How to integrate Doppler secretops MCP with CrewAI

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Introduction

This guide walks you through connecting Doppler secretops to CrewAI using the Composio tool router. By the end, you'll have a working Doppler secretops agent that can list all recent config changes for project x, rollback staging config to previous version, clone production config to a new branch, lock main config to prevent accidental edits through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Doppler secretops account through Composio's Doppler secretops 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:
  • Get a Composio API key and configure your Doppler secretops connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Doppler secretops
  • Build a conversational loop where your agent can execute Doppler secretops 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 secretops MCP server, and what's possible with it?

The Doppler secretops 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 secretops account. It provides structured and secure access to your secrets management platform, so your agent can perform actions like auditing activity logs, managing environment configs, rolling back changes, and automating config cloning on your behalf.

  • Fetch activity and config logs: Quickly retrieve detailed activity logs and config change histories to monitor changes and track security events across your Doppler workspace.
  • Rollback and restore configurations: Direct your agent to roll back a config to a previous version, helping you easily undo unwanted or risky changes with confidence.
  • Clone and create branch configs: Automate the cloning of config branches or create new branch configs for different environments and projects, streamlining your secrets management workflows.
  • Config locking and deletion: Secure your critical configs by locking them against unwanted changes or safely deleting obsolete configurations as part of environment cleanup.
  • Retrieve detailed config metadata: Instantly get comprehensive details for any specific config, including project and environment context, to support debugging and compliance tasks.

Supported Tools & Triggers

Tools
Activity Logs ListTool to list workplace activity logs.
Retrieve Activity LogTool to retrieve a single activity log entry by id.
Retrieve Config Log EntryTool to retrieve a specific config log entry.
Config Logs ListTool to list config change logs for a specific config.
Config Logs RollbackTool to rollback a config to a selected log version.
Clone ConfigTool to clone a branch config including all its secrets.
Create Branch ConfigTool to create a branch config.
Configs DeleteTool to delete a config permanently.
Get Config DetailsTool to fetch a config's details.
Lock ConfigTool to lock a config.
Unlock ConfigTool to unlock a config.
Update ConfigTool to modify an existing config.
Revoke Dynamic Secret LeaseTool to revoke a dynamic secret lease.
Create EnvironmentTool to create a new environment.
Environments DeleteTool to delete an environment.
Get Environment DetailsTool to retrieve an environment.
List EnvironmentsTool to list environments in a Doppler project.
Rename EnvironmentTool to rename an environment.
Remove Group MemberTool to remove a member from a group.
Integrations ListTool to list all external integrations.
Invites ListTool to list open workplace invites.
Remove Project MemberTool to remove a member from a project.
Get Project MemberTool to retrieve a project member by type and slug.
Project Permissions ListTool to list project-level permissions.
Get Project RoleTool to retrieve a project role.
Create ProjectTool to create a project.
Projects DeleteTool to delete a project permanently.
List ProjectsTool to list Doppler projects.
Update SecretsTool to update secrets in a config.

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 starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Doppler secretops connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

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.

Install dependencies

bash
pip install composio crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Doppler secretops via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env

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

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 secretops MCP URL

Create a Composio Tool Router session for Doppler secretops

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

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

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.

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 secretops and CrewAI:

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_secretops"],
)
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 secretops through Composio's Tool Router. The agent can perform Doppler secretops 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

How to build Doppler secretops MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Doppler secretops MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Doppler secretops MCP with Claude Agent SDK

Google ADK

Google ADK

Use Doppler secretops MCP with Google ADK

LangChain

LangChain

Use Doppler secretops MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Doppler secretops MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Doppler secretops MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Doppler secretops MCP with LlamaIndex

FAQ

What are the differences in Tool Router MCP and Doppler secretops MCP?

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

Can I use Tool Router MCP with CrewAI?

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 secretops tools.

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

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

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