How to integrate Kadoa MCP with LlamaIndex

This guide walks you through connecting Kadoa to LlamaIndex using the Composio tool router. By the end, you'll have a working Kadoa agent that can fetch the latest data from your workflow, check crawl status for session abc123, list all pages crawled in last run through natural language commands. This guide will help you understand how to give your LlamaIndex agent real control over a Kadoa account through Composio's Kadoa MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Kadoa is an API-first platform for building and managing workflows that extract data from unstructured sources. It helps automate and monitor extraction tasks at scale.

77 Tools

Introduction

This guide walks you through connecting Kadoa to LlamaIndex using the Composio tool router. By the end, you'll have a working Kadoa agent that can fetch the latest data from your workflow, check crawl status for session abc123, list all pages crawled in last run through natural language commands.

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

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

Also integrate Kadoa with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AICrewAI

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

The Kadoa MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Kadoa account. It provides structured and secure access to your data extraction workflows, so your agent can launch crawls, monitor sessions, retrieve extracted data, and manage workflow configurations automatically on your behalf.

  • Automated workflow monitoring and management: Ask your agent to fetch workflow configurations, enable data validation, or get the latest results from any extraction workflow you have set up.
  • Crawling session control: Have your agent check the status of crawl sessions, list all crawled pages, and pull the raw content (HTML or Markdown) from any page processed by a workflow.
  • Notification channel setup and retrieval: Direct your agent to create notification channels, list available notification event types, and fetch specific channel configurations for streamlined alerting.
  • Location and environment awareness: Let your agent retrieve all supported locations to ensure workflows run in the right environment before launching new extraction jobs.
  • Seamless data access: Instruct your agent to quickly get the most recent data output from any workflow, keeping your automations and dashboards always up to date.

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

Getting API Keys for OpenAI, Composio, and Kadoa

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 Kadoa 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 kadoa_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: ["kadoa"],
    },
  );

  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 Kadoa 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, kadoa)
  • 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 Kadoa 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 Kadoa
  • 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 Kadoa 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 Kadoa
10

Run the agent

npx ts-node llamaindex-agent.ts

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

Complete Code

Here's the complete code to get you started with Kadoa 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: ["kadoa"],
    },
  );

  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 Kadoa 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 Kadoa to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways:
  • Tool Router dynamically exposes Kadoa 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 Kadoa action and event your agent gets out of the box.

Bulk Approve Validation Rules

Tool to bulk approve preview validation rules for a workflow.

Create Crawl Config

Tool to create a new crawling configuration in Kadoa.

Create Notification Channel

Tool to create a notification channel for alerts delivery.

Create Schema

Create a new data schema with specified fields and entity type.

Create Support Issue

Tool to create a support ticket in Kadoa.

Create Workflow Trigger

Tool to create a trigger that fires when a source workflow emits an event.

Delete All Validation Rules

Tool to soft-delete all validation rules for a specific workflow with optional audit trail.

Delete Crawl Configuration

Tool to delete a crawling configuration by its config ID.

Delete Notification Channel

Tool to delete a notification channel by its ID.

Delete Schema

Tool to delete a schema and all its revisions.

Delete Validation Rule

Tool to delete a validation rule from a Kadoa workflow.

Delete Validation Rules (Bulk)

Tool to bulk delete multiple validation rules for a workflow.

Delete Workflow

Delete a workflow permanently from your Kadoa account.

Delete Workflow Trigger

Tool to delete a trigger from a Kadoa workflow.

Disable Validation Rule

Tool to disable a validation rule with a mandatory reason.

Enable Data Validation

Tool to enable data validation on a specified workflow.

Execute Bulk Workflow Operations

Execute actions on multiple workflows at once.

Export Activity Events

Tool to export activity events from audit logs to CSV format for compliance and audit purposes.

Export Activity Workflows

Tool to export workflow configurations and metadata as CSV for portfolio reviews and compliance reporting.

Get Workflow by ID

Retrieve detailed configuration of a workflow by its ID.

Get all locations

Retrieves all available scraping proxy locations (countries) supported by Kadoa.

Get Crawl Bucket Data

Tool to retrieve file content from the Kadoa crawling bucket (HTML or screenshot).

Get Crawl Configuration

Tool to retrieve a crawling configuration by its ID.

Get Crawled Page Content

Tool to retrieve content of a crawled page.

Get Crawled Pages

Tool to list pages crawled during a session.

Get Crawl Status

Tool to fetch current status of a crawling session.

Get Event Type Details

Tool to retrieve details for a specific notification event type.

Get Notification Event Types

Tool to retrieve supported notification event types.

Get Latest Workflow Data

Retrieves the extracted data from a Kadoa workflow's most recent run (or a specific run if runId is provided).

