How to integrate Instantly MCP with LlamaIndex

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Introduction

This guide walks you through connecting Instantly to LlamaIndex using the Composio tool router. By the end, you'll have a working Instantly agent that can create a new cold email campaign, add a new lead to my campaign, check unread emails in my inbox, run an inbox placement test for gmail through natural language commands.

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

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

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

The Instantly MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Instantly account. It provides structured and secure access to your campaigns, leads, and outreach tools, so your agent can perform actions like launching new campaigns, managing leads, tracking inbox statistics, and handling API credentials on your behalf.

  • Automated campaign creation and management: Ask your agent to launch new cold email campaigns or update existing ones, streamlining your outreach workflow without manual setup.
  • Lead and lead list management: Let your agent add new leads, organize them into lists, or enrich them with AI-driven insights to maximize your campaign effectiveness.
  • Email verification and deliverability tracking: Direct your agent to check the verification status of email addresses or run inbox placement tests to monitor and improve deliverability across providers.
  • Inbox activity monitoring: Fetch unread email counts or campaign engagement metrics, helping you stay on top of your outreach performance in real time.
  • API key and webhook automation: Have your agent create or delete API keys for secure integrations, or set up webhooks to receive instant notifications about important Instantly events.

Supported Tools & Triggers

Tools
Check Email Verification StatusTool to check status of an email verification job.
Count Unread EmailsTool to retrieve the count of unread emails.
Create AI EnrichmentTool to create an AI enrichment job for a campaign or lead list.
Create API KeyTool to create a new API key.
Create CampaignTool to create a new campaign.
Create Inbox Placement TestTool to create an inbox placement test.
Create LeadTool to create a new lead.
Create Lead ListTool to create a new lead list.
Create WebhookTool to create a new webhook endpoint.
Delete API KeyTool to delete an API key.
Delete CampaignTool to delete a campaign.
Delete LeadTool to delete a lead by its ID.
Delete Lead ListTool to delete a lead list by ID.
Delete WebhookTool to delete a webhook.
Disable Account WarmupTool to disable the warm-up process for email accounts.
Enable Account WarmupTool to enable the warm-up process for email accounts.
Get CampaignTool to retrieve campaign details.
Get Campaign AnalyticsTool to retrieve analytics for campaigns.
Get Daily Campaign AnalyticsTool to retrieve daily analytics for a campaign.
Get Email Service Provider OptionsTool to retrieve email service provider options for inbox placement tests.
Get Inbox Placement TestTool to retrieve inbox placement test results.
Get LeadTool to retrieve details of a specific lead by its ID.
Get Lead ListTool to retrieve details of a specific lead list by its ID.
Get Lead List Verification StatsTool to retrieve verification statistics for a lead list.
Get WebhookTool to retrieve details of a specific webhook subscription.
Get Webhook EventTool to retrieve details of a specific webhook event.
List Email AccountsTool to list all email accounts for the authenticated user.
List API KeysTool to list all API keys.
List CampaignsTool to list all campaigns.
List Custom TagsTool to list custom tags.
List DFY Email Account OrdersTool to list DFY email account orders.
List EmailsTool to list emails.
List Inbox Placement Blacklist & SpamAssassin ReportsTool to list inbox placement blacklist & SpamAssassin reports.
List Inbox Placement TestsTool to list inbox placement tests.
List Lead ListsTool to list all lead lists.
List LeadsTool to list leads.
List Email ThreadsTool to list email threads.
List Webhook EventsTool to list webhook events.
List WebhooksTool to list configured webhooks.
Mark Thread As ReadTool to mark all emails in a specific thread as read.
Merge LeadsTool to merge multiple leads into a single lead.
Search Campaigns by Lead EmailTool to search campaigns by a lead's email address.
Update CampaignTool to update details of a campaign.
Update LeadTool to update a lead's details.
Update Lead Interest StatusTool to update a lead's interest status.
Update Lead ListTool to update details of a specific lead list by its ID.
Verify EmailTool to initiate email verification.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

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

How the Tool Router works

The Tool Router 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 Instantly account and project
  • Basic familiarity with async Python/Typescript

Getting API Keys for OpenAI, Composio, and Instantly

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 Instantly 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 instantly_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=["instantly"],
    )

    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 Instantly actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Instantly 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, instantly)
  • 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 Instantly 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 Instantly 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 Instantly

Run the agent

npx ts-node llamaindex-agent.ts

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

Complete Code

Here's the complete code to get you started with Instantly 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=["instantly"],
    )

    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 Instantly actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Instantly 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 Instantly to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways:
  • Tool Router dynamically exposes Instantly 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.

How to build Instantly MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Instantly MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Instantly MCP with Claude Agent SDK

Google ADK

Google ADK

Use Instantly MCP with Google ADK

LangChain

LangChain

Use Instantly MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Instantly MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Instantly MCP with Mastra AI

CrewAI

CrewAI

Use Instantly MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Instantly MCP?

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

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

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

Used by agents from

Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

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