Catoms gives every AI feature in your app its own managed harness.
Set it up and change it from your coding agent, over MCP.
Works with Claude Code, Cursor, Codex, any MCP client
✻ Welcome to Claude Code!
cwd: ~/notes-app
> create a research harness for the @agent feature, add web search, and fail the build if citation accuracy drops below 90%
⏺I’ll set up a Catoms harness for the @agent research feature.
⏺catoms - create_harness (MCP)(name: "notes-research", tools: ["web_search", "retrieve"], guardrails: ["prompt_injection"])
⎿Created notes-research v1. Models: your keys, routed by quality, with fallback.
⏺catoms - add_eval (MCP)(harness: "notes-research", suite: "citation-accuracy", fail_below: 0.9)
⎿First run: 23 of 24 passing. Citation accuracy 0.94.
⏺The harness is live. Call it from the notes app:
POST https://api.catoms.dev/v1/notes-research/stream
Calling a model takes an afternoon. Shipping the feature takes a harness: the prompts, tools, memory, guardrails and evals around the model, and the loop that improves them. Every AI feature needs its own, and most product teams don’t have a platform team to build them.
Catoms runs the harness for you, one per feature. You describe it to your coding agent and get back an endpoint.
Catoms harness, one per feature
traced → evals
What we do
A harness for each feature.
A versioned endpoint with streaming, prompts you can roll back, tools, memory, guardrails and evals. Search, summaries and your @agent each get their own.
Run from your coding agent.
Every console action is also an MCP tool. Create, test and change harnesses from Claude Code, Cursor or Codex in plain words.
It improves. You approve.
When eval scores drop, Catoms finds out why and drafts a fix. Nothing reaches production until you say yes.
- Evals runevery change, live traces
- Fix draftedprompt, tool or model
- You approvein your coding agent
- New versionroll back in one call
Pricing
Free
001$0
- 2 harnesses
- A monthly allowance of runs
- Bring your own model keys
- Control everything from your coding agent
Teams and companies
002Let’s talk
- As many harnesses as you have features
- Higher limits and priority support
- SSO and audit logs
- Run Catoms in your own cloud
Get early access
We’re letting product teams in a few at a time so we can help each one set up. Tell us what you want to build.
You're on the list.
We'll write to you when your spot opens. We're letting people in a few teams at a time so we can help each one set up properly.
One favor while you wait: our survey takes about five minutes and asks how you build AI features today. Your answers decide what we build first, and people who answer get in sooner.