How to integrate Agenty MCP with LlamaIndex

This guide walks you through connecting Agenty to LlamaIndex using the Composio tool router. By the end, you'll have a working Agenty agent that can clone your top-performing agent for news sites, list all your running web scraping agents, create a new agent to monitor product prices through natural language commands. This guide will help you understand how to give your LlamaIndex agent real control over a Agenty account through Composio's Agenty MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Agenty logoAgenty
Api Key

Agenty is a web scraping and automation platform for extracting data and automating browser tasks—no coding needed. It streamlines data collection, monitoring, and repetitive online actions.

79 Tools

Introduction

This guide walks you through connecting Agenty to LlamaIndex using the Composio tool router. By the end, you'll have a working Agenty agent that can clone your top-performing agent for news sites, list all your running web scraping agents, create a new agent to monitor product prices through natural language commands.

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

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

Also integrate Agenty 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 Agenty
  • Connect LlamaIndex to the Agenty MCP server
  • Build a Agenty-powered agent using LlamaIndex
  • Interact with Agenty 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 Agenty MCP server, and what's possible with it?

The Agenty MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Agenty account. It provides structured and secure access to your web scraping agents and automation tools, so your agent can perform actions like creating, managing, cloning, and monitoring scraping agents, as well as handling API keys and templates—all on your behalf.

  • Agent creation and configuration: Instantly create new scraping or automation agents, set up their configurations, and optionally auto-start them—all without manual coding.
  • Clone and update agents: Duplicate existing agents to streamline workflows or update agent settings to refine your data extraction processes.
  • Fetch and manage agents: List all active agents in your account, retrieve details for any agent, and organize your entire automation fleet from a single place.
  • Template selection and management: Browse public agent templates or sample agents, making it easy to kickstart new projects or standardize scraping tasks.
  • API key management: Create, download, or delete API keys for secure programmatic access and efficient credential management, keeping your automation environment safe and organized.

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

Step by step10 STEPS
1

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 Agenty account and project
  • Basic familiarity with async Python/Typescript
2

Getting API Keys for OpenAI, Composio, and Agenty

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
3

Installing dependencies

npm install @composio/llamaindex @llamaindex/openai @llamaindex/tools @llamaindex/workflow dotenv

Create a new Typescript project and install the necessary dependencies:

  • @composio/llamaindex: Composio's LlamaIndex integration
  • @llamaindex/openai: OpenAI LLM integration
  • @llamaindex/tools: MCP client for LlamaIndex
  • @llamaindex/workflow: Workflow framework for LlamaIndex
  • dotenv: Environment variable management
4

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 Agenty access
5

Import modules

import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();

Create a new file called agenty_llamaindex_agent.ts and import the required modules:

Key imports:

  • dotenv.config loads .env at runtime
  • readline gives us a simple CLI chat loop
  • Composio is the main Composio SDK client
  • mcp connects to an MCP endpoint
  • createAgent builds a LlamaIndex agent
  • openai configures the LLM backend
6

Load environment variables and initialize Composio

const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!COMPOSIO_API_KEY) throw new Error("COMPOSIO_API_KEY is not set");
if (!COMPOSIO_USER_ID) throw new Error("COMPOSIO_USER_ID is not set");

What's happening:

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

7

Create a Tool Router session and build the agent function

async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["agenty"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
        description : "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Agenty actions." ,
    llm,
    tools,
  });

  return agent;
}

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, agenty)
  • 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 Agenty tools.
  • The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.
8

Create an interactive chat loop

async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}

What's happening:

  • We're creating a direct terminal interface to chat with Agenty
  • The LLM's responses are streamed to the CLI for faster interaction.
  • The agent uses context to maintain conversation history
  • The agent processes the request, selects appropriate Agenty tools, and returns a result
  • We extract the answer from the result data structure and display it to the user
  • You can type 'quit' or 'exit' to stop the chat loop gracefully
  • Agent responses and any errors are streamed in a clear, readable format
9

Define the main entry point

async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err) {
    console.error("Failed to start agent:", err);
    process.exit(1);
  }
}

main();

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 Agenty
10

Run the agent

npx ts-node llamaindex-agent.ts

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

Complete Code

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

import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";
import { LlamaindexProvider } from "@composio/llamaindex";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();

const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) {
    throw new Error("OPENAI_API_KEY is not set in the environment");
  }
if (!COMPOSIO_API_KEY) {
    throw new Error("COMPOSIO_API_KEY is not set in the environment");
  }
if (!COMPOSIO_USER_ID) {
    throw new Error("COMPOSIO_USER_ID is not set in the environment");
  }

async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["agenty"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
    description:
      "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Agenty actions." ,
    llm,
    tools,
  });

  return agent;
}

async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}

async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err: any) {
    console.error("Failed to start agent:", err?.message ?? err);
    process.exit(1);
  }
}

main();

Conclusion

You've successfully connected Agenty to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways:
  • Tool Router dynamically exposes Agenty 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.
TOOLS

Supported Tools

Every Agenty action and event your agent gets out of the box.

Add List Rows

Tool to add new rows to a list.

Create Agent

Creates a new Agenty agent for web scraping, change detection, crawling, map monitoring, or brand monitoring.

Get Agent Templates

Tool to fetch all public agent templates and sample agents.

Delete Agent by ID

Tool to delete a single agent by its ID.

Fetch all agents

Tool to fetch all active agents under an account.

Get Agent by ID

Retrieves complete details of a specific agent including its configuration, input settings, scheduler, and metadata.

