# How to integrate Doppler secretops MCP with CrewAI

```json
{
  "title": "How to integrate Doppler secretops MCP with CrewAI",
  "toolkit": "Doppler secretops",
  "toolkit_slug": "doppler_secretops",
  "framework": "CrewAI",
  "framework_slug": "crew-ai",
  "url": "https://composio.dev/toolkits/doppler_secretops/framework/crew-ai",
  "markdown_url": "https://composio.dev/toolkits/doppler_secretops/framework/crew-ai.md",
  "updated_at": "2026-05-12T10:09:34.971Z"
}
```

## 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 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.

## Also integrate Doppler secretops with

- [OpenAI Agents SDK](https://composio.dev/toolkits/doppler_secretops/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/doppler_secretops/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/doppler_secretops/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/doppler_secretops/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/doppler_secretops/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/doppler_secretops/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/doppler_secretops/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/doppler_secretops/framework/cli)
- [Google ADK](https://composio.dev/toolkits/doppler_secretops/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/doppler_secretops/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/doppler_secretops/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/doppler_secretops/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/doppler_secretops/framework/llama-index)

## 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

| Tool slug | Name | Description |
|---|---|---|
| `DOPPLER_SECRETOPS_ACTIVITY_LOGS_LIST` | Activity Logs List | Tool to list workplace activity logs. Use when you need to fetch recent activity logs. |
| `DOPPLER_SECRETOPS_ACTIVITY_LOGS_RETRIEVE` | Retrieve Activity Log | Tool to retrieve a single activity log entry by id. Use when you have a valid Activity Log id. |
| `DOPPLER_SECRETOPS_CONFIG_LOGS_GET` | Retrieve Config Log Entry | Tool to retrieve a specific config log entry. Use when needing details of a single config log; call after specifying project, config, and log identifiers. |
| `DOPPLER_SECRETOPS_CONFIG_LOGS_LIST` | Config Logs List | Tool to list config change logs for a specific config. Use when you need the audit trail for a config after confirming its identity. |
| `DOPPLER_SECRETOPS_CONFIG_LOGS_ROLLBACK` | Config Logs Rollback | Tool to rollback a config to a selected log version. Use when needing to undo a specific change by its log ID, after confirming project, config, and log ID. |
| `DOPPLER_SECRETOPS_CONFIGS_CLONE` | Clone Config | Tool to clone a branch config including all its secrets. Use after confirming the source config details. |
| `DOPPLER_SECRETOPS_CONFIGS_CREATE` | Create Branch Config | Tool to create a branch config. Use when you need to programmatically establish a new branch-based configuration for a specified project and environment. Use after selecting the target project and environment. |
| `DOPPLER_SECRETOPS_CONFIGS_DELETE` | Configs Delete | Tool to delete a config permanently. Use when you need to remove a config that is no longer needed. |
| `DOPPLER_SECRETOPS_CONFIGS_GET` | Get Config Details | Tool to fetch a config's details. Use when you need metadata for a specific config after specifying the project and config names. Example: "Get details for config 'staging-config' in project 'proj-123'." |
| `DOPPLER_SECRETOPS_CONFIGS_LOCK` | Lock Config | Tool to lock a config. Use when you need to prevent a config from being renamed or deleted after confirming the project and config names. Example: "Lock config 'staging-config' in project 'proj-123' after finalizing environment setup." |
| `DOPPLER_SECRETOPS_CONFIGS_UNLOCK` | Unlock Config | Tool to unlock a config. Use when you need to allow renaming or deletion of a previously locked config. Example: "Unlock config 'staging-config' in project 'proj-123'." |
| `DOPPLER_SECRETOPS_CONFIGS_UPDATE` | Update Config | Tool to modify an existing config. Use when you need to rename a config after confirming project and config names. |
| `DOPPLER_SECRETOPS_DYNAMIC_SECRETS_REVOKE_LEASE` | Revoke Dynamic Secret Lease | Tool to revoke a dynamic secret lease. Use when you need to invalidate an active lease by its ID after confirming the config and dynamic secret identifiers. |
| `DOPPLER_SECRETOPS_ENVIRONMENTS_CREATE` | Create Environment | Tool to create a new environment. Use when you need to programmatically create an environment for a specified project. |
| `DOPPLER_SECRETOPS_ENVIRONMENTS_DELETE` | Environments Delete | Tool to delete an environment. Use when you need to remove an environment from a project after confirming it's no longer in use. |
| `DOPPLER_SECRETOPS_ENVIRONMENTS_GET` | Get Environment Details | Tool to retrieve an environment. Use when you need metadata for a specific environment after specifying the project and environment slug. |
| `DOPPLER_SECRETOPS_ENVIRONMENTS_LIST` | List Environments | Tool to list environments in a Doppler project. Use when you need environment metadata for a specific project after providing the project slug. |
| `DOPPLER_SECRETOPS_ENVIRONMENTS_RENAME` | Rename Environment | Tool to rename an environment. Use when you need to update an environment's display name after confirming project and environment identifiers. |
| `DOPPLER_SECRETOPS_GROUPS_DELETE_MEMBER` | Remove Group Member | Tool to remove a member from a group. Use after confirming the group slug and member identifiers. |
| `DOPPLER_SECRETOPS_INTEGRATIONS_LIST` | Integrations List | Tool to list all external integrations. Use when you need to retrieve all configured external integrations after authentication. |
| `DOPPLER_SECRETOPS_INVITES_LIST` | Invites List | Tool to list open workplace invites. Use when you need to retrieve all pending invitations for the current Doppler workplace after authenticating. |
| `DOPPLER_SECRETOPS_PROJECT_MEMBERS_DELETE` | Remove Project Member | Tool to remove a member from a project. Use after confirming project slug, member type, and slug. Example: "Delete member 'jdoe' of type 'users' from project 'my-project-slug'." |
| `DOPPLER_SECRETOPS_PROJECT_MEMBERS_GET` | Get Project Member | Tool to retrieve a project member by type and slug. Use after confirming project slug, member type, and slug. |
| `DOPPLER_SECRETOPS_PROJECT_PERMISSIONS_LIST` | Project Permissions List | Tool to list project-level permissions. Use when you need to fetch all available permissions for projects after authentication. |
| `DOPPLER_SECRETOPS_PROJECT_ROLES_GET` | Get Project Role | Tool to retrieve a project role. Use when you need details of a specific project role after authenticating. |
| `DOPPLER_SECRETOPS_PROJECTS_CREATE` | Create Project | Tool to create a project. Use when you need to programmatically initialize a new Doppler project after authentication. |
| `DOPPLER_SECRETOPS_PROJECTS_DELETE` | Projects Delete | Tool to delete a project permanently. Use after confirming irreversible removal. |
| `DOPPLER_SECRETOPS_PROJECTS_LIST` | List Projects | Tool to list Doppler projects. Use when you need to retrieve all projects with optional pagination. |
| `DOPPLER_SECRETOPS_SECRETS_UPDATE` | Update Secrets | Tool to update secrets in a config. Use when you need to change secret values for deployments. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Doppler secretops MCP server is an implementation of the Model Context Protocol that connects your AI agent to Doppler secretops. It provides structured and secure access so your agent can perform Doppler secretops operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. 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

