How do I create a Doppler Service Token?

Log in to the [**Doppler Dashboard**](https://dashboard.doppler.com), select your project, go to **Settings** > **Tokens** and click **Generate Token**. Choose the scope (project + config/environment), set the access level (Read or Read+Write) and copy the token immediately — it won't be shown again.

Can I update multiple secrets at once?

Yes! Use the `change_secrets` tool with a JSON object mapping names to values, e.g. `{"DATABASE_URL":"postgres://new-host","API_KEY":"sk-new"}`. This creates or updates all specified secrets in a single atomic operation.

What is the difference between a Personal Token and a Service Token?

A **Personal Token** is scoped to your user account and can access all workspaces and projects you have permission for. A **Service Token** is scoped to a specific project and config, with either read-only or read+write access. Service tokens are recommended for CI/CD and automated integrations, while personal tokens are better for development and admin tasks.

Can I view the activity history for a project?

Yes! Use the `list_activity_logs` tool with the project_slug to see all audit events (secret reads, writes, config changes, user additions). Optionally filter by config_name to see activity for a specific environment only. Each log entry shows who performed the action, when, and what was affected.

Doppler MCP Server for OpenAI Agents SDK 12 tools — connect in under 2 minutes

Name: Doppler
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 12 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Doppler through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Doppler Assistant",
            instructions=(
                "You help users interact with Doppler. "
                "You have access to 12 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Doppler"
        )
        print(result.final_output)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Doppler MCP Server

Connect your Doppler account to any AI agent and take full control of your secrets management through natural conversation.

The OpenAI Agents SDK auto-discovers all 12 tools from Doppler through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries Doppler, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.

What you can do

Workspace & Project Discovery — List all workspaces and projects with their names, slugs and descriptions
Config (Environment) Management — View all configs (development, staging, production) per project and their metadata
Secret Auditing — List all secret names and computed values for any config, with environment fallback resolution
Secret Operations — Add, update and delete secrets in any environment with atomic change requests
Activity Logging — Review the full audit log of secret reads, writes, config changes and user activity per project

The Doppler MCP Server exposes 12 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Doppler to OpenAI Agents SDK via MCP

Follow these steps to integrate the Doppler MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 12 tools from Doppler

Why Use OpenAI Agents SDK with the Doppler MCP Server

OpenAI Agents SDK provides unique advantages when paired with Doppler through the Model Context Protocol.

Native MCP integration via `MCPServerSse` — pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Doppler + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Doppler MCP Server delivers measurable value.

Automated workflows: build agents that query Doppler, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents — one queries Doppler, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Doppler tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Doppler to resolve tickets, look up records, and update statuses without human intervention

Doppler MCP Tools for OpenAI Agents SDK (12)

These 12 tools become available when you connect Doppler to OpenAI Agents SDK via MCP:

change_secrets

Provide project_slug, config_name and a JSON object mapping secret names to values. For example: {"DATABASE_URL":"postgres://...","API_KEY":"sk-..."}. Existing secrets not included are not modified. Add or update secrets in a Doppler config

delete_secrets

Provide project_slug, config_name and comma-separated secret names. WARNING: deleted secrets cannot be recovered. If a secret inherits a value from a parent, it reverts to that value. Delete secrets from a Doppler config

get_account

Returns account email, name, and token metadata (type, scope, permissions). Use this to verify your token is working correctly and understand its access level. Get the current Doppler account details

get_config

Returns config name, project, root status, associated environment template, creation date and locked status. Get details for a specific Doppler config

get_project

Provide the project slug (e.g. "my-api-project") and optionally the workspace slug. Get details for a specific Doppler project

get_secret

Returns the secret name and its resolved value with fallbacks from parent environments applied. Get a specific secret value from a Doppler config

list_activity_logs

Each entry shows who performed what action, when and the affected config. Optionally filter by config_name. Useful for security auditing and compliance. List activity logs for a Doppler project

list_configs

Each config represents a deployment environment (development, staging, production) and contains its own set of secrets. Returns config name, project slug, root status and environment template used. List configs (environments) for a Doppler project

list_environments

g. development, staging, production, preview). Returns environment name, slug and whether it is the default environment. List Doppler environment types

list_projects

Optionally filter by workspace slug. Each project contains configs (environments) and secrets. Returns project name, slug, description, and creation date. List Doppler projects

list_secrets

Returns each secret's name, computed value (with environment fallbacks applied), visibility status. Provide the project_slug and config_name. List all secrets for a Doppler config

list_workspaces

A workspace is the top-level organizational unit in Doppler that groups projects. Returns workspace name, slug and creation date. List all Doppler workspaces

Example Prompts for Doppler in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Doppler immediately.

"Show me all configs for my 'backend-api' project."

"Update the DATABASE_URL secret in my prod config to point to the new database."

"Who changed secrets in my project in the last week?"

Troubleshooting Doppler MCP Server with OpenAI Agents SDK

Common issues when connecting Doppler to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Doppler + OpenAI Agents SDK FAQ

Common questions about integrating Doppler MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.