"Information About Puppeteer MCP" matching MCP servers:

MCP server for browserview.io that lets agents create, inspect, share, and destroy disposable cloud Chromium sessions, and connect via CDP using Playwright or Puppeteer.

Provides AI assistants with real-time access to the AGNO framework documentation by enabling them to browse, search, and fetch documentation pages. This server allows users to query information about AGNO's Agents, Teams, and Workflows directly through MCP-compatible clients.

Stealth browser automation over raw CDP, driving a real unmodified Chrome with no Playwright or Puppeteer in the stack. Returns numbered element refs from the accessibility tree so a model clicks ref 3 instead of guessing a CSS selector, and can attach to an already-running Chrome to reuse logged-in sessions.

Enables LLMs like Claude to navigate the web through Puppeteer-based tools and Steel. Based on the Web Voyager framework, it provides tools for all the standard web actions click clicking/scrolling/typing/etc and taking screenshots.

Enables browser automation for LLMs on Linux display servers, supporting web interaction, screenshots, and JavaScript execution in a real browser.

Enables AI clients to control the user's already-open, logged-in browser pages in real time over a local WebSocket channel, without Playwright, Puppeteer, Selenium, or any browser driver. Exposes tools for navigation, semantic page snapshots, clicking, form filling, JavaScript evaluation, screenshots, network monitoring, cookie handling, and tab management via the CDP.

A persistent memory implementation using a local knowledge graph that lets Claude remember information about users across conversations.

The AgentOps MCP server provides access to observability and tracing data for debugging complex AI agent runs. This adds crucial context about where the AI agent succeeds or fails.

A Model Context Protocol server that enables AI assistants to control a real web browser with stealth capabilities, avoiding bot detection while performing tasks like clicking, filling forms, taking screenshots, and extracting data.

Enables LLMs to perform web browsing tasks, take screenshots, and execute JavaScript using Puppeteer for browser automation.

Drive Clearcote, a Chromium build with its fingerprint protection patched into the engine, from any MCP client: about 20 tools to navigate, read, extract, click, fill, screenshot and keep sessions, plus a CDP endpoint that hands the same browser to Playwright or Puppeteer. The server lives in the repo's mcp/ folder (npx clearcote-mcp or pip install clearcote-mcp).

A server that enables AI models to access user geolocation information via EdgeOne Pages Functions through the Model Context Protocol.

A transparent message ferry between Claude Desktop and Claude Code CLI, enabling task delegation with any MCP configuration without the bridge needing to know about specific MCPs.

Enables Cursor agents to communicate via a shared chat room, allowing them to ask questions, share status, and warn about conflicts while collaborating on the same repo.

Enables browser automation and AI-driven workflows through Puppeteer integration, with file management, agent coordination, and QNAP network storage support.

A Model Context Protocol server that provides browser automation capabilities using Playwright, enabling LLMs to interact with web pages, take screenshots, and execute JavaScript in a real browser environment.

Enables read-only access to Pocket Agent's product information, public persona templates, and app catalog. No authentication required.

Enables AI models to access user geolocation information through EdgeOne Pages Functions, allowing location-aware AI interactions.

A Server-Sent Events implementation using FastAPI framework that integrates Model Context Protocol (MCP), allowing AI models to access external tools and data sources like weather information.

MCP server that enables Claude Code to communicate with other Claude Code agents over HTTP, allowing users to ask questions about remote codebases or delegate coding tasks.

An interface enabling high-frequency communication between AI tools (like Cursor and Windsurf) and users, allowing for option selection and information gathering through CLI, Web, or PyQt interfaces.

A unified browser automation protocol that connects AI agents to multiple automation backends including Selenium, Playwright, and Puppeteer. It provides a centralized interface for agents to navigate websites, execute JavaScript, and manage web interactions across various browser engines.

An MCP Server that provides weather information by ZIP code using Interzoid's API, allowing agents to retrieve current weather conditions based on postal codes.

An agentic AI system that orchestrates multiple specialized AI tools to perform business analytics and knowledge retrieval, allowing users to analyze data and access business information through natural language queries.

An authless Cloudflare Workers server that provides tools to scrape, analyze, and answer questions about websites using Cloudflare's Browser Rendering and AI capabilities.

A server that allows AI agents to consult multiple large language models (like Grok, Gemini, Claude, GPT-4o) through Model Context Protocol for assistance and information.

An MCP (Multi-Agent Conversation Protocol) Server that provides an interface to access Pokémon data through the PokéAPI, enabling agents to retrieve information about Pokémon species, abilities, moves, and more via natural language.

Enables LLMs to communicate with Agent-to-Agent (A2A) protocol compliant agents, providing tools for sending messages, managing tasks, and retrieving agent information.

An MCP server that keeps raw tool output out of the context window by sandboxing and compressing results (about 98% reduction), persisting file edits, git operations, tasks and decisions in SQLite with BM25 retrieval so the agent resumes after compaction, and enforcing routing across 17 platforms via MCP and hooks. It also encourages the model to write scripts that compute answers and log only results instead of reading large data into context.

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