Make your AI agents make the most of their tokens.
WORKS WITH
Every observability tool is built for LLM developers. TokenJam is built for people whose agents have real-world side effects — and real-world bills.
Coding agents and autonomous workflows run for hours unattended. They edit files, send emails, hit APIs. Without observability, you find out what happened when something breaks — or when the bill arrives.
A Claude Code session can rack up $45 in an hour. Most calls don't need the most expensive model — but without per-task cost attribution, you can't tell which ones do.
Behavioral drift, sensitive-action alerts, eval-to-production correlation — they all require API keys, hosted backends, and credit cards. TokenJam runs on your machine.
tj optimize analyzes your real sessions and flags model-downgrade candidates plus per-provider monthly budget projection. Shipped.
pip install. No signup, no proxy, no SaaS account. Full-featured CLI (tj status / traces / cost / drift) with JSON output. Local REST API + Prometheus /metrics.
The only observability tool built for agents with real-world side effects. Configurable alerts fire on email sends, file writes, form submissions, and payment actions.
unique to TokenJamReal-time USD cost per LLM call, attributed to the agent and tool that triggered it. Configurable daily/session/per-agent budget alerts fire before you get the bill.
per-model pricing TOMLDeterministic, no-cloud drift detection. Automatically baselines token usage, tool call sequences, output schema, and session duration — alerts when agents deviate.
no API key requiredFull GenAI Semantic Conventions compliance from day one. Agent spans, tool calls, token metrics — exportable to Grafana, Jaeger, Datadog, or any OTel backend without transformation.
OTel SemConv v1.37+JSON Schema validation for tool outputs and agent responses. Declare schemas per-agent/tool in config, or use inference mode to auto-derive from observed sessions.
JSON Schema draft-07A full-featured CLI (tj status / traces / cost / drift) with JSON output on every command. Local API at localhost with Prometheus /metrics endpoint, OpenAPI spec included.
pipe-friendly · scriptableMost coding-agent calls don't need the most expensive model. tj optimize analyzes your real sessions and flags model-downgrade candidates plus per-provider monthly budget projection — driven by your actual traces, not generic heuristics. Every recommendation ships with a quality-equivalence caveat, so you decide what to apply.
Works with every major agent runtime
The tools your team already uses are built for LLM developers. TokenJam fills the gap they all leave open.
| Feature | TokenJam | Langfuse | LangSmith | Helicone | Guardrails AI |
|---|---|---|---|---|---|
| Observability | |||||
| OTel GenAI SemConv nativecompliant from day one | ✓ | ~ | ~ | — | — |
| LLM call tracing | ✓ | ✓ | ✓ | ✓ | — |
| Token & cost tracking | ✓ | ✓ | ✓ | ✓ | — |
| Framework agnostic | ✓ | ✓ | — | ✓ | ✓ |
| Autonomous agent safety | |||||
| Sensitive action alertsemail, file write, payment, form submit | ✓ | — | — | — | — |
| Cost budget alertsdaily / session / per-agent | ✓ | — | — | — | — |
| NemoClaw sandbox events | ✓ | — | — | — | — |
| Retry loop detection | ✓ | — | — | — | — |
| Runtime verification | |||||
| Behavioral drift detection | ✓ | — | — | — | — |
| Output schema validation | ✓ | — | — | — | ✓ |
| Token economics | |||||
| Trace-driven cost recommendationsmodel-downgrade candidates + per-provider budget projection | ✓ | — | — | ~ | — |
| Eval-to-production correlationimport Inspect / DeepEval / Promptfoo | ~ | — | ~ | — | — |
| MCP server for agent self-introspection13 MCP tools shipped | ✓ | — | — | — | — |
| Multi-agent fleet aggregationcloud.tokenjam.dev — coming soon | cloud | ~ | ✓ | — | — |
| Developer experience | |||||
| Fully local, no signup | ✓ | ✓ | — | ~ | ✓ |
| CLI interface | ✓ | — | — | — | — |
| OTLP export to any backendGrafana, Jaeger, Datadog… | ✓ | ✓ | — | — | — |
| Open source / self-hostable | ✓ | ✓ | — | ✓ | ✓ |
Connect what graded your agent offline with what it's doing in production. In active development; the OSS roadmap is public.
Ingest results from Inspect AI, DeepEval, Promptfoo, HUD, and Coval. Correlate failed eval cases with matching production sessions. The only OSS layer that connects what graded your agent offline with what it's doing in production.
5 importers planned