Every engineering team has spent years trying to keep credentials out of source code. Then AI agents moved the problem. Coding agents review code, agents run workflows, and MCP servers broker access to databases, cloud providers, and internal APIs on a developer’s behalf. For every engineer on a team, there are now dozens of automated identities that need secrets too, and each one is another place a credential can leak. AI agents have accelerated code creation but have also created a challenge for modern teams. Secrets management has become a critical infrastructure across enterprises, and most tooling was never built for it.
Doppler centralizes credentials for every engineer, pipeline, and AI agent in a single, easy-to-use control plane. Security teams love Doppler because it’s a critical tool that developers actually use, now available both in cloud or on-prem.
One platform, every identity
Doppler’s secrets management platform stores API keys, database URLs, tokens, and certificates in a single system of record and delivers them to applications at runtime. Developers, CI/CD pipelines, MCP servers, and AI agents all draw from the same source of truth, so there’s no separate process for machines. Changes sync in real time, so every team and environment stays consistent as the setup grows, and Doppler remains the single source of truth in the center of it all.
A hierarchy built to scale
Projects sit at the root of Doppler’s structure, generally tied to an application or service. Within a project, every environment has a root config and branches, and a config is a set of secrets. Branch configs inherit from the root while letting teams tune individual deployments, secret referencing cuts duplication, and each developer gets a personal config for local work. This structure replaces the need for .env files and is more secure and even easier to use.
Secrets accessed at runtime
Rather than hardcoding credentials in your application files, Doppler can inject them at runtime. The Doppler CLI’s doppler run command fetches secrets on demand and passes them as environment variables, so nothing sensitive lives in scripts, config files, or prompts. Doppler is well-suited for a variety of complex values that break traditional .env workflows, like multi-line encryption keys and embedded JSON and YAML. The same pattern keeps secrets out of the places AI workflows tend to leak them: logs, prompts, and model context.
Doppler also has the ability to remove long-lived credentials from the picture entirely. OIDC is available as an option. Azure, AWS, and GCP Syncs support creation with short-lived, verifiable identity tokens instead of static keys while teams that prefer to keep using static secrets still can. Dynamic secrets go a step further: for supported platforms, Doppler generates credentials scoped and time-boxed to a single session, then revokes them automatically when the lease ends.
Streamlined governance and visibility
Doppler enforces least privilege with fine-grained access controls and user groups scoped to only the projects and environments each identity needs. Secrets are all versioned, and access and view history are all captured. Any change can be easily rolled back or audited for compliance or investigation needs.
For larger teams, SCIM keeps membership in sync with your identity provider, so users and groups are provisioned and deprovisioned automatically and access never lingers after someone’s role changes. Doppler also connects to the tools teams already run through 50+ integrations across cloud platforms, CI/CD systems, and application frameworks, so secrets flow to where they’re consumed without custom code.
Engineers can leverage Change Requests to propose updates to configs they can’t write directly, giving admins control without breaking existing workflows. Log Forwarding allows users to push activity logs into existing SIEM tools for forensic analysis or deeper alerting. Doppler runs as a fully managed cloud service or deploys on-prem for teams with stricter requirements.
Built for AI agents
This is where Doppler’s model matters most. Agents are widely adopted by the vast majority of our customers. Machine credentials can be scoped per identity and rotated automatically, so a single compromise has a limited blast radius and a short lifespan.
The Doppler MCP server lets agents request the configuration they need natively, without custom scripts or hardcoded credentials, and permissions are enforced at every layer, so raw secrets stay out of the model’s context. Most importantly, because pricing is human-based, running 10 agents or 1,000 costs the same.
Secrets as the foundation for the next era
AI hasn’t changed the importance of secrets management, but it has fundamentally shifted the stakes. The teams adopting agents safely are the ones treating every identity, human, or machine as a critical area of their application to secure. Doppler gives them that confidence today, whether the secrets are needed across a person, a pipeline, or an agent.