# Running a Google ADK Workspace on Molecule AI Google's Agent Development Kit (ADK) is now a first-class runtime on Molecule AI. This tutorial walks you from zero to a running ADK agent workspace — one that persists per-conversation session state and sits alongside your Claude Code and Gemini CLI workers in the same A2A network. ## What you'll need - A Molecule AI account with at least one provisioned tenant - A `GOOGLE_API_KEY` from [aistudio.google.com](https://aistudio.google.com) (or Vertex AI credentials — see below) - `curl` + `jq` ## Setup ```bash # 1. Store your Google API key as a global secret curl -s -X PUT http://localhost:8080/settings/secrets \ -H "Content-Type: application/json" \ -d '{"key":"GOOGLE_API_KEY","value":"YOUR-AI-STUDIO-KEY"}' | jq . # 2. Create a google-adk workspace WS=$(curl -s -X POST http://localhost:8080/workspaces \ -H "Content-Type: application/json" \ -d '{ "name": "adk-agent", "role": "Google ADK inference worker", "runtime": "google-adk", "model": "google:gemini-2.0-flash" }' | jq -r '.id') echo "Workspace: $WS" # 3. Wait for ready (~30s) until curl -s http://localhost:8080/workspaces/$WS | jq -r '.status' | grep -q ready; do echo "Waiting..."; sleep 5 done # 4. Send your first task curl -s -X POST http://localhost:8080/workspaces/$WS/a2a \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","id":"1","method":"message/send", "params":{"message":{"role":"user","parts":[{"kind":"text", "text":"Summarise the ADK architecture in 3 bullet points."}]}}}' \ | jq '.result.parts[0].text' # 5. Multi-turn — session state is preserved across calls curl -s -X POST http://localhost:8080/workspaces/$WS/a2a \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","id":"2","method":"message/send", "params":{"message":{"role":"user","parts":[{"kind":"text", "text":"Now give me a one-line TL;DR of what you just said."}]}}}' \ | jq '.result.parts[0].text' # 6. Vertex AI alternative — set these instead of GOOGLE_API_KEY # curl -X PUT .../secrets -d '{"key":"GOOGLE_GENAI_USE_VERTEXAI","value":"1"}' # curl -X PUT .../secrets -d '{"key":"GOOGLE_CLOUD_PROJECT","value":"my-project"}' # curl -X PUT .../secrets -d '{"key":"GOOGLE_CLOUD_LOCATION","value":"us-central1"}' ``` ## Expected output After step 4, ADK streams the Gemini response through its event bus, filters for `is_final_response()` events, and returns the agent's reply as a standard A2A text part. Step 5 should reference the prior answer — the adapter ties each A2A `context_id` to an `InMemorySessionService` session, so conversation state is isolated per task context and survives across calls within the same session. ## How it works The `google-adk` adapter wraps Google ADK's runner/session model behind the same `AgentExecutor` interface used by every other Molecule AI runtime. On each turn, `GoogleADKA2AExecutor` calls `runner.run_async()` with the incoming message wrapped in a `google.genai.types.Content` object, then drains the event stream until it collects a final-response event. The `google:` model prefix is stripped before being passed to ADK — so `google:gemini-2.0-flash` in your workspace config becomes `gemini-2.0-flash` in the ADK `LlmAgent`. Error class names are sanitized before leaving the executor; raw Google SDK stack traces never reach the A2A caller. ## Mixed-runtime teams ADK workspaces participate in the same A2A network as Claude Code, Gemini CLI, Hermes, and LangGraph workers. An orchestrator can delegate long-context summarisation to a `google-adk` worker (Gemini 1.5 Pro's 1M token window) while routing tool-use tasks to a `claude-code` worker — with no provider-specific code in the orchestrator itself. Add an ADK peer with `POST /workspaces`, set `GOOGLE_API_KEY`, and it's available for `delegate_task` immediately. ## Related - PR #550: [feat(adapters): add google-adk runtime adapter](https://git.moleculesai.app/molecule-ai/molecule-core/pull/550) - [Google ADK (adk-python)](https://github.com/google/adk-python) - [Gemini CLI runtime tutorial](./gemini-cli-runtime.md) - [Platform API reference](../api-reference.md)