Artificial intelligence, and GenAI technologies in particular, are transforming our technology landscape.
For continuous delivery, AI allows us to solve previously-unsolvable problems. Parsing complex log files and diagnosing root cause failures and providing intelligent remediation; natural-language exploration of your software landscape, simplifying auditing, compliance, and standardization; agentic workflows providing intelligent glue between your essential software services.
At Octopus, we are bringing these capabilities to the best continuous delivery tool on the market, lowering risk, improving efficiency, and accelerating your software delivery.
Our AI capabilities span three complementary areas, each designed to address different aspects of your deployment lifecycle - from interactive assistance and troubleshooting to fully autonomous DevOps operations.
Current Capabilities
Octopus MCP Server
The Octopus MCP (Model Context Protocol) server represents a significant leap forward in AI integration capabilities. Built on Anthropic’s open standard for connecting AI agents to external data sources and tools, the MCP server will enable AI agents like Claude to interact directly with your Octopus Deploy infrastructure.
With supporting governance features like Agent API keys and Agent Service Accounts, you can also keep agent actions fully auditable in clear, filterable audit logs, so you can meet your compliance requirements.
The MCP server provides tools designed to solve key use-cases within change management, troubleshooting, and administration audit & compliance.
The MCP server architecture ensures that your deployment data remains secure while enabling powerful AI-assisted workflows. All interactions are logged and auditable, maintaining the compliance and governance standards your organization requires.
Learn more about Octopus MCP Server
Octopus AI Recovery Agent
Rapid recovery is crucial for Continuous Delivery. The Recovery Agent helps you recover from failures fast by using AI to analyze causes, suggest fixes, and, in the future, execute remediation steps - keeping you in control while handling the heavy lifting.
Octopus Server communicates with foundation models via https. For more details, see outbound requests.
Learn more about Octopus Recovery Agent
Claude Agent Step
The Claude Agent Step lets you run Claude Code, an AI agent, as a step in your deployment process or runbook. You bring your own Anthropic API key and choose the model. Octopus provides the rest: somewhere for the agent to run, context about the deployment it’s part of, and scoped access to your infrastructure.
Because the agent runs inside your deployment, it can do the work that would otherwise need custom scripting or a human. It can investigate why a deployment failed, run a smoke test against a freshly deployed service before you promote it, or handle the one-off glue tasks between your deployment tools.
The step is an alpha release. Letting an AI agent near your infrastructure is, like most things in deployment, an exercise in risk management, so the step gives you a few layers of control: you choose how the agent is sandboxed (the choice is mandatory), which tools it’s allowed to use, and which MCP servers it can talk to. Octopus also screens for prompt injection and keeps an access-controlled transcript of each session, so you can see exactly what the agent did (and why).
Learn more about the Claude Agent Step
API context for AI assistants (llms.txt)
Octopus Server’s /llms endpoint provides a Markdown summary of its API and deployment step properties. You can give the URL or downloaded content to your AI coding assistant as context for writing scripts and integrations.
Learn more about the llms.txt endpoint
Getting Started
Begin your AI-powered DevOps journey today with the Octopus AI Assistant, or the Octopus MCP Server. As an Early Access participant, you’ll help shape these features while gaining early access to capabilities that will transform how teams deploy software.
Security and Privacy
All AI capabilities in Octopus Deploy are built with security and privacy as foundational principles. We never use customer data to train AI models, all sensitive values remain protected through our existing security model, and AI features respect your current permission boundaries. The AI Assistant backend is open source and has been independently audited, with results available through our trust center.