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Anaconda Agent Studio is a desktop application for creating, configuring, and running AI agents locally on your machine. You can build agents through a visual interface or by using the built-in Anaconda Assistant, then connect them to external services, your own tools, and the AI models of your choice.

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Installing Agent Studio

Agent Studio is displayed in the left-hand navigation by default. Disable it on the Settings page. If you belong to an organization, your administrator might restrict access to beta features.
  1. In the left-hand navigation, under BETA, select Agent Studio.
  2. On the Agent Studio page, click Download.
  3. Accept the terms of service and privacy policy to enable the download.
  4. Click Download again to begin the installation.
    Download progress displays in the upper-right corner. A notification appears when the download completes.

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Launching Agent Studio

  1. From the Agent Studio page, click Launch.
  2. Click Sign in to authenticate. A browser window opens to complete sign-in with your Anaconda account credentials.

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Capabilities

Agent creation
Create agents from templates or from scratch. Each agent can be configured with a system prompt, Python tools, plugins, MCP servers, skills, and reference documents.
AI model providers
Connect to an AI provider and select from its available models. Agent Studio includes Anaconda’s hosted models by default. You can also add your own API keys from providers like OpenAI, Anthropic, Google, or Groq, or connect to a model running locally in Anaconda Desktop.
Tools, plugins, and MCP servers
Write custom Python tools for your agents, add plugins that bundle integrations for services like Atlassian, GitHub, and Miro, or connect to any MCP server for access to external APIs and services. Every agent is also exposed as an MCP server, so agents can delegate tasks to each other.
Compare chat
Send the same prompt to up to four agents or models simultaneously and compare their responses side by side.
Sandbox isolation
Run agents inside Docker containers to isolate them from your local system. Configure network access, resource limits, and folder mounts per agent.
Safety guardrails
The agent runtime automatically screens messages for PII, prompt injection, and secrets. When a safety filter triggers, the response is blocked and Agent Studio displays a warning in the chat.
File-based configuration
Agent configurations are stored as local files that you can version control with Git or share with teammates.