GraphCanon updated Sep 11, 2026 · GitHub synced Sep 11, 2026
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Decision brief
dunetrace is a real-time monitoring tool for AI agents in production that provides insights into observability and reliability, primarily targeting Python and Node.js ecosystems.
Good fit when
- When you need to monitor the performance of AI agents in real-time, as dunetrace offers insights specific to observability and reliability.
- If your project involves Python or Node.js development and requires detailed monitoring of AI agent operations.
Avoid when
- When focusing solely on non-code aspects like UI/UX without any need for backend AI agent observation.
- If you are looking for a platform that supports extensive integrations beyond Python and Node.js, as dunetrace's focus is limited to these environments.
- Pricing:
- unknown - The repository does not specify any pricing information; it only mentions a license which is categorized as 'other'.
- Requirements:
- Requires Docker
Observed Jul 17, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Active (10d since push)
- As of Sep 11, 2026
- Provenance
- Not a fork · Personal account
- As of Sep 11, 2026
- Security (OSV)
- 4 low (4 low)
- As of Jul 15, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install dunetraceSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
A real-time monitoring tool for AI agents that offers observability and reliability insights in Python and Node.js.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Sep 11, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Sep 11, 2026
- Languages
- python
Source: github.language · Sep 11, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Sep 11, 2026)
") # auto-instruments installed clients (OpenAI, Anthropic, Mistral, Bedrock, LangChain, CrewAI, httpx, requests)Source link
Source: README excerpt (regex_v1, Sep 11, 2026)
npm install dunetrace # Node.js / TypeScriptSource link
Source: README excerpt (regex_v1, Sep 11, 2026)
pip install dunetrace # Python npm install dunetrace # Node.js / TypeScriptSource link
Tags
README
Quick Start See the examples index for ready‑to‑run examples. 1. Start the backend 2. Install the SDK 3. Instrument your agent Python TypeScript / Node.js → TypeScript auto instrumentation Try the built in failure scenarios Open the dashboard: http://localhost:3000
For agents
This page has a .md twin and JSON over the API.