How to integrate Anchor browser MCP with LlamaIndex

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Introduction

This guide walks you through connecting Anchor browser to LlamaIndex using the Composio tool router. By the end, you'll have a working Anchor browser agent that can fetch full content of a product page, list all active browser sessions now, get details for a specific browser profile through natural language commands.

This guide will help you understand how to give your LlamaIndex agent real control over a Anchor browser account through Composio's Anchor browser MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Anchor browser with

TL;DR

Here's what you'll learn:
  • Set your OpenAI and Composio API keys
  • Install LlamaIndex and Composio packages
  • Create a Composio Tool Router session for Anchor browser
  • Connect LlamaIndex to the Anchor browser MCP server
  • Build a Anchor browser-powered agent using LlamaIndex
  • Interact with Anchor browser through natural language

What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.

Key features include:

  • ReAct Agent: Reasoning and acting pattern for tool-using agents
  • MCP Tools: Native support for Model Context Protocol
  • Context Management: Maintain conversation context across interactions
  • Async Support: Built for async/await patterns

What is the Anchor browser MCP server, and what's possible with it?

The Anchor browser MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Anchor browser account. It provides structured and secure access to powerful web automation features, so your agent can fetch web content, manage browser sessions, control profiles, and interact with extensions on your behalf.

  • Automated webpage content retrieval: Instruct your agent to browse to any URL and fetch the fully rendered page content in HTML or markdown, enabling easy scraping or summarization.
  • Session and profile management: Let your agent create, list, or delete browser profiles, as well as start, end, or monitor multiple browsing sessions for different workflows or user contexts.
  • Browser extension control: Have the agent list all installed browser extensions, making it easy to audit and manage your browser environment programmatically.
  • Resource and file listing: Ask your agent to retrieve a list of files or resources uploaded during browser automation tasks, ensuring nothing gets lost in the shuffle.
  • Comprehensive session oversight: Quickly get an overview of all active browser sessions, their statuses, and terminate any or all sessions instantly for security or resource management needs.

Supported Tools & Triggers

Tools
Click MouseTool to perform a mouse click at specified coordinates within a browser session.
Copy Selected TextTool to copy currently selected text in a browser session to the clipboard.
Create IntegrationTool to create a new integration with a third-party service like 1Password.
Create or Update Task DraftTool to create or update the draft version of a task.
Create ProfileCreates a new browser profile from an active session.
Create TaskTool to create a new task or update an existing task with the same name.
Delete ExtensionTool to delete a browser extension and remove it from storage.
Delete IntegrationTool to delete an existing integration and remove its stored credentials.
Delete ProfileTool to delete a browser profile by ID.
Delete TaskTool to soft delete a task and all its versions.
Delete Task VersionTool to soft delete a specific version of a task.
Deploy TaskTool to deploy a task by creating a new version with auto-incremented version number.
Double Click MouseTool to perform a double click at specified coordinates in a browser session.
Drag and DropTool to perform a drag and drop operation from start coordinates to end coordinates within a browser session.
End All SessionsTool to terminate all active browser sessions at once.
End Browser SessionTool to end a specific browser session by ID.
Get Batch Session StatusTool to retrieve detailed status information for a specific batch including progress and errors.
Get Browser SessionTool to retrieve detailed information about a specific browser session.
Get Clipboard ContentTool to retrieve the current content of the clipboard from a browser session.
Get Latest Task VersionTool to retrieve the latest version of a task including the full base64 encoded code content.
Get Profile (v2)Tool to retrieve details of a specific profile by its name.
Get Session PagesTool to retrieve all pages associated with a specific browser session.
Get Task DraftTool to retrieve the draft version of a task, including the full Base64 encoded code content.
Get Task Execution ResultTool to retrieve a single task execution result by its ID.
Get Task MetadataTool to retrieve task metadata without downloading the full task code.
Get Task VersionTool to retrieve a specific version of a task, including the full code content.
Get Webpage ContentTool to retrieve rendered content of a webpage in HTML or Markdown format.
List Agent ResourcesList all agent resources (files) uploaded to a browser session.
List ExtensionsRetrieves all browser extensions uploaded by the authenticated user.
List IntegrationsTool to retrieve all integrations for the authenticated team.
List ProfilesTool to fetch all stored browser profiles.
List Session DownloadsTool to retrieve metadata of files downloaded during a browser session.
List Session RecordingsTool to list all recordings for a specific browser session.
List SessionsTool to list all browser sessions.
List Task ExecutionsTool to retrieve execution history for a specific task with filtering and pagination support.
List TasksTool to retrieve a paginated list of all tasks for the authenticated team.
List Task VersionsTool to retrieve all versions of a specific task, including draft and published versions.
Mouse MoveTool to move the mouse cursor to specified coordinates within a browser session.
Navigate to URLTool to navigate a browser session to a specified URL.
Paste TextTool to paste text at the current cursor position in a browser session.
Pause AgentTool to pause the AI agent for a specific browser session.
Pause Session RecordingTool to pause the video recording for a specific browser session.
Perform Keyboard ShortcutTool to perform a keyboard shortcut using specified keys in a browser session.
Perform Web TaskTool to perform autonomous web tasks using AI agents.
Mouse DownTool to perform a mouse button down action at specified coordinates within a browser session.
Publish Task VersionTool to publish a specific version of a task.
Release Mouse ButtonTool to release a mouse button at specified coordinates within a browser session.
Resume AgentTool to resume the AI agent for a specific browser session.
Resume Session RecordingTool to resume video recording for a specific browser session.
Run TaskTool to execute a task in a browser session with a specific or latest version.
Run Task by NameTool to execute a task by its name, always using the latest version.
Screenshot WebpageTool to take a screenshot of a specified webpage within a session.
Scroll SessionTool to perform a scroll action at specified coordinates within a browser session.
Set Clipboard ContentTool to set the content of the clipboard in a browser session.
Signal EventTool to signal a specific event to be received by other processes or sessions.
Start Browser SessionTool to start a new browser session with optional customizations.
Take ScreenshotTool to take a screenshot of the current browser session and return it as an image.
Type TextTool to type specified text with optional delay between keystrokes.
Update ProfileUpdates an existing browser profile with data from an active session.
Update Task MetadataUpdates task metadata (name and description).
Upload ExtensionTool to upload a new browser extension as a ZIP file for use in browser sessions.
Upload FileTool to upload a file to a browser session as an agent resource.
Upload Files to SessionTool to upload files directly to a browser session for use with web forms and file inputs.
Wait for EventBlocks execution until a specific named event is signaled or the timeout expires.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before you begin, make sure you have:
  • Python 3.8/Node 16 or higher installed
  • A Composio account with the API key
  • An OpenAI API key
  • A Anchor browser account and project
  • Basic familiarity with async Python/Typescript

