"Information about crawer or crawler" matching MCP servers:

Enables agents to discover, search, compare, and inspect tested MCP tools by problem or keyword, with certification verdicts, scorecard summaries, certified scope, and explicit not-tested details.

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.

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.

Enables AI coding tools to run CheckMyLaunch scans on GitHub repos or live URLs and retrieve findings and repair prompts directly within the chat.

Lets an AI assistant statically scan HTML and JavaScript landing-page code that turns Meta's fbclid URL parameter into the _fbc cookie (and hand-written _fbp cookies), flagging known ways the click ID is changed, truncated, or kept from an older ad, without executing the code or contacting Meta.

Lets AI agents ask which tests a Playwright or Vitest project contains, which are skipped and why, by reading the test source files statically. Nothing is executed, written, or sent over the network, and answers come back as paged JSON with summaries, filters, and scan diagnostics.

Enables coding agents to compile supplied files, run optional focused tests, and get static findings across ten programming languages, providing a deterministic feedback loop on the code they are about to return.

Enables AI agents to measure Chinese, Japanese and Korean page titles by rendered pixel width and judge whether they fit Google's search result column, flagging titles that would be truncated or cut near the edge. It also reads tags from local HTML files or directories and applies the same width, boilerplate and keyword-zone checks.

Umbra is the trust layer for AI-generated code. It scores any repo 0-100 with file:line evidence (security, slop, Docker-verified build/boot, and claim receipts that catch agents lying about tests), and guards agent file writes mid-stream blocking leaked keys, alg:none JWTs, and git-hook plants before they land. Tools: scan_repo, guard_content, get_score.

Render, analyze, and verify audio (WAV or FLAC) through a fully offline, deterministic engine, exposed as MCP tools for AI agents.

Enables LLMs to read existing PageSnap session packs and map locators to Playwright, Selenium, or Cypress without capturing or opening a browser.

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.

MCP server for axe-core accessibility audits. Enables scanning URLs or HTML for WCAG violations with impact levels and fix guidance.

Generates synthetic time-series test data with configurable trend, seasonality, noise, anomalies, and multiple correlated streams, outputting JSON, CSV, or SQL.

Runs SQL statements in memory against real PostgreSQL 18 and SQLite 3.49 engines after loading your schema and sample rows, returning each statement's own verdict: errors with line, column, and hints, constraint violations, or the resulting rows. It also compares both dialects to expose portability differences, all with no database server, network, or API key.

Enables AI-assisted visual regression testing by capturing baselines, comparing screenshots, and using AI to judge whether visual differences are bugs or acceptable changes.

AI-driven mobile app testing via MCP, enabling AI coding agents to test Android apps without test frameworks or testIDs.

Enables coding agents to drive and inspect running Shiny apps (R and Python) by setting inputs, clicking, reading outputs, and getting detailed error information.

Automated Playwright E2E test repair powered by a self-improving, governed MCP server that runs failing tests, collects failure artifacts, reasons about root causes, validates and applies fixes, and re-runs to verify.

Enables running Lighthouse web performance audits via MCP, providing Core Web Vitals, performance scores, and optimization suggestions for single or multiple URLs.

An MCP server that turns Zod schemas into mocks, violations, and contract tests, enabling AI agents to reason about API contracts without manually crafting payloads.

An MCP server that lets AI agents run PHP unit and integration tests inside Docker containers without local PHP or Composer.

Enables AI assistants to access RenderDoc capture data and assist with graphics debugging by retrieving draw calls, shader information, buffers, textures, and pipeline state.

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.

Peeko is a read-only MCP server that provides Claude with screenshots of iOS Simulators, Android emulators, or physical Android devices.

Free, rules-based checks for e-commerce product pages: AI shopping readiness (structured data, reviews, return and shipping terms, GTINs, AI crawler access), Google Merchant Center compliance, store SEO audit and Shopify checkout deadlines. No AI calls, nothing stored.

Enables validating JSON/JSONC, getting/setting values with jq-like paths, pretty-printing or minifying, validating against Ajv JSON Schema, and diffing local files or inline strings without network calls.

Turns JUnit XML test reports from CI into queryable QA metrics, letting AI assistants answer plain-English questions about failures, flaky tests, regressions pinned to a commit, root-cause clusters, and performance drift. Also generates ready-to-share QA health reports and self-contained HTML dashboards without logging into separate tools.

Rarefaction is a Model Context Protocol (MCP) server that gives a coding agent the call graph and code context for one symbol straight from the project's language server (Language Server Protocol, LSP). Ask about a function, method or type and get, in one call: its signature and doc, its body, who calls it (tests marked), what it calls, who implements it, the tests that reach it and the short list

Provides MCP tools to verify logical expressions and retrieve decision statistics, with verdicts VALID, INVALID, or UNDECIDED.