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

**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
```bash
pip install composio crewai crewai-tools[mcp] python-dotenv
```

### 3. Set up environment variables

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
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import dependencies

**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
```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")
```

### 5. Create a Composio Tool Router session for Doppler secretops

**What's happening:**
- You create a Doppler secretops only session through Composio
- Composio returns an MCP HTTP URL that exposes Doppler secretops tools
```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
```

### 6. Initialize the MCP Server

**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.
```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,
    )
```

### 7. Create a CLI Chatloop and define the Crew

**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.
```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")
```

## Complete Code

```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_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](https://composio.dev/toolkits/doppler_secretops/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/doppler_secretops/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/doppler_secretops/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/doppler_secretops/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/doppler_secretops/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/doppler_secretops/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/doppler_secretops/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/doppler_secretops/framework/cli)
- [Google ADK](https://composio.dev/toolkits/doppler_secretops/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/doppler_secretops/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/doppler_secretops/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/doppler_secretops/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/doppler_secretops/framework/llama-index)

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- [Appcircle](https://composio.dev/toolkits/appcircle) - Appcircle is an enterprise-grade mobile CI/CD platform for building, testing, and publishing mobile apps. It streamlines mobile DevOps so teams ship faster and with more confidence.
- [Appdrag](https://composio.dev/toolkits/appdrag) - Appdrag is a cloud platform for building websites, APIs, and databases with drag-and-drop tools and code editing. It accelerates development and iteration by combining hosting, database management, and low-code features in one place.
- [Appveyor](https://composio.dev/toolkits/appveyor) - AppVeyor is a cloud-based continuous integration service for building, testing, and deploying applications. It helps developers automate and streamline their software delivery pipelines.
- [Backendless](https://composio.dev/toolkits/backendless) - Backendless is a backend-as-a-service platform for mobile and web apps, offering database, file storage, user authentication, and APIs. It helps developers ship scalable applications faster without managing server infrastructure.
- [Baserow](https://composio.dev/toolkits/baserow) - Baserow is an open-source no-code database platform for building collaborative data apps. It makes it easy for teams to organize data and automate workflows without writing code.
- [Bench](https://composio.dev/toolkits/bench) - Bench is a benchmarking tool for automated performance measurement and analysis. It helps you quickly evaluate, compare, and track your systems or workflows.
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- [Bitbucket](https://composio.dev/toolkits/bitbucket) - Bitbucket is a Git-based code hosting and collaboration platform for teams. It enables secure repository management and streamlined code reviews.
- [Blazemeter](https://composio.dev/toolkits/blazemeter) - Blazemeter is a continuous testing platform for web and mobile app performance. It empowers teams to automate and analyze large-scale tests with ease.
- [Blocknative](https://composio.dev/toolkits/blocknative) - Blocknative delivers real-time mempool monitoring and transaction management for public blockchains. Instantly track pending transactions and optimize blockchain interactions with live data.

## Frequently Asked Questions

### 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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