How to integrate Doppler MCP with CrewAI

This guide walks you through connecting Doppler to CrewAI using the Composio tool router. By the end, you'll have a working Doppler agent that can get secrets for staging environment in doppler, add a new secret to marketing project, list all projects and their environments through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a Doppler account through Composio's Doppler MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Api Key

Doppler is a secrets management platform for organizing and syncing environment variables. It lets teams securely centralize, share, and update secrets across infrastructure.

26 Tools

Introduction

This guide walks you through connecting Doppler to CrewAI using the Composio tool router. By the end, you'll have a working Doppler agent that can get secrets for staging environment in doppler, add a new secret to marketing project, list all projects and their environments through natural language commands.

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

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

Also integrate Doppler with

ChatGPTOpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenCodeCursorVS CodeOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndex

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Doppler connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Doppler
  • Build a conversational loop where your agent can execute Doppler operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

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

The Doppler MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Doppler account. It provides structured and secure access so your agent can perform Doppler operations on your behalf.

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 step08 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Doppler connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python
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 crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Doppler via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env
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_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model
5

Import dependencies

python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

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")
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Doppler MCP URL
6

Create a Composio Tool Router session for Doppler

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["doppler"])

url = session.mcp.url
What's happening:
  • You create a Doppler only session through Composio
  • Composio returns an MCP HTTP URL that exposes Doppler tools
7

Initialize the MCP Server

python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
What's Happening:
  • Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
  • MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
  • Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
  • Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
  • Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.
8

Create a CLI Chatloop and define the Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's Happening:
  • Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
  • Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
  • Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
  • Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
  • Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
  • Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.

Complete Code

Here's the complete code to get you started with Doppler and CrewAI:

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_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.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["doppler"],
)
url = session.mcp.url

# Configure LLM
llm = LLM(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY"),
)

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\n")

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

Conclusion

You now have a CrewAI agent connected to Doppler through Composio's Tool Router. The agent can perform Doppler operations through natural language commands.

Next steps:

  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations
TOOLS

Supported Tools

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

Get Authenticated User Info

Tool to retrieve information about the authenticated user or token.

Get Config Log

Tool to retrieve a specific config log from Doppler.

List Config Logs

Tool to retrieve configuration change logs for a specific config in a project.

Get Config

Tool to retrieve a specific Doppler config by project and config name.

List Doppler Configs

Tool to list configurations from a Doppler project.

Create Encrypted Share Link

Tool to generate a Doppler Share link by sending an encrypted secret.

Create Plain Text Share Link

Tool to generate a Doppler Share link by sending a plain text secret.

List Environments

Tool to list all environments in a Doppler project.

List Integrations

Tool to retrieve all existing integrations in Doppler.

List Change Requests

Tool to list existing change requests in the Doppler workplace.

Get Project Role

Tool to retrieve details of a specific project role in Doppler.

List Project Roles

Tool to list all available project roles in Doppler.

List Project Role Permissions

Tool to list all available permissions for project roles in Doppler.

Get Project Details

Tool to retrieve details of a specific Doppler project by its identifier.

List Doppler Projects

Tool to list all Doppler projects in your workspace.

Delete Secret

Tool to delete a secret from a Doppler config.

Download Secrets

Tool to download secrets from a Doppler config in various formats.

Get Secret

Tool to retrieve a specific secret from a Doppler project config.

List Doppler Secrets

Tool to list all secrets for a specific Doppler config within a project.

List Secret Names

Tool to retrieve the list of secret names from a specific Doppler config.

Update Doppler Secrets

Tool to update secrets in a Doppler config.

Update Secret Note

Tool to update a note for a secret in Doppler.

Get Workplace Information

Tool to retrieve workplace information from Doppler.

Get Workplace Role

Tool to retrieve workplace role information from Doppler.

List Workplace Roles

Tool to list all workplace roles in your Doppler workspace.

List Workplace Permissions

Tool to retrieve all available workplace permissions in Doppler.

FRAMEWORKS

How to build Doppler MCP Agent with another framework

ChatGPT logo

ChatGPT

Use Doppler MCP with ChatGPT

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Doppler MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Doppler MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Doppler MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Doppler MCP with Claude Cowork

Codex logo

Codex

Use Doppler MCP with Codex

Cursor logo

Cursor

Use Doppler MCP with Cursor

OpenClaw logo

OpenClaw

Use Doppler MCP with OpenClaw

Hermes logo

Hermes

Use Doppler MCP with Hermes

CLI logo

CLI

Use Doppler MCP with CLI

Google ADK logo

Google ADK

Use Doppler MCP with Google ADK

LangChain logo

LangChain

Use Doppler MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Doppler MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Doppler MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Doppler MCP with LlamaIndex

OpenCode logo

OpenCode

Use Doppler MCP with OpenCode

VS Code logo

VS Code

Use Doppler MCP with VS Code

FAQ

Frequently asked questions

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

Yes, you can. CrewAI 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 Doppler tools.

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

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Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati
Harsha Gaddipati
Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya
Abhi Arya
Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave
Nirman Dave
CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu
Ryan Yu
Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola
Tomisin Jenrola
Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche
Jerome Leclanche
Co-Founder, Ingram Technologies