How to integrate Centralstationcrm MCP with LlamaIndex

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Introduction

This guide walks you through connecting Centralstationcrm to LlamaIndex using the Composio tool router. By the end, you'll have a working Centralstationcrm agent that can add new company to crm contacts, log a sales opportunity for a client, count total people in my crm, record a birthday for an existing contact through natural language commands.

This guide will help you understand how to give your LlamaIndex agent real control over a Centralstationcrm account through Composio's Centralstationcrm 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 Centralstationcrm
  • Connect LlamaIndex to the Centralstationcrm MCP server
  • Build a Centralstationcrm-powered agent using LlamaIndex
  • Interact with Centralstationcrm 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 Centralstationcrm MCP server, and what's possible with it?

The Centralstationcrm MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Centralstationcrm account. It provides structured and secure access to your customer relationship data, so your agent can perform actions like managing contacts, creating deals, updating company records, and tracking key interactions on your behalf.

  • Automated contact management: Quickly add new people to your CRM, update their details, and ensure your contact database stays current without manual entry.
  • Company and organization creation: Effortlessly create new company records so you can keep your account-based selling and organization tracking up-to-date.
  • Deal tracking and creation: Instantly log new sales opportunities by creating deals linked to your contacts or companies, helping your team stay on top of the pipeline.
  • Detailed relationship enrichment: Add addresses, assistants, avatars, and contact details to people in your CRM, making every customer profile richer and more actionable.
  • Milestone and history recording: Record important life events or milestones (like birthdays or anniversaries) for each person to boost relationship management and personalized outreach.

Supported Tools & Triggers

Tools
Check ConnectionTool to verify the connection status of the centralstationcrm api key.
Count PeopleTool to retrieve the total number of people in the account.
Create CompanyTool to create a new company record.
Create DealTool to create a new deal record.
Create PersonTool to create a new person record.
Create Person AddressTool to create a new address for a specific person.
Create Person AssistantTool to create a new assistant (assi) entry for a specific person.
Create Person AvatarTool to create a new avatar for a specific person.
Create Person Contact DetailTool to create a new contact detail for a specific person.
Create Person Historic EventTool to create a new historic event for a specific person.
Delete CompanyTool to delete a company record by id.
Delete personTool to delete a person record by id.
Delete Person AddressTool to delete a person's address by its id.
Delete Person AssiTool to delete an assi entry of a person.
Delete Person AvatarTool to delete a person's avatar by its id.
Delete Person Contact DetailTool to delete a contact detail of a person.
Delete Person Historic EventTool to delete a historic event of a person by its id.
Get API User MaildropTool to retrieve the current api user's maildrop for people and companies.
Get CompanyTool to retrieve details of a specific company by id.
Get DealTool to retrieve details of a specific deal by its id.
Get DealsTool to retrieve a paginated list of all deals.
Get PersonTool to retrieve details of a specific person by id.
Get Person AddressTool to retrieve a specific address of a person by address id.
Get Person AddressesTool to retrieve all addresses for a specific person.
Get Person AssiTool to retrieve a specific assi entry of a person by id.
Get Person AssisTool to retrieve all assistant entries for a specific person.
Get Person AvatarTool to retrieve a specific avatar of a person by avatar id.
Get Person AvatarsTool to retrieve all avatars for a specific person.
Get Person Contact DetailTool to retrieve a specific contact detail by id for a person.
Get Person Custom FieldsTool to retrieve all custom fields for a specific person.
Get Person Historic EventTool to retrieve a specific historic event of a person by id.
Get Person Historic EventsTool to retrieve all historic events for a specific person.
Get PersonsTool to retrieve a paginated list of all people.
Merge PersonTool to merge another person into an existing person by id.
Search RecordsSearch records
Search PeopleTool to retrieve people matching search criteria.
Stats PeopleTool to retrieve key statistics about people.
Update CompanyTool to update an existing company by id.
Update PersonTool to update an existing person by id.
Update Person AddressTool to update a specific address of a person.
Update Person AssiTool to update an assi entry of a person.
Update Person Contact DetailTool to update a specific contact detail of a person by id.
Update Person Historic EventTool to update a historic event of a person by id.

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 Centralstationcrm account and project
  • Basic familiarity with async Python/Typescript

Getting API Keys for OpenAI, Composio, and Centralstationcrm

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 Centralstationcrm 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 centralstationcrm_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=["centralstationcrm"],
    )

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

Run the agent

npx ts-node llamaindex-agent.ts

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

Complete Code

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

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

OpenAI Agents SDK

OpenAI Agents SDK

Use Centralstationcrm MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Centralstationcrm MCP with Claude Agent SDK

Google ADK

Google ADK

Use Centralstationcrm MCP with Google ADK

LangChain

LangChain

Use Centralstationcrm MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Centralstationcrm MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Centralstationcrm MCP with Mastra AI

CrewAI

CrewAI

Use Centralstationcrm MCP with CrewAI

FAQ

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

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

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

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

Used by agents from

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

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