Put runtime limits around your Python agents.
AgentGuard checks budgets, repeated tool calls, retries, and elapsed time in instrumented Python code. Handle its exceptions to stop the next operation. No account, API key, or dashboard required for the first proof.
pip install agentguard47
Watch a runaway coding agent get stopped.
A stuck agent loops and burns budget at 3 AM. AgentGuard47 trips the budget and loop guards locally and writes the trace — no account, no dashboard, no network.
See a guard stop the next operation.
The homepage points non-signup users at a concrete local sequence they can copy into a clean Python environment and inspect without talking to us.
agentguard doctor
agentguard demo
agentguard quickstart --framework raw --write
Four failure modes, one small SDK.
Budget burn
Set call, token, or dollar ceilings before a coding agent turns a bad loop into a bill.
Tool loops
Stop repeated tool calls and repeated argument paths while the run is still live.
Retry storms
Cap retry attempts when a tool, provider, or repo step keeps failing the same way.
Timeout drift
Make long-running agent work fail clearly instead of hanging until the operator notices.
Start local. Add hosted control only when the work becomes shared.
Best first action
Run `doctor`, `demo`, and a generated quickstart file locally.
No account, no dashboard, no network requirement.
When it matters
Use retained incidents, alerts, team visibility, and remote kill.
Useful after a workflow has real runs worth operating.
Boundary
AgentGuard47 focuses on runtime enforcement and incident control.
It is not prompt management, eval orchestration, or a trace warehouse.
The real integration is small.
Plain Python
import agentguard
tracer = agentguard.init(
service="repo-coder",
budget_usd=5.00,
trace_file="traces.jsonl",
local_only=True,
)
with tracer.trace("agent.run") as span:
span.event("tool.call", data={"tool": "edit"})
After local proof
Open the quickstart for OpenAI, Anthropic, LangChain, LangGraph, CrewAI, or raw Python. Then connect the hosted dashboard only when the trace needs to be retained or shared.
Run the local proof. Keep the dashboard optional.
Run doctor and the offline demo, then add guards to the Python calls you control. Guards do not cancel in-flight provider requests or automatically protect every action in Claude Code or Cursor. The MCP server provides read-only visibility into retained traces.
Tried the demo? Run agentguard demo --feedback, inspect the local report,
then share a first-run result if you choose.
The form is public. Do not include traces, prompts, paths, or secrets.