Agents

Agents on the pipe

Mechanical agent traffic through one OpenAI-compatible pipe with BYOK and zero-token replay.

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Run agent fleets through a single OpenAI-compatible base URL. Keep BYOK. Turn identical tool loops and retries into zero-upstream-token HITs — and close every session with a signed receipt you can show finance, or Legal, without asking anyone to trust you.

Summary

  • One contract — Shell, MCP, SDK, Cursor: same /v1/chat/completions shape.
  • Zero-token replay — Exact matches HIT Redis; labs are not re-billed for the completion.
  • Session receipts — Every call in a run, tagged with one session id, aggregates into a single signed record.
  • Tree isolation — Give each agent or session class a cache tree when shared main is too coarse.
  • Governed browse — Compliant public-web fetch on the pipeline side, not shadow scrapers.
  • Ledger — Path tags and org export for FinOps.

Why agents need a black box (not another model)

Agents multiply identical work: retries, evaluator loops, CI prompt packs. Bigger context windows do not remove that waste. But an unattended agent also multiplies a harder problem — nobody watched it run, so "what did it actually call, and what did it cost" has no answer except the agent's own transcript. Metrecept is the pipe on repeated inference and the recorder on the session — not a competing lab, and not a governor that tries to stop the agent mid-flight.

Anti-pattern: every agent talks to labs bare

  • No HIT inventory → every retry pays prefill again
  • No session record → an incident review has nothing but logs someone has to trust
  • No org ledger → shadow AI spend
  • No shared inventory hygiene → preview pollution on main

How Metrecept wins

  1. Point the agent runtime at api.withohm.dev/v1 with BYOK headers.
  2. Tag X-Ohm-Path for cost centers; optional X-Ohm-Cache-Tree per fleet; optional X-Ohm-Session to scope a run.
  3. Read /v1/usage and signed receipts on HITs — or pull one aggregated, signed receipt for the whole session from GET /v1/sessions/{id}.

Trust fence

Replay inventory is never a training corpus. Prove the loop: Waste demo. Prove the session: Session demo.

Next

The black box · Product: Pipe · Quickstart · Cursor / MCP · Start — $0 seat

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