focxle MCPサーバー
✓ 検証済みプロセス内でトークン使用量を直接監視することで、複数のベンダーにわたるAIエージェントのコストを追跡・集計します。
別名 focxle/focxle-python, focxle-python, focxle
- スター
- 0
- ツール
- —
- ダウンロード数(30日間)
- 122
- 最新バージョン
- 0.1.7
- 最終コミット
- 2026年8月10日
- ライセンス
- MIT
focxle MCPとは
focxleはMCPサーバーです。 プロセス内でトークン使用量を直接監視することで、複数のベンダーにわたるAIエージェントのコストを追跡・集計します。.
プロジェクトのREADMEから生成された概要
focxle MCP server について
focxleは、単一のプロセス内で複数の異なるベンダーにわたるAIエージェントのコストを追跡し、割り当てを行う手段を提供します。OpenAI、Anthropic、Serperなどの個別のダッシュボードを確認する代わりに、開発者は特定のエージェントに紐づく支出の内訳を統合して確認できます。ベンダー自身のカウントからトークン使用量を直接監視するため、推測やプロキシに頼ることなく正確性を確保できます。
このツールは、アカウント、APIキー、初期ネットワーク通信を必要としないPythonライブラリによるローカル統合を想定して設計されています。fail open設計を採用しているため、計測ツールでエラーが発生しても、エージェントのリクエストは中断されません。Cursor、Windsurf、Claude CodeなどのAI統合エディタを使用している開発者向けに、MCP serverが同梱されており、ローカルのJSONロールアップを使用してチャットインターフェースから直接支出履歴を照会できます。
できること
- 1マルチベンダーのエージェントコストを分析今週エージェントが使用したすべてのAPIプロバイダーにわたる総支出を、AIエディタに計算させます。
- 2高コストなエージェントワークフローの特定現在のAPI利用料金のうち、どの特定のエージェント名が最も高い割合を占めているかを特定します。
- 3コスト削減のための予算制限のシミュレーション特定の呼び出しごとの支出制限を実装していた場合、どれくらいの金額を節約できたかを評価します。
プロジェクトの README から作成されています。すべてのユースケースは、その引用と照らし合わせて確認されています。
focxle MCPのインストール方法
フォーマット検証日 2026年11月10日Cursor に追加Gooseに追加Claude Codeにfocxle MCPをインストール
$ claude mcp add focxle-python -- uvx focxleCursorにfocxle MCPをインストール
~/.cursor/mcp.json
{
"mcpServers": {
"focxle-python": {
"command": "uvx",
"args": [
"focxle"
]
}
}
}VS Codeにfocxle MCPをインストール
.vscode/mcp.json
{
"servers": {
"focxle-python": {
"type": "stdio",
"command": "uvx",
"args": [
"focxle"
]
}
}
}VS Code CLIにfocxle MCPをインストール
$ code --add-mcp '{"name":"focxle-python","type":"stdio","command":"uvx","args":["focxle"]}'Claude Desktopにfocxle MCPをインストール
claude_desktop_config.json
{
"mcpServers": {
"focxle-python": {
"command": "uvx",
"args": [
"focxle"
]
}
}
}Codexにfocxle MCPをインストール
$ codex mcp add focxle-python -- uvx focxleCodex config.tomlにfocxle MCPをインストール
~/.codex/config.toml
[mcp_servers.focxle-python] command = "uvx" args = ["focxle"]
Gemini CLIにfocxle MCPをインストール
$ gemini mcp add -s user focxle-python uvx -- focxleGemini settings.jsonにfocxle MCPをインストール
~/.gemini/settings.json
{
"mcpServers": {
"focxle-python": {
"command": "uvx",
"args": [
"focxle"
]
}
}
}設定
FOCXLE_NO_HISTORYSet to 1 to stop focxle keeping any local spend history. The server then has nothing to read and will say so.
| 名前 | 説明 | 種類 |
|---|---|---|
| FOCXLE_NO_HISTORY | Set to 1 to stop focxle keeping any local spend history. The server then has nothing to read and will say so. |
自動チェック
実行日 2026年11月15日完全なレポート →自動チェックに合格しました。これはセキュリティ監査ではありません。コードを読み、サーバーに必要最小限のアクセス権を与えてください。 チェックの仕組み
- ソースリポジトリがリンクされており、アクセス可能focxle/focxle-python is public and reachablegithub.com/focxle/focxle-python ↗合格
- パッケージがこのリポジトリをソースとして指定focxle names focxle/focxle-python as sourcepypi.org/project/focxle/ ↗合格
- ビルドの来歴 (Sigstore 証明)No build attestation published for this release未チェック
- オープンソースライセンス (OSI)MITspdx.org/licenses/MIT.html ↗合格
- 過去1年以内にコミットまたはリリースありLast commit or release 2026-09-21github.com/focxle/focxle-python ↗合格
- OpenSSF Scorecard未チェック
- パッケージ名が有名なパッケージに酷似していないNo popular package one edit away from focxle合格
- パッケージおよびその依存関係に重大な勧告なし1 resolved dependencies checked; no critical advisoryosv.dev ↗合格
- モデルへの隠れた指示がない0 tool descriptions and the README read; no override phrases, credential paths or hidden characters合格
- 破壊的なツールがラベル付けされている未チェック
- リモートエンドポイントが MCP ハンドシェイクに応答未チェック
README
GitHubで見る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 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
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 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:
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 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.
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 decide
python -m focxle share on
python -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 mrinal@focxle.com.
- 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.
focxle MCPのよくある質問
focxle MCPをClaude Codeに追加するには
ターミナルでclaude mcp add focxle-python -- uvx focxleを実行します。すべてのプロジェクトで利用するには--scope userを追加します。
focxle MCPをCursorに追加するには
~/.cursor/mcp.jsonを開き、上記のインストールセクションに示すCursor設定を使ってmcpServersの下にサーバーを追加します。
focxleを使用するためにアカウントやAPIキーは必要ですか?
いいえ、アカウント、APIキー、設定ファイルは一切不要です。価格情報はパッケージに含まれているため、オフラインで動作します。
focxleを使うと既存のエージェントコードが壊れることはありますか?
このライブラリはfail open(フェイルオープン)設計になっています。万が一エラーが発生しても、エージェントの呼び出しはそのまま実行され、エラーのみが記録されます。
コードエディタでfocxleを使用できますか?
はい、MCP serverが含まれているため、Claude Code、Cursor、Windsurf、Zedなどのエディタからエージェントの支出について質問できます。
プロンプトやレスポンスがサーバーに送信されることはありますか?
いいえ、エージェント名、モデル名、プロンプト、レスポンス、URLなどが送信されることはありません。テレメトリはデフォルトでオフになっており、明示的に有効にした場合にのみ、匿名のベンダー別合計値が送信されます。