Update Agent by ID

Updates an existing agent's configuration, settings, and metadata.

Create API Key

Creates a new API key for programmatic access to the Agenty API.

Delete API key by ID

Delete an API key by its unique identifier.

Download API keys

Tool to download all API keys under an account in CSV format.

Get all API keys

Tool to retrieve all API keys under an account.

Get API key by ID

Retrieves detailed information about a specific API key by its ID.

Reset API key by ID

Resets (regenerates) the secret value of an existing API key.

Update API key by ID

Updates an existing API key's name and role by its unique identifier.

Capture Screenshot

Tool to capture a full-page or visible screenshot of any webpage URL.

Capture Screenshot with Options

Tool to capture webpage screenshots with extensive customization options including full-page capture, image format, quality settings, viewport configuration, and post-processing.

Change API key status by ID

Toggles the enabled/disabled status of an API key.

Get all connections

Retrieves all connections from your Agenty account.

Convert URL to PDF

Tool to convert a webpage URL to a PDF document.

Convert URL to PDF with Options

Tool to convert a URL or raw HTML to PDF with customizable options.

Copy Agent

Tool to copy an existing agent by its ID, creating a duplicate with optionally a new name.

Create Workflow

Creates a new workflow in Agenty to automate actions based on agent events.

Get dashboard reports and usage

Tool to fetch account reports like pages used by agent, date, and product.

Delete List Row by ID

Tool to delete a specific row from a list by its unique identifier.

Delete List Rows by IDs

Tool to delete specific rows from a list by their IDs.

Delete Project

Tool to delete a project by its ID.

Delete Schedule

Tool to delete a schedule for an agent by its agent ID.

Delete Workflow by ID

Tool to delete a workflow by its ID.

Download Agent Result

Tool to download agent results by agent ID in CSV, TSV or JSON format.

Download List Rows

Tool to download list rows as CSV file.

Download users

Tool to download users list in CSV format.

Download workflows

Tool to download all workflows in CSV format.

Extract Structured Data

Tool to auto-extract structured data from a webpage including schema.

Extract Structured Data from URL

Tool to auto-extract structured data from a webpage URL.

Get Agent Result

Tool to get the most recent result data for an agent.

Get all team members

Tool to retrieve all team members (users) under an account.

Get URL Redirects

Tool to get the complete redirect chain for a URL.

Get Job Result

Tool to get the result data from a completed job.

Get list by ID

Retrieves detailed information about a specific list by its ID.

Get List Row by ID

Tool to fetch a specific row by its ID from a list.

Get Page Content

Tool to fetch the complete HTML content of any webpage URL.

Get Page Content with Options

Tool to fetch HTML content of a webpage with custom options including ad blocking.

Get Project by ID

Retrieves complete details of a specific project by its ID, including name, description, creator information, and timestamps.

Get Redirects with Options

Tool to get the complete redirect chain of a URL with custom navigation options.

Get Agent Schedule

Tool to retrieve the schedule configuration for a specific agent.

Get User by ID

Tool to retrieve detailed information about a user by their ID.

Get Workflow by ID

Retrieves complete details of a specific workflow by its ID.

Get agent input by ID

Retrieves the input configuration for a specific agent by its ID.

Update Input by Agent ID

Updates the input configuration for a specific agent in Agenty.

Download jobs

Tool to download all jobs in CSV format.

Download job file by ID

Tool to download output files by job ID.

Download Job Result by ID

Tool to download the agent output result by job ID.

Fetch all jobs

Tool to fetch all jobs under an account.

Get Job by ID

Retrieves comprehensive details about a specific job including its status, progress metrics (pages processed/succeeded/failed), timing information (created/started/completed times), resource consumption (page credits), and any error messages.

Get Job Logs by ID

Tool to fetch logs for a given job by its ID.

List job output files

Lists all output files generated by a specific job.

Start Agent Job

Tool to start a new agent job.

Stop Job by ID

Tool to stop a running job by job ID.

Clear List Rows

Tool to clear all rows in a list by its ID.

Create List

Tool to create a new list.

Delete List by ID

Tool to delete a specific list by its ID.

Download lists

Tool to download all lists in CSV format.

Get all lists

Tool to retrieve all lists under an account.

Fetch List Rows by ID

Tool to fetch all rows in a specified list.

Update List by ID

Tool to update a list's name and optionally description by list ID.

Upload CSV file to List

Tool to upload a CSV file to an Agenty list for bulk import of data rows.

Patch Workflow

Tool to partially update a workflow by ID.

Add Agents to Project

Add one or more agents to an Agenty project to organize and group related agents together.

Create Project

Creates a new project in Agenty.

Get all projects

Retrieve all projects in the authenticated user's account.

Remove Agent from Project

Remove an agent from an Agenty project.

Scrape Webpage Data

Tool to scrape data from any webpage using jQuery/CSS selectors.

Toggle Agent Schedule

Tool to toggle schedule on/off for an agent.

Transfer Agent Ownership

Tool to transfer agent ownership to another Agenty account.

Update List Row

Tool to update a specific row in a list by list ID and row ID.

Update Project

Update an existing project's name and description in Agenty.

Update Agent Schedule

Updates the schedule configuration for a specific agent.

Update User by ID

Tool to update a user's information by user ID.

Update Workflow

Tool to update an existing workflow's configuration by workflow ID.

FAQ

Frequently asked questions

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

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 Agenty tools.

Yes, absolutely. You can configure which Agenty 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.

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 Agenty data and credentials are handled as safely as possible.

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