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Parallel Browser MCP Server

@etairl

Repository

Basic information

Category

Browser Automation

Transports

stdio

Author

etairl

Submitted by

Itay

About Parallel Browser MCP Server

MCP server for parallel browser automation across multiple providers. Run multiple concurrent browser sessions in memory with a shared, provider-agnostic tool surface across Playwright (local Chromium), Browserbase, Anchor Browser, and Cloudflare Browser Run. Each session gets a

#browser#automation#playwright#browserbase#anchor#cloudflare#parallel#puppeteer#scraping#web

Parallel Browser MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "parallel-browser-mcp": {
      "command": "npx",
      "args": [
        "parallel-browser-mcp@latest"
      ]
    }
  }
}

Parallel Browser MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

Fetch the live tool list by running this server in a temporary sandbox using the button above.

Overview

What is Parallel Browser Mcp?

Parallel Browser Mcp is an MCP server for parallel browser automation. It exposes a numeric session model so one client can create and control multiple browser sessions simultaneously across several providers: local Playwright Chromium, Browserbase, Anchor Browser, and Cloudflare Browser Run. It is designed for developers building AI-driven browser automation workflows within MCP‑compatible clients.

How to use Parallel Browser Mcp?

Install via npm (npx parallel-browser-mcp@latest) and add the server configuration to your MCP client (e.g., Claude, Cursor, VS Code). The server runs over stdio. Create sessions by calling start_session with a provider, then use any browser_* tool by passing the returned numeric sessionId. Provider credentials and defaults are set in environment variables or a JSON config object.

Key features of Parallel Browser Mcp

  • Multiple concurrent browser sessions with numeric IDs in memory
  • Unified provider abstraction for Playwright, Browserbase, Anchor, and Cloudflare
  • Session management tools: start, close, close all, list sessions
  • Over 20 browser automation tools (navigate, click, fill, screenshot, and more)
  • Configuration via environment variables, config file, or inline JSON

Use cases of Parallel Browser Mcp

  • Run multiple browser-based agents in parallel from a single MCP client
  • Automate web scraping and form filling across different browser providers
  • AI agents that need to manipulate several pages concurrently (e.g., research, data extraction)
  • Test browser automation scripts locally with Playwright and switch to cloud providers

Frequently asked questions

1

Which providers does Parallel Browser Mcp support?

It supports four providers: Playwright (local Chromium), Browserbase (via `@browserbasehq/sdk`), Anchor (via `anchorbrowser`), and Cloudflare (via Cloudflare Browser Run).

2

How do I configure provider credentials?

Credentials are set via environment variables: `BROWSERBASE_API_KEY`, `ANCHOR_API_KEY`, `CLOUDFLARE_API_TOKEN`, and `CLOUDFLARE_ACCOUNT_ID`. Playwright requires no credentials. Additional provider‑specific options can be set in a JSON configuration provided through `BROWSER_MCP_CONFIG` or a config file.

3

How do I run the server?

You can run it locally with `node dist/index.js` after building, or use the npm CLI: `npx parallel-browser-mcp@latest`. The server communicates over stdio, so it integrates with any MCP client that supports stdio transport.

4

What tools are available for controlling a session?

The server offers session tools (`start_session`, `close_session`, `close_all_sessions`, `get_sessions`) and browser tools such as `browser_navigate`, `browser_click`, `browser_fill`, `browser_screenshot`, `browser_snapshot`, `browser_evaluate`, and more—over 20 in total.

5

How do I start and use a session?

Call `start_session` with a provider name (e.g., `"playwright"`). The response includes a numeric session ID. Then call any `browser_*` tool with `{ "sessionId": <id>, ...}`. Finally, call `close_session` to release resources.

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