How data is stored
TMA1 stores traces and conversation logs on your local disk in ~/.tma1/data/. Nothing is uploaded to remote services, and you can inspect or delete the data at any time.
TMA1
Know what your agent is doing and what it costs
Tokens, cost, latency — every LLM call, recorded locally. Click a spike to see which conversation is burning money.
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AGENT ONBOARDING
Read https://tma1.ai/SKILL.md and follow the instructions to install and configure TMA1 for your AI agent
Manual install
$ curl -fsSL https://tma1.ai/install.sh | bash
> irm https://tma1.ai/install.ps1 | iex
localhost:14318
See what happened
An agent ran for 20 minutes. What did it do? Open the dashboard, click a trace, read the full conversation.
Catch the expensive calls
That $40 session last Tuesday — was it one huge context window or a runaway retry loop? Now you know.
Nothing leaves your machine
Your agent sees your codebase, your env vars, your keys. That data stays in ~/.tma1/, never uploaded anywhere.
Features
Observability without the overhead
Four dedicated views — Claude Code, Codex, OpenClaw, and OTel GenAI — auto-detected from your data. No Grafana, no cloud, no YAML.
01
Cost breakdown
Which model costs the most? Which conversation burned through your budget? Token counts and estimated cost per model, with burn-rate projections and cache efficiency analysis.
localhost:14318
02
Session replay
Your agent ran for 25 minutes across 4 turns. What happened? Drill into any session to see every API call, tool decision, and result — with model, tokens, cost, and latency per event.
localhost:14318
03
Tool analytics
When your agent feels slow, is it the model or the tool calls? p50 and p95 latency percentiles per tool, with call counts, success rates, and trend charts over time.
localhost:14318
04
Security monitoring
Your agent can run shell commands, fetch URLs, and be fed injected prompts. TMA1 flags all of it. Tracks webhook errors, stuck sessions, and channel health for OpenClaw.
localhost:14318
05
Conversation replay
Your agent just edited 15 files. What was it thinking? Click a trace to read the full dialogue — handy for debugging or auditing what your agent did.
localhost:14318
06
Anomaly detection
An agent stuck in a retry loop can burn hundreds of dollars. TMA1 flags unusual token counts, high error rates, and slow responses before costs pile up.
localhost:14318
07
Full-text search
Search everything. Find a specific model, trace an error back to a call, or filter by tool name.
How it works
Setup
Paste the onboarding instruction into your agent and it handles the rest. Or do it yourself:
[1]
Install
One command. Downloads everything into ~/.tma1/. No Docker, no system packages.
[2]
Configure your agent
Point the OTel endpoint to http://localhost:14318/v1/otlp. Works with Claude Code, Codex, OpenClaw, or any OTel SDK.
[3]
Open the dashboard
Browse to localhost:14318. Traces show up seconds after your agent’s next LLM call.
Security
Security & Privacy
Your agent reads your codebase, your API keys, your infrastructure. Sending that to a cloud observability service defeats the purpose. Everything stays local.
No network calls
After first launch (which downloads the embedded database engine once), TMA1 makes no further network calls. No analytics, no crash reports, no update checks.
Fully open source
TMA1 is Apache-2.0. Read the code, audit the build, and run it air-gapped.
Single binary
tma1-server runs as one local process and manages its embedded storage engine. No Docker, no system packages, no runtime dependencies.
Your data, your disk
Delete ~/.tma1/ and everything is gone. No orphaned cloud state, no remote accounts to close.
FAQ
Common questions
Which agents are supported?
Any agent that emits OpenTelemetry data. Claude Code sends metrics and logs. Codex sends logs and traces, and can also emit native metrics when otel.metrics_exporter is configured. OpenClaw sends traces and metrics. Any OTel SDK app with GenAI semantic conventions works out of the box. The dashboard auto-detects the data source and shows the right view.
Can I query the data with SQL?
Yes. Run mysql -h 127.0.0.1 -P 14002 to connect to the local SQL endpoint, or open localhost:14000/dashboard/ for the built-in query UI. Raw traces are in opentelemetry_traces, logs in opentelemetry_logs, and native metric tables are auto-created from incoming OTel metrics.
How much disk space does it use?
It depends on traffic and conversation length. A typical setup uses a few hundred MB per month.
Quick start
Try it now
Paste this into your agent. It reads the skill file and handles the rest.
AGENT ONBOARDING
Read https://tma1.ai/SKILL.md and follow the instructions to install and configure TMA1 for your AI agent
Or install manually
$ curl -fsSL https://tma1.ai/install.sh | bash
> irm https://tma1.ai/install.ps1 | iex
$ tma1-server
$ openclaw config set diagnostics.otel.endpoint http://localhost:14318/v1/otlp
$ export OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:14318/v1/otlp
$ open http://localhost:14318