"Information about Meta ads or advertising on Meta platforms" matching MCP servers:

An MCP server exposing every documented Email on Acid API v5 request as a tool — 24 tools across authentication, email client lists, email rendering testing, and spam testing.

MCP server for self-hosted qTest Manager, enabling natural-language management of projects, modules, test cases, requirements, traceability, and test execution via the qTest REST API.

Enables a stateless, horizontally scaled MCP server using the 2026-07-28 specification, with tools for load testing and instance-aware operations.

Analyzes websites for broken links, missing meta tags, and redirect chains, returning a health score and actionable suggestions.

Enables checking whether a Meta, LinkedIn, or Google Ads campaign is structurally able to serve and convert before spending, by inspecting schedule, bid, destination, approval, geo, and budget fields through read-only tools. It also reconciles reported spend across the three platforms against a ledger to surface discrepancies, armed campaigns, and drift.

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 coding agents to verify whether a GitHub pull request is genuinely ready by checking draft state, conflicts, check results on the head commit, review requirements, merge queue status, and expected commit, returning a verdict with reasons and owners pinned to a commit and timestamp. It reports merged or closed PRs without judging them and never authorizes a merge.

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.

Measures what MCP servers cost in context tokens: probes a URL or a local command now, measures a whole config file, and looks up the daily results for every server in the official MCP registry on mcpcost.ulehla.dev.

Enables AI assistants to run code in 24 programming languages on HackerEarth's sandboxed servers and read the printed output or errors, without installing local toolchains. It also lists supported languages with exact identifiers for use when submitting code.

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

Screen-reader navigation cost analyzer. Measures how hard it is for assistive-technology users to discover, reach, and operate interactive targets on the web.

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.

MCP server that exposes Dira ProSuite quality verification to AI assistants, enabling data quality checks on geospatial datasets through natural language.

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.

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.

Enables AI assistants to generate realistic, synthetic test data on demand, including valid PESELs, NIPs, addresses, and more across 27 EU countries, through two tools: list_generators and generate.

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.

Enables MCP clients to run fresh audits of any public web page on mobile or desktop, returning category scores, lab metrics, and prioritized findings for performance, accessibility, best practices, and SEO. Each call performs a new uncached audit, so users can compare results within a conversation.

Exposes six evidence-oriented tools over stdio so MCP clients can navigate unfamiliar code, ask typed questions about repository evidence, review completed changes, and select existing tests.

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.

Grades MCP servers on agent usability (A–F) — description quality, schema design, tool naming and token cost, the properties that decide whether a model picks the right tool. Benchmarked across 36 popular servers; a third scored D or F.

Enables LLM agents to programmatically inspect, debug, and test other MCP servers by wrapping the MCP Inspector CLI. Supports listing and calling tools, reading resources, and testing prompts on both local and remote MCP servers.

Provides AI coding assistants with on-demand access to component specs, test scenarios, accessibility requirements, and build guides from the Web UI Component Specification.

Audits Excel workbooks by tracing cell dependencies and detecting circular references, volatile functions, and other formula risks, enabling natural-language audit queries on local files.

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.

Wraps Claude Code's code-review skill so any MCP client can run reviews over a PR, branch, working directory, or last commit, with five parallel reviewer subagents, low-to-max effort levels, and optional fix mode that edits files in place. Also supports follow-up questions on a previous review session and a free environment self-check.