How to integrate Apollo MCP with LlamaIndex

This guide walks you through connecting Apollo to LlamaIndex using the Composio tool router. By the end, you'll have a working Apollo agent that can bulk enrich profiles for new leads, add contacts to outreach sequence now, create a new sales deal for acme through natural language commands. This guide will help you understand how to give your LlamaIndex agent real control over a Apollo account through Composio's Apollo MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Apollo is a CRM and lead generation platform that helps businesses discover contacts and manage sales pipelines. Use it to streamline customer outreach and track your deals from one place.

48 Tools

Introduction

This guide walks you through connecting Apollo to LlamaIndex using the Composio tool router. By the end, you'll have a working Apollo agent that can bulk enrich profiles for new leads, add contacts to outreach sequence now, create a new sales deal for acme through natural language commands.

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

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

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

The Apollo MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Apollo account. It provides structured and secure access to your CRM and lead generation data, so your agent can create contacts, enrich organizations, manage deals, update account stages, and automate tasks for your sales pipeline—all on your behalf.

  • Contact and account creation: Instantly add new contacts or accounts to Apollo, linking them to organizations and stages to keep your CRM up to date with zero manual entry.
  • Bulk data enrichment: Rapidly enrich multiple people or organizations at once, leveraging Apollo's database to fill gaps and update your records with the latest information.
  • Sales opportunity and pipeline management: Let your agent create new deals, retrieve opportunity stages, and move accounts through your sales funnel to optimize pipeline performance.
  • Automated outreach sequencing: Add contacts to email sequences, making it easy to launch targeted campaigns and follow-ups without lifting a finger.
  • Task creation and label organization: Generate actionable Apollo tasks for your team and organize contacts or accounts with labels, so nothing slips through the cracks.

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

Getting API Keys for OpenAI, Composio, and Apollo

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 Apollo 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 apollo_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: ["apollo"],
    },
  );

  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 Apollo 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, apollo)
  • 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 Apollo 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 Apollo
  • 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 Apollo 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 Apollo
10

Run the agent

npx ts-node llamaindex-agent.ts

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

Complete Code

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

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

Add Contacts to Sequence

Adds contacts to a specified Apollo email sequence and returns the contact details.

Bulk organization enrichment

Enriches data for up to 10 organizations simultaneously by providing a list of their base company domains (e.

Bulk people enrichment

Use to enrich multiple person profiles simultaneously with comprehensive data from Apollo's database.

Bulk update account stage

Bulk updates the stage for specified existing Apollo.

Create an Apollo account

Creates a new account in Apollo.

Bulk create Apollo accounts

Creates multiple accounts in Apollo.

Bulk create Apollo contacts

Tool to bulk create multiple contacts in Apollo with a single API call.

Create call record in Apollo

Tool to log call records in Apollo from external systems.

Create Apollo contact

Creates a new contact in Apollo.

Create custom field

Creates a new custom field in Apollo.

Create Apollo deal

Creates a new sales opportunity (deal) in Apollo.

Create Apollo Task

Tool to create a single task in Apollo.

Get Account by ID

Tool to retrieve detailed information about a specific account by its Apollo ID.

Check Apollo API key status

Tool to check whether the provided Apollo API key is valid and accepted by Apollo (health/auth check).

Get Apollo Contact

Retrieves detailed information about a specific contact by its ID.

Get Apollo deal

Retrieves information about a specific deal by its ID.

Get Labels

Retrieves all labels from Apollo.

Get opportunity stages

Retrieves all configured opportunity (deal) stages from the Apollo.

Get Organization by ID

Retrieves complete information about a specific organization by its Apollo ID.

Get Organization Job Postings

Retrieves paginated job postings for a specified organization by its ID, optionally filtering by domain; ensure `organization_id` is a valid identifier.

Get typed custom fields

Retrieves all typed custom field definitions available in the Apollo.

List Apollo account stages

Retrieves the IDs for all available account stages in your team's Apollo account.

List apollo contact stages

Retrieves all available contact stages from an Apollo account, including their unique IDs and names.

List Apollo deals

Retrieves a list of deals from Apollo, using Apollo's default sort order if 'sort_by_field' is omitted.

List email accounts

Retrieves all email accounts and their details for the authenticated user; takes no parameters.

List Fields

Retrieves all field definitions from Apollo.

List Apollo Users

Retrieves a list of all users (teammates) associated with the Apollo account, supporting pagination via `page` and `per_page` parameters.

Enrich organization data

Fetches comprehensive organization enrichment data from Apollo.

Search organizations in Apollo

Searches Apollo's database for organizations using various filters; consumes credits on every call (unavailable on free plans) — avoid re-running identical queries and surface quota errors rather than retrying.

Enrich person with Apollo

Enriches and retrieves information for a person from Apollo.

Apollo people search

Searches Apollo's contact database for people using various filters; results capped at 50,000 records and does not enrich contact data.

Search Apollo Accounts

Searches for accounts within your existing Apollo.

Search for Calls

Searches for call records in Apollo.

Search Apollo contacts

Searches Apollo contacts using keywords, stage IDs (from 'List Contact Stages' action), or sorting (max 50,000 records; `sort_ascending` requires `sort_by_field`).

Search news articles

Tool to search for news articles about companies in Apollo's database.

Search outreach emails

Tool to search for outreach emails sent through Apollo sequences.

Search sequences

Searches for sequences (e.

Search tasks

Searches for tasks in Apollo.

Update an Apollo account

Updates specified attributes of an existing account in Apollo.

Update account ownership

Updates the ownership of multiple Apollo accounts to a specified user.

Update Apollo call record

Tool to update an existing call record in Apollo.

Update Apollo contact details

Tool to update an existing contact's information in Apollo.

Update contact ownership

Updates the ownership of specified Apollo contacts to a given Apollo user, who must be part of the same team.

Bulk update Apollo contacts

Tool to bulk update multiple Apollo contacts with a single API call.

Update contact stage

Updates the stage for one or more existing contacts in Apollo.

Update contact status in sequence

Updates a contact's status within a designated Apollo sequence, but cannot set the status to 'active'.

Update Apollo deal

Updates specified fields of an existing Apollo.

View API Usage Stats

Fetches Apollo API usage statistics and rate limits for the connected team.

FAQ

Frequently asked questions

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

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

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