TokenOps icon

TokenOps

TokenOps is a unit-economics platform for AI companies that attributes LLM spend by customer, reconciles vendor invoices, and surfaces per-customer gross margin. It offers SDK wrappers, MCP tools, and workflow tools for finance and operations teams.

TokenOps

Overview

TokenOps is a unit-economics platform for AI companies that turns LLM usage into per-customer cost and gross-margin data. It captures events at the client layer, reconciles those events against monthly vendor invoices, and shows how spend maps to the customers who incurred it.

The product is positioned for teams that need to answer profitability questions from actual usage rather than spreadsheet exports. It supports one-line wrappers for major LLM providers, exposes the data through a dashboard, API, and MCP tools, and is offered through an early-access flow with a free trial on real telemetry.

Source examples on the page show customer-level cost, revenue, and margin views, plus workflows for building per-customer P&Ls, reconciling invoices, detecting anomalies, and simulating price changes. The workflow framing suggests TokenOps is aimed at finance, operations, and engineering teams that need recurring visibility into LLM unit economics.

Core capabilities

Client-side attribution

Wrap supported LLM clients with a single line so each call can be attributed to a customer without changing the vendor routing path.

Invoice reconciliation

Capture events, price them against tokens, and reconcile monthly vendor invoices so effective cost can be compared with the invoice total.

Per-customer gross margin

Break down spend, revenue, and margin by customer so teams can see which accounts are profitable and where loss-making usage is concentrated.

MCP access for finance queries

Expose financial data through a 30-tool MCP catalog plus four composite workflow tools for use in Claude Desktop, Cursor, Codex, or other MCP-aware clients.

Structured finance workflows

Use composite workflows for per-customer P&L, invoice reconciliation, anomaly detection, and price-change forecasting.

Multi-SDK and multi-vendor support

Support TypeScript and Python SDK usage, including edge runtimes, with wrappers for Anthropic, OpenAI, Amazon Bedrock, Google AI, Vercel AI, and Azure OpenAI.

Common use cases

  • Customer profitability reporting

    Track which customers are profitable by joining captured LLM usage to customer revenue and margin data for a given period.

  • Vendor invoice reconciliation

    Compare invoice totals with captured events to understand effective rate, drift, and savings across vendors and billing periods.

  • Usage anomaly detection

    Watch per-customer cost run-rate and detect unusual spikes before the monthly invoice arrives.

  • Agent-assisted finance queries

    Use MCP-aware assistants to answer finance questions such as customer margin, loss-making accounts, or cost breakdowns in plain English.

  • Pricing and margin simulations

    Model the impact of new seat-based or usage-based pricing against recent usage to see margin effects and potential churn risk.

Pros and Cons

Pros

  • Attributes LLM spend by customer instead of only at the workspace or vendor level.
  • Reconciles vendor invoices against captured events to surface effective rate and drift.
  • Provides both SDK wrappers and MCP tools, giving teams and agents multiple ways to query the same data.
  • Supports several major LLM providers through one-line wrappers.
  • Includes workflow tools for P&L, reconciliation, anomaly detection, and price-change analysis.

Cons

  • Pricing is not published on the page beyond a trial and plan-sizing note.
  • The page emphasizes early access, so availability may still be limited.

FAQ

What does TokenOps do?

TokenOps captures LLM events at the client layer, attributes spend by customer, reconciles vendor invoices against those events, and exposes the results through the dashboard, API, and MCP tools.

Which LLM providers does it support?

The source shows one-line wrappers for Anthropic, OpenAI, Amazon Bedrock, Google AI, Vercel AI, and Azure OpenAI, with support for TypeScript and Python.

How do you set it up?

You can install the SDK, wrap your LLM client, and pass a customerId on each call. The page says the first event can be seen in under five minutes.

Is there pricing information available?

TokenOps says it offers a 30-day free trial on your real telemetry with no card required. After the trial, it says plans are sized to usage, but no pricing details are published on the page.

Quick Facts

Category
AI finance / developer tool
Primary use
Per-customer LLM cost and gross margin tracking
Access model
Early access with a 30-day free trial and no card required
Integrations
Anthropic, OpenAI, Amazon Bedrock, Google AI, Vercel AI, Azure OpenAI
Interfaces
SDK, dashboard, API, MCP tools
Domain
lovie.co

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