How to integrate SalesRobot MCP with Pydantic AI

This guide walks you through connecting SalesRobot to Pydantic AI using the Composio tool router. By the end, you'll have a working SalesRobot agent that can list your campaigns, review prospect status, add prospects, update prospects, and send messages through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a SalesRobot account through Composio's SalesRobot MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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SalesRobot is a sales engagement platform for LinkedIn outreach, campaign management, prospecting, and messaging. It helps sales teams automate personalized outreach workflows and manage replies at scale.

10 Tools

Introduction

This guide walks you through connecting SalesRobot to Pydantic AI using the Composio tool router. By the end, you'll have a working SalesRobot agent that can list your campaigns, review prospect status, add prospects, update prospects, and send messages through natural language commands.

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

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

Also integrate SalesRobot with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for SalesRobot
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your SalesRobot workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

What is the SalesRobot MCP server, and what's possible with it?

The SalesRobot MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your SalesRobot account. It provides structured and secure access to your LinkedIn outreach campaigns, prospects, conversations, profiles, and posts, so your agent can manage prospects, review campaigns, track outreach, research profiles, and send messages on your behalf.

  • Campaign and prospect management: Have your agent list campaigns, review their prospects, add a LinkedIn prospect to a campaign, and update existing prospect details.
  • Outreach progress tracking: Let the agent check each prospect's sequence progress and message status within a campaign.
  • LinkedIn profile research: Direct your agent to retrieve person or company profiles and review their recent LinkedIn posts.
  • Inbox and messaging support: Instruct your agent to find relevant inbox conversations and send a message in an existing LinkedIn conversation.
  • Connected account visibility: Have your agent list the LinkedIn accounts connected to SalesRobot before running campaign, prospect, or messaging tasks.

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 step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account with an active API key
  • Basic familiarity with Python and async programming
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like SalesRobot
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs
5

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to SalesRobot
  • MCPServerStreamableHTTP connects to the SalesRobot MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for SalesRobot
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["salesrobot"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to SalesRobot tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
salesrobot_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[salesrobot_mcp],
    instructions=(
        "You are a SalesRobot assistant. Use SalesRobot tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the SalesRobot endpoint
  • The agent uses GPT-5 to interpret user commands and perform SalesRobot operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with SalesRobot.\n")

while True:
    user_input = input("You: ").strip()
    if user_input.lower() in {"exit", "quit", "bye"}:
        print("\nGoodbye!")
        break
    if not user_input:
        continue

    print("\nAgent is thinking...\n", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • SalesRobot API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

Here's the complete code to get you started with SalesRobot and Pydantic AI:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for SalesRobot
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["salesrobot"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    salesrobot_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[salesrobot_mcp],
        instructions=(
            "You are a SalesRobot assistant. Use SalesRobot tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with SalesRobot.\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "bye"}:
            print("\nGoodbye!")
            break
        if not user_input:
            continue

        print("\nAgent is thinking...\n", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've built a Pydantic AI agent that can interact with SalesRobot through Composio's Tool Router. With this setup, your agent can perform real SalesRobot actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + SalesRobot for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
TOOLS

Supported Tools

Every SalesRobot action and event your agent gets out of the box.

Add Prospect to Campaign

Add one identified LinkedIn prospect to a SalesRobot campaign.

Get LinkedIn Profile

Retrieve a LinkedIn person or company profile through a connected SalesRobot LinkedIn account.

Get Prospect Sequence Status

Get sequence-step execution and message status for one prospect, optionally within a campaign.

List Campaign Prospects

List and filter prospects for a campaign or across campaigns on one connected LinkedIn account.

List Campaigns

List and filter campaigns for one connected LinkedIn account, returning campaign UUIDs for prospect and status workflows.

List Inbox Threads

List and filter synchronized SalesRobot inbox threads for one connected LinkedIn account.

List LinkedIn Accounts

List LinkedIn accounts connected to SalesRobot and return the account UUIDs required by most other tools.

List LinkedIn Posts

List recent posts for a LinkedIn person or company through a connected SalesRobot LinkedIn account.

Send Message

Send one message in an existing SalesRobot LinkedIn conversation.

Update Prospect

Update profile, contact, and custom field data for one existing SalesRobot prospect.

FRAMEWORKS

How to build SalesRobot MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use SalesRobot MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use SalesRobot MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use SalesRobot MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use SalesRobot MCP with Claude Cowork

Codex logo

Codex

Use SalesRobot MCP with Codex

OpenClaw logo

OpenClaw

Use SalesRobot MCP with OpenClaw

Hermes logo

Hermes

Use SalesRobot MCP with Hermes

CLI logo

CLI

Use SalesRobot MCP with CLI

Google ADK logo

Google ADK

Use SalesRobot MCP with Google ADK

LangChain logo

LangChain

Use SalesRobot MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use SalesRobot MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use SalesRobot MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use SalesRobot MCP with LlamaIndex

CrewAI logo

CrewAI

Use SalesRobot MCP with CrewAI

FAQ

Frequently asked questions

With a standalone SalesRobot MCP server, the agents and LLMs can only access a fixed set of SalesRobot tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from SalesRobot and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. Pydantic AI 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 SalesRobot tools.

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

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