Getting API Keys for OpenAI, Composio, and Anchor browser

OpenAI API key (OPENAI_API_KEY)
  • Go to the OpenAI dashboard
  • Create an API key if you don't have one
  • Assign it to OPENAI_API_KEY in .env
Composio API key and user ID
  • Log into the Composio dashboard
  • Copy your API key from Settings
    • Use this as COMPOSIO_API_KEY
  • Pick a stable user identifier (email or ID)
    • Use this as COMPOSIO_USER_ID

Installing dependencies

pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv

Create a new Python project and install the necessary dependencies:

  • composio-llamaindex: Composio's LlamaIndex integration
  • llama-index: Core LlamaIndex framework
  • llama-index-llms-openai: OpenAI LLM integration
  • llama-index-tools-mcp: MCP client for LlamaIndex
  • python-dotenv: Environment variable management

Set environment variables

bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id

Create a .env file in your project root:

These credentials will be used to:

  • Authenticate with OpenAI's GPT-5 model
  • Connect to Composio's Tool Router
  • Identify your Composio user session for Anchor browser access

Import modules

import asyncio
import os
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

Create a new file called anchor browser_llamaindex_agent.py and import the required modules:

Key imports:

  • asyncio: For async/await support
  • Composio: Main client for Composio services
  • LlamaIndexProvider: Adapts Composio tools for LlamaIndex
  • ReActAgent: LlamaIndex's reasoning and action agent
  • BasicMCPClient: Connects to MCP endpoints
  • McpToolSpec: Converts MCP tools to LlamaIndex format

Load environment variables and initialize Composio

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set in the environment")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment")

What's happening:

This ensures missing credentials cause early, clear errors before the agent attempts to initialise.

Create a Tool Router session and build the agent function

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["anchor_browser"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")

    description = "An agent that uses Composio Tool Router MCP tools to perform Anchor browser actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Anchor browser actions.
    """
    return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True)

What's happening here:

  • We create a Composio client using your API key and configure it with the LlamaIndex provider
  • We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, anchor browser)
  • The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
  • LlamaIndex will connect to this endpoint to dynamically discover and use the available Anchor browser tools.
  • The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.

Create an interactive chat loop

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

What's happening here:

  • We're creating a direct terminal interface to chat with your Anchor browser database
  • The LLM's responses are streamed to the CLI for faster interaction.
  • The agent uses context to maintain conversation history
  • You can type 'quit' or 'exit' to stop the chat loop gracefully
  • Agent responses and any errors are displayed in a clear, readable format

Define the main entry point

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")

What's happening here:

  • We're orchestrating the entire application flow
  • The agent gets built with proper error handling
  • Then we kick off the interactive chat loop so you can start talking to Anchor browser

Run the agent

npx ts-node llamaindex-agent.ts

When prompted, authenticate and authorise your agent with Anchor browser, then start asking questions.

Complete Code

Here's the complete code to get you started with Anchor browser and LlamaIndex:

import asyncio
import os
import signal
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["anchor_browser"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")
    description = "An agent that uses Composio Tool Router MCP tools to perform Anchor browser actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Anchor browser actions.
    """
    return ReActAgent(
        tools=tools,
        llm=llm,
        description=description,
        system_prompt=system_prompt,
        verbose=True,
    );

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")

Conclusion

You've successfully connected Anchor browser to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways:
  • Tool Router dynamically exposes Anchor browser tools through an MCP endpoint
  • LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
  • The agent becomes more capable without increasing prompt size
  • Async Python provides clean, efficient execution of agent workflows
You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.

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FAQ

What are the differences in Tool Router MCP and Anchor browser MCP?

With a standalone Anchor browser MCP server, the agents and LLMs can only access a fixed set of Anchor browser tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Anchor browser and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with LlamaIndex?

Yes, you can. LlamaIndex fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Anchor browser tools.

Can I manage the permissions and scopes for Anchor browser while using Tool Router?

Yes, absolutely. You can configure which Anchor browser scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Anchor browser data and credentials are handled as safely as possible.

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