Your AI agent just burned $2,000 in tokens overnight.
AgentGuard stops it at $5.
Stop runaway AI agents before they burn your API budget or leak data.
- • Kill infinite loops
- • Enforce hard dollar caps
- • Track cost per agent
- • Block unsafe actions in real time
Built for teams running AI agents in production:
Latest release
Monthly installs
Detect repeated tool calls across any depth. Automatic circuit breaker fires before costs compound.
Set a budget. Agent stops mid-run when it's hit. No more $2,000 surprise invoices.
See exactly what each run costs, per LLM call. Dollar amounts, not token estimates.
Stop any agent instantly from the dashboard. No redeployment needed.
Patch OpenAI/Anthropic with one call. Costs and traces flow automatically.
Record real runs and replay them for regression tests. No flaky mocks.
Pure Python stdlib. One package, nothing to audit. No supply chain risk.
Docker gave you container scanning.
AgentGuard gives you agent scanning.
CI/CD gate → Runtime enforcement → Compliance trail
Other tools watch your agents fail. AgentGuard stops them.
| Feature | AgentGuard | Langfuse | LangSmith | Helicone |
|---|---|---|---|---|
| Tracing | ✓ | ✓ | ✓ | ✓ |
| Cost tracking | ✓ | ✓ | ✓ | ✓ |
| Budget enforcement | Hard stop mid-run | ✗ | ✗ | Soft alert |
| Loop detection | Auto circuit-breaker | ✗ | ✗ | ✗ |
| Remote kill switch | Instant, no redeploy | ✗ | ✗ | ✗ |
| Auto-intervention | Rule engine on ingest | ✗ | ✗ | ✗ |
| Open source | SDK only | Full (MIT) | ✗ | Gateway |
| Setup | 3 lines | Hours | 30 min | 2 min |
"Can't I just add max_iterations myself?"
You could add a budget check. But can you also detect retry loops across 12 tool calls, auto-kill the agent remotely without redeploying, send a Slack alert with the trace link, log the intervention for compliance, and show your team a dashboard of how much you saved — all in a weekend? That's what AgentGuard does out of the box.
See it in action
Works with every agent framework
How it works
Install the SDK
pip install agentguard47
Add 3 lines
Wrap your agent with Tracer and HttpSink
See traces
Gantt timelines, alerts, and usage in the dashboard
from agentguard47 import Tracer, BudgetGuard from agentguard47.sinks.http import HttpSink from agentguard47.instrument import patch_openai sink = HttpSink(url="https://app.agentguard47.com/api/ingest", api_key="ag_...") tracer = Tracer(sink=sink, service="my-agent") patch_openai(tracer) # auto-tracks cost per call guard = BudgetGuard(max_cost_usd=5.00) # stop at $5 with tracer.trace("agent.run") as span: span.event("reasoning.step", data={"thought": "search docs"}) with span.span("tool.search"): pass # your tool here
Trusted by builders shipping agents to production
Monthly PyPI installs
Pricing
Pro 14-day free trial
- 500,000 events/month
- 30-day retention
- 5 API keys
- 1 user
Security & Trust
No supply chain risk. One pip install, one package to audit.
MIT-licensed. Read every line on GitHub. No vendor lock-in.
TLS 1.3 in transit, AES-256 at rest via Supabase Postgres.
30-90 day auto-cleanup by plan. No indefinite data hoarding.
FAQ
Why zero dependencies?
What data do you store?
Can I self-host?
Does it work with my framework?
Do I need a credit card?
Stop babysitting your agents.
14-day Pro trial. No credit card. 3 lines of code.
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