frames, folds Playwright retries, and renders CloudWatch/GCP JSON logs down to the signal. Typically 80–95% fewer tokens on failures. Tool: compact_output. Run: npx -y logslim logslim-mcp

Publishes what an AI made — a page, a markdown or PDF doc, or a whole site — to a live HTTPS link. Runs locally over stdio from the @drop2run/mcp npm package, or hosted at https://mcp.dropto.run/mcp for chats that connect by URL.

Runs a project's Playwright or CTRF test suite and returns a redacted failure packet (failing test, file and line, console errors, failed requests, rerun command) so a coding agent can fix and rerun. Also reports whether a commit has a signed, passing test receipt on GitHub.

An MCP server that enforces disciplined Git workflows by planning coding tasks into small, test-gated commits, ensuring tests pass before staging and preventing out-of-scope or oversized changes.

MCP server that aggregates test failures, cross-references flakiness history, and outputs a release readiness verdict.

Blocks unsafe PostgreSQL migrations before an AI agent writes or runs them. check_before_apply returns a pass/fail gate; reads the real Postgres parser, classifies the lock each statement takes, checks 112 safety rules. Runs offline, no database required.

Before you move to Python 3.15 (or 3.15t), find every dependency with no wheel for it on your platforms — and the bump that fixes it. CLI, GitHub Action, MCP server.

Lets any MCP-capable client connect to the public Codemagic REST API to list apps and teams, inspect build history, and optionally trigger or cancel builds and manage team settings. Runs locally over stdio with the user's own API token and configurable read-only, build, or administrative permission modes.

Enables MCP clients to read a Forgejo, Codeberg, or Gitea instance—including users, repositories, issues, pull requests, search, notifications, comments, reviews, and Actions runs—with opt-in, time-boxed guarded writes for repository, branch, issue, pull request, comment, migration, push-mirror, and workflow operations.

Checks whether software dependencies (npm packages, GitHub Actions, MCP servers, Docker images) are alive, dormant, abandoned, archived, or deleted using dated observations from lastseen.dev.

MCP server that lets coding agents test AI agents. Create YAML test cases, snapshot golden baselines, check for regressions, and generate visual reports all from inside Claude Code or any MCP-compatible tool. Works with LangGraph, CrewAI, OpenAI, Claude, Mistral, and any HTTP API.

Enables CI/CD failure triage for GitHub Actions by inspecting failed runs, classifying root causes with LLM assistance, retrieving relevant runbook guidance, estimating flakiness, and either preparing dry-run fix PRs or publishing structured diagnoses to Discord for human review.

The network-change verifier for AI agents: validate a BGP or routing change in a real containerlab lab before it reaches production, and get a pass, fail or inconclusive verdict with evidence. Runs on FRR, Nokia SR Linux, SONiC and Arista cEOS.

Post-quantum readiness for AI coding agents: scans code for quantum-vulnerable cryptography (RSA/ECDH/ECDSA/DH) and returns NIST ML-KEM/ML-DSA/SLH-DSA (and hybrid) migration guidance, with fix verification and dependency checks. Content-based, advisory tools only; runs local (npx @quantakrypto/mcp) or as a hosted OAuth endpoint.

Enables agents and CI pipelines to audit MCP servers and agent tool-chains by statically scanning repositories, local checkouts, tools/list exports, or live endpoints for risks such as destructive actions without confirmation, mismatched safety annotations, injection surfaces, credential or PII exposure, and unguarded command, path, or URL sinks. All checks are read-only and never execute the scanned code or call tools/call.

Tells your coding agent which tests to run after a change, and whether a failing test is its fault. Tools: select_tests (only the tests the change can affect, with reasons), triage_failure (new regression, pre-existing, flaky or unknown) and explain. Needs a self-hosted siftwise server; fails open to the full suite. Tested with Claude Code, Copilot, Cursor, Codex and Gemini.

Enables agents to run Playwright suites, diagnose failures from trace-level DOM, network and console evidence, and apply locator fixes that are re-run and reverted if still red. It also repeats failing tests for per-test flaky, regressed or broken verdicts and surfaces the same diagnosis and fix diffs in CI job summaries and PRs.

A temporary MCP server that scrapes Bitrise Insights using Playwright to fetch flaky test data, providing tools to query workspace and app test insights until the official API is released.