Get Latest Workflow Validation

Retrieves the latest validation results for the most recent job of a workflow.

Get Notification Channel

Tool to retrieve details of a specific notification channel.

Get Notification Logs

Tool to retrieve notification event logs with optional filtering by workflow, event type, and date range.

Get Notification Setting

Retrieves a specific notification setting by its unique identifier.

Get Schema by ID

Retrieve a specific schema by its unique identifier.

Get Validation Anomalies

Tool to retrieve all anomalies for a specific validation.

Get Validation Anomalies By Rule

Tool to retrieve anomalies for a specific validation rule.

Get Validation Configuration

Tool to retrieve the data validation configuration for a specific workflow.

Get Validation Rule

Tool to retrieve a specific validation rule by its ID.

Get Workflow Audit Log

Retrieve audit log entries for a workflow.

Get Workflow Job

Tool to retrieve the current status and telemetry information for a specific workflow job.

Get Workflow Run History

Tool to fetch workflow run history.

Get Workflows

Retrieve a paginated list of workflows with optional filtering.

Get Workflow Trigger

Tool to retrieve a specific trigger for a workflow.

Get Workflow Validation Results

Retrieves the latest validation results for a specific workflow job.

Get Workspace Details

Tool to retrieve detailed information about a workspace (user, team, or organization).

List Activity Events

Tool to retrieve activity events from audit logs with basic filtering and pagination.

List Changes

Tool to retrieve all data changes detected across workflows in your Kadoa account.

List Crawl Sessions

Tool to retrieve a paginated list of crawling sessions with optional filtering.

List Job Validations

Tool to list all validation runs for a specific job with pagination support.

List Notification Channels

Tool to retrieve all notification channels configured for the account.

List Notification Settings

Tool to retrieve all notification settings, with optional filtering by workflow ID or event type.

List Schemas

Tool to retrieve all schemas accessible by the authenticated user.

List Support States

Tool to retrieve available support issue states.

List Validation Rules

Tool to list all data validation rules with optional pagination and filtering.

List Workflow Triggers

Tool to get all triggers where the specified workflow is the source.

Pause Crawl Session

Tool to pause an active crawling session.

Pause Workflow

Tool to pause a running or scheduled workflow.

Create Advanced Workflow

Tool to create an advanced workflow.

Start Crawl Session

Starts a new web crawling session to crawl and index pages from a website.

Create Notification Setting

Tool to create a notification setting linking channels to events.

Send Test Notification

Sends a test notification event to verify notification channel configurations are working correctly.

Subscribe to Webhook Events

Tool to subscribe to specified webhook events.

Create Workflow

Create a new Kadoa web scraping workflow.

Configure Workflow Monitoring

Configure monitoring and scheduling for a Kadoa workflow to detect data changes.

Generate Workflow Validation Rule

Generate an AI-powered data validation rule for a Kadoa workflow.

Update Notification Channel

Tool to update an existing notification channel.

Resume Crawl Session

Tool to resume a paused crawling session.

Resume Workflow

Resumes a paused, preview, or error workflow.

Run Ad-hoc Extraction

Tool to synchronously extract data from a URL using a given template.

Run Workflow

Tool to trigger a workflow to run immediately.

Schedule Validation Job

Tool to schedule a data validation job for a specific workflow job.

Unsubscribe from Webhook Events

Unsubscribe from webhook event notifications by deleting a notification setting.

Update Notification Settings

Tool to update existing notification settings for events.

Update Schema

Tool to update an existing Kadoa schema.

Update Validation Configuration

Tool to update the complete data validation configuration including alerting settings for a specific workflow.

Update Workflow Metadata

Tool to update workflow metadata such as name, description, tags, and configuration settings.

Update Workflow Trigger

Tool to update trigger properties including event type and enabled status.

FRAMEWORKS

How to build Kadoa MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Kadoa MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Kadoa MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Kadoa MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Kadoa MCP with Claude Cowork

Codex logo

Codex

Use Kadoa MCP with Codex

OpenClaw logo

OpenClaw

Use Kadoa MCP with OpenClaw

Hermes logo

Hermes

Use Kadoa MCP with Hermes

CLI logo

CLI

Use Kadoa MCP with CLI

Google ADK logo

Google ADK

Use Kadoa MCP with Google ADK

LangChain logo

LangChain

Use Kadoa MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Kadoa MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Kadoa MCP with Mastra AI

CrewAI logo

CrewAI

Use Kadoa MCP with CrewAI

FAQ

Frequently asked questions

With a standalone Kadoa MCP server, the agents and LLMs can only access a fixed set of Kadoa tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Kadoa 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 Kadoa tools.

Yes, absolutely. You can configure which Kadoa 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 Kadoa data and credentials are handled as safely as possible.

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