focxle — what your AI agents cost

focxle

See what every AI agent costs you, across every vendor. In one line, with no account, in under a second.

Nothing you already have can tell you what one agent cost. Your OpenAI dashboard cannot see Anthropic. Neither can see Serper, Firecrawl, or the twelve other APIs your agent calls in a loop at 3am. They all report per key and per month, which is the wrong unit twice over: you do not run a key, you run agents, and by the time the month closes the money is gone.

focxle runs inside your process, so it sees every one of them, attributes them to the agent that made the call, and prices them from the vendor's own token counts rather than a guess. Connect an account and payments your agent settles on-chain land in the same total.

Why the number gets large fast. Do the arithmetic on a stuck agent. Two frontier-model calls a second, 10k tokens in and 1k out, at $5 per million in and $25 per million out, is 7.5 cents a call and $540 an hour. Twelve hours overnight is $6,480. A two-day weekend is $25,900. Nobody budgets for this, because nobody plans it: it is a bad stopping condition, one retry wrapper too many, a tool that feeds its own output back into the prompt. The first anyone hears is the invoice.

That is the entire reason this exists. It is free, forever, to watch it happen and to see exactly what a cap would have stopped before you pay for one.

This library fails open. It runs inside your agent, so the worst thing it could do is break a request it was only supposed to measure. If anything inside it fails, your call goes through and the failure is counted and printed at the end. focxle.init(fail_open=False) inverts that if an unmeasured call is genuinely worse for you than a failed one.

It blocks nothing by default. Out of the box it only measures. Refusing a call needs an account on a paid plan, and even then the instruction comes from a signed document rather than a local setting, so nothing you or we write in code can quietly switch it on. Calls to vendors we cannot price are always allowed through.

pip install focxle

import focxlefocxle.init()

That is the whole setup. No account, no API key, no config file, and no network call. Prices ship with the package, so the first run works on a plane. Telemetry is off unless you turn it on, and we ask exactly once.

What you get

  focxle spend                                          $47.21  --------------------------------------------------------  support-triage                          $31.04  (1,284 calls)      anthropic                                         $28.10      google.serper.dev                                  $2.94  research                                $16.17  (203 calls)      openai                                            $14.02      api.firecrawl.dev                                  $2.15
  3 calls would have been stopped under $1.50/call and $50/day  $12.30 prevented, worst single call $4.10      3x  single call $4.10 over the $1.50 per-call limit  $5,904 a month at the rate this run was going  $412.60 prevented across 17 runs in 9 days  observe mode: nothing was actually blocked
  prices dated 2026-08-05
  turn these into real caps: https://focxle.com/upgrade

The second block is the point. It is what a cap would have done, evaluated by the same code that would do the blocking, printed so you can decide whether you want one before you pay for one.

Every figure there is a measurement, not a sales number. The total, the worst call and the running total are sums of calls that really happened, priced from the vendor's own usage numbers. The monthly figure is the only projection, it is this run's own measured rate carried forward, it says so on the line itself, and it is withheld entirely unless the run was long enough and busy enough to mean anything.

If a cap would have stopped a large share of your calls, it says that instead of quoting a figure. A cap that blocks a quarter of an agent's work is not saving money, it is stopping the agent, and calling the difference a saving would make the number worthless on the day it matters. Nothing is offered for sale on those runs either.

Why there is nothing else quite like this

Cost tools for AI fall into three shapes, and all three ask you for something before they tell you anything.

Vendor dashboards are per key and per month, one per vendor, and none of them can see the others. Four vendors means four tabs and no total.

Proxies and gateways see everything, because every call now goes through somebody else's server. That is a new dependency on your live path, a new company holding your prompts, and a new thing that can be down at 3am.

Observability platforms want a trace pipeline, an account, and a seat or per-trace bill before the first number appears. Several are excellent. All of them are a project, and none of them is something you do at 4pm because you got a surprising invoice at lunchtime.

focxle is pip install focxle and one line. It has zero dependencies, so nothing enters your environment and nothing can conflict with your pins. It makes zero network calls on the free path, which the test suite proves by deleting socket.socket and running the whole suite anyway. It needs no account, no key and no config file, and the price table ships inside the package, so the first run works on a plane. It fails open by construction: the worst thing a bug in here can do is fail to measure a call that still went through.

And it answers the question none of the others can: what did this agent cost me, across everything it touched.

Attributing spend to an agent

Per agent is the number nobody else can show you, and it only exists if calls are labelled.

with focxle.agent("support-triage"):    result = my_agent.run(ticket)

Works across threads and async tasks. Or set FOCXLE_AGENT in the environment, which is usually right, because the same image is normally deployed as several different agents.

Exact token counts

The HTTP layer already sees your model calls. Wrapping the client upgrades them from "a request happened" to the vendor's own token counts.

from openai import OpenAIclient = focxle.watch(OpenAI())

Streaming is handled. Wrapping the same client twice is a no-op rather than a double count.

