lookspan

Local-first observability dashboard for AI agents. MCP-native. One command.

npx lookspan          # → http://127.0.0.1:3100

Lookspan ingests spans/traces from your agents into a local SQLite database and shows them in a real-time dashboard — traces, costs, latency stats and alerts. Everything runs on your machine; data never leaves it; infra cost is zero.

Send data

Any language, via HTTP:

curl -X POST http://127.0.0.1:3100/api/ingest \
  -H "Content-Type: application/json" \
  -d '{"spans":[{"traceId":"t1","spanId":"s1","parentSpanId":null,"type":"llm_call","name":"agent.run","startedAt":"2026-06-02T10:00:00Z","endedAt":"2026-06-02T10:00:01Z","status":"ok","framework":"custom","model":"gpt-4o","provider":"openai","usage":{"inputTokens":1000,"outputTokens":500,"costUsd":0}}]}'

• MCP / TypeScript: npm i @lookspan/mcp — wrap any MCP client.
• Python (LangGraph, CrewAI, generic): pip install lookspan.
• OpenTelemetry: point OTEL_EXPORTER_OTLP_TRACES_ENDPOINT=http://127.0.0.1:3100/v1/traces — no Lookspan SDK needed.

Options

npx lookspan [options]
  -p, --port <port>        default 3100
      --host <host>        default 127.0.0.1
      --db <path>          default ~/.lookspan/lookspan.db
      --retention <dur>    prune traces older than e.g. 7d, 24h
      --token <token>      require Authorization: Bearer <token>
      --pricing <file>     custom model pricing table (JSON)
      --alert-error | --alert-cost <usd> | --alert-tokens <n> | --alert-duration <ms>
      --open               open the dashboard in your browser

MIT · github.com/JoniMartin27/lookspan