Inferrail MCP server

Inferrail

<!-- mcp-name: io.github.domondi1/inferrail -->

Decide, execute, and record AP invoice-exception recovery.

For one eligible invoice-extraction exception, Inferrail decides whether it gets one permitted machine retry or your established human-review path, executes the retry through a supported integration, and records the resulting cost and outcome — with invoice content and provider credentials staying in your own process the whole time.

AP invoice-exception recovery: 30-second demo

pip install inferrail
inferrail ap demo

Fixture-based, zero-key, no network call. Runs the real decision engine through all five core scenarios — an eligible exception recovered by one retry, an unsuccessful retry that falls back to human review, a case the policy routes straight to human review, a repeated request handled without re-executing anything, and inspecting the resulting decision/outcome records — then points you at inferrail ap report to inspect them yourself.

Want a real (billed) OpenAI call instead of fixtures, or to see how you'd wire in your own extraction pipeline and review queue? See examples/apinvoiceexception_recovery/. Full contract — supported failure types, retry method, validation contract, human-review handoff, versioned policy config, persistence/idempotency, the hosted HTTP API — in docs/capabilities/ap-invoice-exception-recovery.md.

No claim of proven savings or customer adoption is made anywhere in this README — see that capability doc's "Pricing and performance assumptions," which labels every dollar figure as an explicit assumption, not a validated result.

Also in this package: the self-hosted LLM gateway and cost receipts

Everything below this point is Inferrail's original, still fully-supported product: a self-hosted gateway that turns supported OpenAI chat-completion traffic into local, attributable economic receipts — the same receipt/cost substrate the AP product's OpenAIRetryAdapter and reporting build on. It remains available and unchanged; nothing about the AP release modifies its behavior or its commands.

Inferrail turns supported OpenAI chat-completion traffic into local, attributable economic receipts. Give related requests a customer-defined work_id, declare an outcome when your application knows one, and inspect the known inference economics associated with that work without storing prompts, responses, or tool payloads in Inferrail's own records.

For the supported chat-completions surface, Inferrail records known cost when measured usage and a verified price are available. Otherwise it reports unknown, never a fabricated $0.

Gateway: 30-second demo

pip install inferrail
inferrail demo

The demo needs no API key, no network call, and no provider billing. It runs canned requests through Inferrail's real engine with made-up prices labeled DEMO, then shows receipts, attribution, work-level economics, and explicit unknown evidence.

As of 0.2.0, the stable PyPI release includes the gateway, receipts, reports, TaskTransaction, and work commands (Work Economics), alongside AP invoice-exception recovery above.

What just happened?

AI request
  -> InferenceReceipt
  -> caller-supplied attribution
  -> related requests share work_id
  -> customer-declared outcome
  -> Work Economics

Shortened. The full README is on GitHub.