For LangChain, where the framework builds the client for you:

chain.invoke(x, config={"callbacks": [focxle.langchain_handler()]})

Ask it in your editor

focxle ships an MCP server, so you can ask about your own spend in Claude Code, Cursor, Windsurf, Zed or anything else that speaks MCP:

what did my agents cost this week which agent is the expensive one what would a $2 per call cap have stopped

Add this to your client's MCP config:

{  "mcpServers": {    "focxle": { "command": "python", "args": ["-m", "focxle", "mcp"] }  }}

It answers from a small daily rollup kept in ~/.focxle/history.json, written when an instrumented process exits. It reads that file and nothing else: no network, no account, and it never starts measuring anything itself, so your editor's own model calls are never counted as yours. FOCXLE_NO_HISTORY=1 turns the rollup off, and then there is nothing to ask about.

Reading the numbers yourself

focxle.spend()                      # total USD observedfocxle.spend("support-triage")      # for one agentfocxle.counterfactual()             # what a cap would have stoppedfocxle.report()                     # print now instead of at exitfocxle.init(file="~/spend.jsonl")   # one JSON object per call

What it does not do

It does not block anything on its own. With no account, policy evaluation runs and the verdict is only recorded, so you see what a cap would have done before you decide you want one. Policy(mode="enforce") written in your own code is refused and downgraded to observe, with a note on stderr: enforcement is something an account is granted, not a flag a process sets for itself.

When it is granted, caps are judged on what you have actually spent, not on a guess at what a call is about to cost. Output length cannot be known before the reply is written, so guessing it refuses ordinary work and misses the runaways. The one exception is the per-call ceiling, which has to be decided in advance: it prices the max_tokens you asked for, so set it above what your largest declared reply would cost rather than above what calls typically cost.

It does not price everything. A vendor missing from the price table is recorded at zero, and both the host and the exact model id are named in the report, so a zero that means "free" is never confused with a zero that means "we did not recognise this". The call is allowed through. Blocking a call because we do not know what it costs would be this library making a decision on missing information inside a process that trusted it to be passive. An invented figure would be worse, because it looks like knowledge.

Routers are priced as the provider they name, so a call through OpenRouter to anthropic/claude-haiku-4.5 costs what that model costs. Dots and dashes in a version are treated as one spelling, because which one you see depends on whose SDK produced the string.

It is per process. An agent running across fifty workers produces fifty partial pictures. Reconciling them needs somewhere to send them, which is what an account is for. The one exception is the running total of what a cap would have prevented, which is kept in ~/.focxle/lifetime.json so a second run does not start from zero. It holds two numbers and a date, never leaves your machine, and FOCXLE_NO_LIFETIME=1 stops it being written at all.

Everything under ~/.focxle is created for your user only, 0700 on the directory and 0600 on the files, the way ~/.ssh and ~/.aws/credentials are. Your account id is a credential: whoever reads it can read that account's spend and start a checkout against it, and agent workloads run on shared CI runners constantly. Anything an earlier version left world readable is tightened the next time it is written.

It has no dependencies. Nothing is added to your environment and nothing can conflict with your versions. The SDKs and frameworks it instruments are detected at runtime and never imported at install time.

What is sent anywhere

Nothing, unless you turn it on. There is no network call on the observe path at all, which the test suite asserts by removing socket.socket and running anyway.

There is exactly one thing we ask for, printed once after your first breakdown and never again. It is off until you type a command:

python -m focxle share preview   # the exact JSON, before you decidepython -m focxle share onpython -m focxle share off

If you turn it on, it sends anonymous vendor totals: which vendors you used, how many calls, how much, and the hosts we could not price. That last one is the whole reason we ask, because it is how we know what to price next.

It never sends your agent names, your model names, prompts, responses, URLs or anything derived from your machine. The install id is a random UUID generated locally, not a hash of your hostname, because anything derived can be reversed by whoever holds the same input. Private hosts (.internal, .corp, bare names, IP addresses) are dropped from every field and counted under withheld, so the totals are visibly partial rather than quietly so.

It never prompts. This runs at process exit, often with no terminal attached, and blocking on stdin there would hang a production agent.

If you enable the local file sink, it records the host and the first two segments of the path, never query strings, so your search terms and document ids stay out of it. That file never leaves your machine.

Compatibility

Python 3.9 and up. Instruments openai, anthropic, httpx, requests and LangChain when they are present, and does nothing when they are not.

Source, issues and contributions

The source is published at github.com/focxle/focxle-python so you can read it before running it inside your agent. It is generated from a private build repository and is source only: the test suite lives there and is not mirrored here, because those files have never been through the checks that decide what is safe to publish.

Because the repo is generated, pull requests cannot be merged back and are not accepted. That is a limitation of how this is built, not a comment on your patch. What is genuinely wanted, and acted on:

• Bugs and feature requests — open an issue, or email [email protected].
• A vendor or model we price wrongly, or do not price at all. The report names them, and that list is the single most useful thing you can send us.
• Security findings — use GitHub's private vulnerability reporting on that repo, or email the address above. Please give us a reasonable window before publishing.

Licence

MIT.