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  3. Focxle β€” what your AI agents cost
Focxle β€” what your AI agents cost logo
Health: ActiveRecent health check succeeded.Last checked 9/21/2026, 11:46:18 PM

Focxle β€” what your AI agents cost

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time β€” check back soon.
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What your AI agents cost, across every vendor and HTTP API. Local only, no account, no network.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "focxle-what-your-ai-agents-cost": {
      "command": "uvx",
      "args": [
        "focxle"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing AlternativesπŸ’» More in Developer Tools

Documentation Overview

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.

Terminal
pip install focxle
server.ts
import focxle
focxle.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

Code
  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.

python
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.

server.ts
from openai import OpenAI
client = 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:

python
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:

config.json
{
  "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

python
focxle.spend()                      # total USD observed
focxle.spend("support-triage")      # for one agent
focxle.counterfactual()             # what a cap would have stopped
focxle.report()                     # print now instead of at exit
focxle.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.

Read the full README β†’View source on GitHub β†’

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Frequently Asked Questions about Focxle β€” what your AI agents cost

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "focxle-what-your-ai-agents-cost": { "command": "uvx", "args": ["focxle"] } }

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Technical Specs & Signals

CategoryπŸ’»Developer Tools
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimePython
Last updatedAug 10, 2026
12/12 checks healthy over the last 43d
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Last commit1mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Aug 10, 2026
37Quality signal: Fair Β· 37/100How this signal is calculated β–Ύ
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Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools16/30
Adoption & activity2/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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Scanned 3d ago via OSV.dev Β· focxle (PyPI)

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