"How to Create Looker Dashboards" matching MCP servers:

Automates Looker Studio dashboards using Playwright, enabling creation, modification, screenshots, and exports.

Enables an AI assistant to explore BigQuery datasets, run read-only queries and create views, then build and refine dashboards in the Looker Studio editor — charts, text, shapes, themes and exact layouts — verifying the result with screenshots. Write actions are gated behind explicit configuration, dry-run and audit logging.

Fetches a URL and returns the main content as clean Markdown, using plain HTTP when possible and headless Chromium for JavaScript-rendered or bot-protected pages.

MyChart MCP Server

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

Enables AI agents to fetch one or many web pages concurrently and receive clean, LLM-ready Markdown with navigation, ads and boilerplate stripped away, plus extracted metadata such as title, description, author, Open Graph tags and canonical URL. It runs locally over stdio with no API key or account, requiring only a single command.

Enables an LLM to control a separate Chrome session on Avito for searching and parsing listings, reading account and Pro dashboards/statistics, switching profiles, and editing forms. Requires explicit confirmation for irreversible actions.

An integration that allows Large Language Models to interact with Raindrop.io bookmarks through the Model Context Protocol, enabling users to create and search bookmarks directly through AI assistants.

Fetches website content and converts it to Markdown format with AI-powered content cleanup, ad removal, and full OpenAPI/Swagger specification support for easy processing by AI assistants.

Enables agents to transform tabular Markdown content into structured, type-inferred records with normalized formatting through an MCP-compatible interface.

Enables converting Markdown and HTML tables into structured JSON records with automatic column type inference and format normalization. It also offers supporting web-agent primitives such as DOM semantic pruning, form field auto-mapping, and execution trajectory evaluation, all via a zero-dependency MCP server.

Measures and improves how findable, readable, and usable a website is to AI answer engines and autonomous AI agents through hosted AEO audit tools.

Enables browser automation over MCP using a real Chrome browser with existing profile, supporting real tabs, downloads, cookies, and RPA workflows.

Lets an AI assistant check any URL to see how much of a page's main content is present in the raw HTML versus only after JavaScript runs, showing which text blocks, meta fields, canonical tags, JSON-LD and links AI crawlers like GPTBot and ClaudeBot cannot read. It also reports what robots.txt allows for 22 AI bot tokens and how the site responds to each bot's user-agent.

Enables AI agents to drive a persistent Chrome session that stays signed in to your own Google account, with tools for navigation, snapshots, clicking, typing, keystrokes, screenshots, JavaScript evaluation, and lifecycle or re-login control. It also exports every row behind a Looker Studio report to CSV and checks whether the session is still healthy.

Enables secure access to Tor/onion services with content filtering and safety guardrails for AI assistants.

Converts X (Twitter) posts into JSON, PDF, PNG, Markdown, or Slack/Discord messages using public endpoints, no API key or login required.

Enables English and Chinese web search through zero-key sources, plus optional paid providers under an explicit routing policy, without requiring an API account to start. Returns compact multi-source results that preserve provenance, provider failures, and bounded evidence budgets so agents can inspect how each result was found.

Converts any webpage URL to clean, well-formed Markdown with title and H1 preservation, URL validation, and graceful fallbacks. One of 16 single-purpose servers in an open-source monorepo with full CI/CD to PyPI.

Enables AI agents to interact with Dash dashboards by exposing them as MCP servers via a WebSocket bridge, with automatic tool registration and human-in-the-loop confirmation.