Render Reference

Ask your coding agent to run /create-agent, or do it by hand. Create agents/my_agent.py:

from agno.agent import Agent

from app.learning import shared_learning
from app.settings import default_model
from db import get_postgres_db

INSTRUCTIONS = """\
What the agent does, which tools it uses, the rules to follow when answering.
"""

my_agent = Agent(
    id="my-agent",
    name="My Agent",
    user_id="anonymous-user",  # Local fallback; authenticated runs supply identity.
    model=default_model(),
    db=get_postgres_db(),
    instructions=INSTRUCTIONS,
    learning=shared_learning,
    add_datetime_to_context=True,
    add_history_to_context=True,
    num_history_runs=5,
)

The fallback user ID lets local anonymous calls use the shared learning machine; those calls share one profile. Authenticated run identity overrides this default.

Import it in app/main.py and update the agents argument in the existing AgentOS call. Keep its other arguments, including teams, workflows, knowledge, and registry:

from agents.my_agent import my_agent

agent_os = AgentOS(
    # Keep the other arguments from the existing call.
    agents=[platform_builder, platform_manager, platform_engineer, my_agent],
)

Add its UI metadata beneath the existing manifest: key in app/config.yaml:

  my-agent:
    description: "What the agent does."
    quick_prompts:
      - "First example prompt"
      - "Second example prompt"
      - "Third example prompt"

Local containers reload Python source changes. After editing app/config.yaml, run docker compose restart agentos-api to reload the manifest. For production, commit and push; Render rebuilds automatically.

app/settings.py defines default_model(), used by every agent. Change it in one place:

from agno.models.anthropic import Claude

def default_model():
    return Claude(id="claude-sonnet-5")

Add anthropic to pyproject.toml, set the provider key in your env, and regenerate pins:

./scripts/generate_requirements.sh

Rebuild locally with docker compose up -d --build. For production, commit the Python, pyproject.toml, and regenerated requirements changes, then sync the env and push the commit:

./scripts/render/env-sync.sh
git push

Agno ships 100+ toolkits. See Toolkits.

from agno.tools.slack import SlackTools

my_agent = Agent(
    # Keep the agent’s existing configuration.
    tools=[SlackTools()],
)

1. Edit pyproject.toml.
2. Regenerate pins: ./scripts/generate_requirements.sh (add upgrade to refresh every pin).
3. Rebuild locally with docker compose up -d --build, or commit and push to redeploy.

Set both variables in your env file:

SLACK_BOT_TOKEN=xoxb-...
SLACK_SIGNING_SECRET=...

Sync with ./scripts/render/env-sync.sh. The interface activates automatically and routes messages to the Agno team. Change team= in app/main.py to select another team, or replace it with agent=my_agent to route to an agent. See Slack setup.

The deployment check runs daily by default (ENABLE_DEPLOY_CHECK=True); it uses fixed checks without model calls. The run-evals schedule is always registered but starts disabled because it uses model calls. Enable it from the AgentOS UI. Both workflows remain runnable on demand. Startup reapplies ENABLE_DEPLOY_CHECK to the deployment-check schedule; the enabled state of an existing run-evals schedule is preserved.

Expected before the first Blueprint launch. Open dashboard.render.com → New + → Blueprint, connect your copy of the repo, and apply. The script prints these steps and polls every 15 seconds for up to 30 minutes, so you can leave it running while you launch.

Create one in the dashboard under Account Settings → API Keys, then export it or add it to .env.production. The scripts read it from either place.

Expected. At os.agno.com, choose Connect OS → Live, enter your onrender.com URL, name it Live AgentOS, turn on Token-Based Authorization (JWT) on the connection panel, and connect. The UI generates the public key. If the OS is already connected, enable the setting under Settings → OS & Security. Paste the full PEM into the script prompt. To add a PEM later, set JWT_VERIFICATION_KEY and run ./scripts/render/env-sync.sh. To use JWKS, commit and push the file into the image build context, or configure a mount. Set JWT_JWKS_FILE to its container path, then let auto-deploy rebuild or roll the service. Env sync alone only updates the path.

JWT scope enforcement is on whenever RUNTIME_ENV is not dev. Set JWT_VERIFICATION_KEY and sync. For JWKS, verify the file exists inside the container at JWT_JWKS_FILE; changing the variable alone does not deliver it. To disable JWT inside a private VPC behind another auth layer, set authorization=False in app/main.py and remove both JWT environment variables from the Render service. MCP OAuth remains active when MCP_CONNECT_SECRET is set.

Render builds the pushed branch, so local uncommitted changes stay on your machine. Commit, push to your deploy branch, and let autoDeploy rebuild. redeploy.sh warns when it finds uncommitted changes.

Check that the schedule is enabled, the scheduler is running, and its request URL is reachable from the container. Inspect application logs for request or authentication failures. The default loopback URL reaches the app on port 8000. For hosted MCP OAuth, set a public AGENTOS_URL and run ./scripts/render/env-sync.sh.

The service is likely on the free plan, which sleeps between requests; the in-process scheduler and MCP streams stop when it does. Set plan: starter (or higher) in render.yaml and push.