[Molecule-Platform-Evolvement-Manager] PR #59 (commitdae42e2) was merged ~2 weeks ago with a bad diff that deleted all Next.js/Fumadocs build files (package.json, app/, lib/, source.config.ts, tsconfig.json, etc.) and most MDX content pages. This broke the Vercel build, taking doc.moleculesai.app offline. Root cause: the PR branch was likely rebased or reset to a state that only contained the marketing/ subtree, so the merge diff showed deletions for every other file. This commit: 1. Restores all build infrastructure from the last good commit (86fa0e9) 2. Restores 25 deleted MDX content pages (concepts, quickstart, etc.) 3. Adds frontmatter (title) to 55 .md files added post-bad-merge that were missing the required YAML frontmatter for Fumadocs 4. Removes duplicate quickstart.mdx (superseded by quickstart.md) 5. Adds CI workflow (.github/workflows/ci.yml) to catch build failures on PRs before merge — this would have prevented the outage Build verified: 99 static pages generated successfully. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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| Running a Gemini CLI Workspace on Molecule AI |
Running a Gemini CLI Workspace on Molecule AI
Molecule AI now ships a gemini-cli runtime adapter alongside the existing claude-code adapter. This tutorial walks you from zero to a running Gemini agent workspace in under five minutes.
What you'll need
- A Molecule AI account with at least one provisioned tenant
- A Google
GEMINI_API_KEY(get one at aistudio.google.com) - The Molecule AI CLI (
pip install molecule-ai)
Setup (10 steps)
# 1. Install / upgrade the CLI
pip install --upgrade molecule-ai
# 2. Authenticate
molecule auth login
# 3. Store your Gemini API key as a global secret
molecule secrets set GEMINI_API_KEY="YOUR_KEY_HERE" --global
# 4. Create a gemini-cli workspace
molecule workspace create my-gemini-agent --runtime gemini-cli
# 5. Confirm it's running (status → "ready" within ~30 s)
molecule workspace status my-gemini-agent
# 6. Send your first task
molecule workspace run my-gemini-agent "Summarise the last 5 git commits in this repo"
# 7. View the streamed response
molecule workspace logs my-gemini-agent --follow
# 8. Check the agent's memory file (GEMINI.md)
molecule workspace exec my-gemini-agent cat GEMINI.md
# 9. Delegate a cross-workspace task to your new Gemini peer
molecule workspace run orchestrator "delegate_task my-gemini-agent 'Draft release notes for v1.4'"
# 10. Tear down when done
molecule workspace delete my-gemini-agent
Expected output
After step 5 you should see:
my-gemini-agent gemini-cli ready ord 2026-04-16T06:30:00Z
After step 6, Gemini CLI streams its reasoning and final answer directly to stdout. The agent uses GEMINI.md (seeded from your workspace's system-prompt.md) as persistent context — equivalent to CLAUDE.md for Claude Code workspaces.
How it works
Molecule AI's gemini-cli adapter mirrors the battle-tested claude-code pattern: a Docker image installs @google/gemini-cli globally, and CLIAgentExecutor drives the subprocess. Because Gemini CLI reads MCP config from ~/.gemini/settings.json rather than accepting a --mcp-config flag, the adapter's setup() method merges the A2A MCP server definition into that file at boot — preserving any user-defined tools.
Multi-provider teams
The real power surfaces when you mix runtimes on the same Molecule AI tenant. Your orchestrator workspace can delegate tasks to both claude-code and gemini-cli workers simultaneously using delegate_task_async, then synthesize results — all through the same A2A protocol. This is provider diversity at the infrastructure layer, not at the application layer.