TraceRoot is an open-source observability platform for AI agents — Capture traces, monitors production issues, and debug with AI that sees your source code and Github history.
Features
| Feature | Description |
|---|---|
| Tracing | Capture LLM calls, agent actions, and tool usage via OpenTelemetry-compatible SDK. Intelligently surfaces the traces that matter — noise filtered, signal prioritized. |
| Agentic Debugging | AI that sees all your traces, connects to a sandbox with your production source code, identifies the exact failing line, and correlates the failure with your GitHub commits, PRs, and issues. BYOK support for any model provider. |
| Detectors | LLM-as-judge evaluator monitors incoming trace for hallucinations, tool/logic failures, safety violations, and intent drift — surfaces findings and auto-triggers root cause analysis with email and slack alerts. |
Why TraceRoot?
-
Traces alone don't scale.
As AI agent systems grow more complex, manually sifting through every trace is unsustainable. TraceRoot's Detectors selectively screen incoming traces — flagging hallucinations, tool failures, logic errors, and safety issues automatically, so you spend time fixing problems, not hunting for them.
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Debugging AI agent systems is painful.
Root-causing failures across agent hallucinations, tool call instabilities, and version changes is hard. TraceRoot's AI connects to a sandbox running your production source code, identifies the exact failing line, and cross-references your GitHub history — commits, PRs, open issues and creates PR to fix it.
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Fully open source, no vendor lock-in.
Both the observability platform and the AI debugging layer are open source. BYOK support for any model provider — OpenAI, Anthropic, Gemini, xAI, DeepSeek, OpenRouter, Kimi, GLM and more.
Documentation
Full documentation available at traceroot.ai/docs.
Getting Started
TraceRoot Cloud
The fastest way to get started. Ample storages and LLM tokens for testing, no credit card needed. Sign up here!
Self-Hosting
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Developer mode: Run TraceRoot locally to contribute.
# Get a copy of the latest repo git clone https://github.com/traceroot-ai/traceroot.git cd traceroot # Hosted the infras in docker and app itself locally make devFor more details, see CONTRIBUTING.md.
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Local docker mode: Run TraceRoot locally to test.
# Get a copy of the latest repo git clone https://github.com/traceroot-ai/traceroot.git cd traceroot # Hosted everything in docker make prod -
Terraform (AWS): Run TraceRoot on k8s with Helm and Terraform. This is for production hosting. Still in experimental stage.
Integrations
Native SDKs
| Language | Repository |
|---|---|
| Python | traceroot-py |
| TypeScript | traceroot-ts |
Agent Frameworks
| Integration | Supports | Description |
|---|---|---|
| Agno | Python | Automated instrumentation of agent runs, tool calls, and multi-step reasoning. |
| AutoGen | Python | Automated instrumentation of multi-agent conversations, agent loops, and tool calls. |
| Claude Agent SDK | Python, JS/TS | Automated instrumentation of agent invocations, subagent delegations, tool calls, and token usage. |
| CrewAI | Python | Automated instrumentation of multi-agent collaborative workflows and task executions. |
| DSPy | Python | Automated instrumentation of module executions, signature predictions, and underlying LLM calls. |
| Google ADK | Python | Automated instrumentation of agent runs, tool executions, and the multi-turn agent loop. |
| LangChain & LangGraph | Python, JS/TS | Automated instrumentation by passing callback handler to LangChain application. |
| LangChain DeepAgents | Python, JS/TS | Automated instrumentation by passing callback handler to DeepAgents pipeline. |
| LlamaIndex | Python | Automated instrumentation of RAG pipelines, document ingestion, retrieval, and LLM synthesis. |
| Mastra | JS/TS | Automated instrumentation via the TraceRoot OTLP exporter. |
| OpenAI Agents SDK | Python, JS/TS | Automated instrumentation of agent runs, tool executions, and handoff transitions. |
| Pydantic AI | Python | Automated instrumentation of agent runs, LLM calls, and tool invocations via pydantic-ai's native OpenTelemetry support. |
| Vercel AI SDK | JS/TS | Native OpenTelemetry tracing via experimental_telemetry — no instrumentModules config required. |
Model Providers
| Integration | Supports | Description |
|---|---|---|
| Anthropic | Python, JS/TS | Automated instrumentation of the Messages API. |
| Google Gemini | Python | Automated instrumentation via the Google GenAI SDK. |
| Mistral | Python | Automated instrumentation of Mistral chat completions, tool calls, and streaming responses. |
| OpenAI | Python, JS/TS | Automated instrumentation of Chat Completions and Responses API. |
Don't see your framework or provider? Request an integration.
Python SDK Quickstart
pip install traceroot openai
import traceroot
from traceroot import Integration, observe
from openai import OpenAI
traceroot.initialize(integrations=[Integration.OPENAI])
client = OpenAI()
@observe(name="my_agent", type="agent")
def my_agent(query: str) -> str:
response = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": query}],
)
return response.choices[0].message.content
if __name__ == "__main__":
my_agent("What's the weather in SF?")
TypeScript SDK Quickstart
npm install @traceroot-ai/traceroot openai
import OpenAI from 'openai';
import { TraceRoot, observe } from '@traceroot-ai/traceroot';
TraceRoot.initialize({ instrumentModules: { openAI: OpenAI } });
const openai = new OpenAI();
const myAgent = observe({ name: 'my_agent', type: 'agent' }, async (query: string) => {
const response = await openai.chat.completions.create({
model: 'gpt-4o',
messages: [{ role: 'user', content: query }],
});
return response.choices[0].message.content;
});
async function main() {
try {
await myAgent("What's the weather in SF?");
} finally {
await TraceRoot.shutdown();
}
}
main().catch(console.error);
Security & Privacy
Your data security and privacy are our top priorities. Learn more in our Security and Privacy documentation.
Community
Special Thanks for pi-mono project, which powers the foundation of our agentic debugging runtime!
Contributing 🤝: If you're interested in contributing, you can check out our guide here. All types of help are appreciated :)
Support 💬: If you need any type of support, we're typically most responsive on our Discord channel, but feel free to email us [email protected] too!
License
This project is licensed under Apache 2.0 with additional Enterprise features.