How to integrate Salesforce MCP with LlamaIndex

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Introduction

This guide walks you through connecting Salesforce to LlamaIndex using the Composio tool router. By the end, you'll have a working Salesforce agent that can add new contact to spring campaign, clone opportunity with all associated products, complete follow-up task for lead smith, associate contact jane doe to acme account through natural language commands.

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

The Salesforce MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Salesforce account. It provides structured and secure access to your CRM data, so your agent can perform actions like managing contacts, handling opportunities, automating campaigns, and tracking tasks on your behalf.

  • Automated contact and lead management: Effortlessly create new accounts, add contacts or leads to campaigns, and associate contacts with accounts to keep your CRM data up-to-date.
  • Streamlined opportunity management: Let your agent clone opportunities, add products to deals, and manage the full sales cycle for your pipeline.
  • Intelligent campaign automation: Enable your agent to create campaigns, enroll contacts or leads, and track campaign engagement for more effective marketing.
  • Task completion and workflow efficiency: Have your agent mark Salesforce tasks as completed and update records, keeping your team on track without manual intervention.
  • Flexible record operations: Allow the agent to clone existing records or apply lead assignment rules, ensuring data consistency and smart routing across your Salesforce environment.

Supported Tools & Triggers

Tools
Triggers
Add contact to campaignAdds a contact to a campaign by creating a campaignmember record, allowing you to track campaign engagement.
Add lead to campaignAdds a lead to a campaign by creating a campaignmember record, allowing you to track campaign engagement.
Add product to opportunityAdds a product (line item) to an opportunity.
Apply lead assignment rulesApplies configured lead assignment rules to a specific lead, automatically routing it to the appropriate owner based on your organization's rules.
Associate contact to accountAssociates a contact with an account by updating the contact's accountid field.
Clone opportunity with productsClones an opportunity and optionally its products (line items).
Clone recordCreates a copy of an existing salesforce record by reading its data, removing system fields, and creating a new record.
Complete taskMarks a task as completed with optional completion notes.
Create accountCreates a new account in salesforce with the specified information.
Create campaignCreates a new campaign in salesforce with the specified information.
Create contactCreates a new contact in salesforce with the specified information.
Create leadCreates a new lead in salesforce with the specified information.
Create noteCreates a new note attached to a salesforce record with the specified title and content.
Create opportunityCreates a new opportunity in salesforce with the specified information.
Create taskCreates a new task in salesforce to track activities, to-dos, and follow-ups related to contacts, leads, or other records.
Delete accountPermanently deletes an account from salesforce.
Delete campaignPermanently deletes a campaign from salesforce.
Delete contactPermanently deletes a contact from salesforce.
Delete leadPermanently deletes a lead from salesforce.
Delete notePermanently deletes a note from salesforce.
Delete opportunityPermanently deletes an opportunity from salesforce.
Get accountRetrieves a specific account by id from salesforce, returning all available fields.
Get campaignRetrieves a specific campaign by id from salesforce, returning all available fields.
Get contactRetrieves a specific contact by id from salesforce, returning all available fields.
Get dashboardGets detailed metadata for a specific dashboard including its components, layout, and filters.
Get leadRetrieves a specific lead by id from salesforce, returning all available fields.
Get noteRetrieves a specific note by id from salesforce, returning all available fields.
Get opportunityRetrieves a specific opportunity by id from salesforce, returning all available fields.
Get report metadataGets detailed metadata for a specific report including its structure, columns, filters, and groupings.
Get report instance resultsGets the results of a report instance created by running a report.
Get user infoRetrieves information about the current user or a specific user in salesforce.
List accountsLists accounts from salesforce using soql query, allowing flexible filtering, sorting, and field selection.
List campaignsLists campaigns from salesforce using soql query, allowing flexible filtering, sorting, and field selection.
List contactsLists contacts from salesforce using soql query, allowing flexible filtering, sorting, and field selection.
List dashboardsLists all dashboards available in salesforce with basic metadata including name, id, and urls.
List email templatesLists available email templates in salesforce with filtering and search capabilities.
List leadsLists leads from salesforce using soql query, allowing flexible filtering, sorting, and field selection.
List notesLists notes from salesforce using soql query, allowing flexible filtering, sorting, and field selection.
List opportunitiesLists opportunities from salesforce using soql query, allowing flexible filtering, sorting, and field selection.
List reportsLists all reports available in salesforce with basic metadata including name, id, and urls.
Log callLogs a completed phone call as a task in salesforce with call-specific details like duration, type, and disposition.
Log email activityCreates an emailmessage record to log email activity in salesforce, associating it with related records.
Mass transfer ownershipTransfers ownership of multiple records to a new owner in a single operation using salesforce's composite api for better performance.
Remove from campaignRemoves a lead or contact from a campaign by deleting the campaignmember record.
Run reportRuns a report and returns the results.
Run SOQL queryExecutes a soql query against salesforce data.
Search accountsSearch for salesforce accounts using multiple criteria like name, industry, type, location, or contact information.
Search campaignsSearch for salesforce campaigns using multiple criteria like name, type, status, date range, or active status.
Search contactsSearch for salesforce contacts using multiple criteria like name, email, phone, account, or title.
Search leadsSearch for salesforce leads using multiple criteria like name, email, phone, company, title, status, or lead source.
Search notesSearch for salesforce notes using multiple criteria like title, body content, parent record, owner, or creation date.
Search opportunitiesSearch for salesforce opportunities using multiple criteria like name, account, stage, amount, close date, or status.
Search tasksSearch for salesforce tasks using multiple criteria like subject, status, priority, assigned user, related records, or dates.
Send emailSends an email through salesforce with options for recipients, attachments, and activity logging.
Send email from templateSends an email using a predefined salesforce email template with merge field support.
Send mass emailSends bulk emails to multiple recipients, either using a template or custom content.
Update accountUpdates an existing account in salesforce with the specified changes.
Update campaignUpdates an existing campaign in salesforce with the specified changes.
Update contactUpdates an existing contact in salesforce with the specified changes.
Update leadUpdates an existing lead in salesforce with the specified changes.
Update noteUpdates an existing note in salesforce with the specified changes.
Update opportunityUpdates an existing opportunity in salesforce with the specified changes.
Update taskUpdates an existing task in salesforce with new information.

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

Getting API Keys for OpenAI, Composio, and Salesforce

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 Salesforce 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 salesforce_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=["salesforce"],
    )

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

Run the agent

npx ts-node llamaindex-agent.ts

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

Complete Code

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

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

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FAQ

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

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

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

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

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