Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者による説明(英語の原文)
Compares AI coding tool spend before and after a migration via MCP tools.
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"teamspend": {
"command": "uvx",
"args": [
"teamspend-cli",
"teamspend-mcp"
]
}
}
}ターミナルでこれを実行します
claude mcp add teamspend -- uvx teamspend-cli teamspend-mcpプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"teamspend": {
"command": "uvx",
"args": [
"teamspend-cli",
"teamspend-mcp"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"teamspend": {
"type": "stdio",
"command": "uvx",
"args": [
"teamspend-cli",
"teamspend-mcp"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月7日にチェック
レジストリ名は、リポジトリを所有するGitHubアカウント RudrenduPaul で確認済みです
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
これはパソコンで動くため、インターネット上のエンドポイントはありません
パソコンで動き、代わりにローカルの設定を使います
パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。
GitHubリポジトリの最終更新は–、最新バージョン(0.2.6)がレジストリに届いたのは3 か月前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにPython (uv)も必要です。
同じカテゴリには:Spec Driven Development, Remote Desktop Commander, Kanal Varna — drains, leaks & plumbing (Varna, BG)
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Drain unblocking, leak detection & plumbing in Varna, Bulgaria: services, prices, areas, contact
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
Install • Usage • Features • Compare • FAQ • Contributing
Your AI coding tools will never tell you if switching between them actually saved money. teamspend does, in one command.
The recording above uses claude-code-personal (credential-free, reads local session logs) so the install-to-first-run flow plays end to end with no admin API keys required; the live output shape is identical whichever adapter you point it at.
npx teamspend-cli --tools cursor,claude-code --before 2026-04-01:2026-04-30 --after 2026-06-01:2026-06-30
Six tools now, not two: Cursor, Claude Code, GitHub Copilot, OpenCode, and Codex CLI, plus a credential-free personal mode for anyone without admin access. More teams are running more than one AI coding tool at once, or moving between them, than ever before. Every one of those tools has a dashboard that's perfectly accurate about itself and structurally incapable of showing you anything else. teamspend is the missing piece: one real number, pulled straight from both tools' own APIs, showing exactly what changed.
npx teamspend-cli --tools cursor,claude-code --before 2026-04-01:2026-04-30 --after 2026-06-01:2026-06-30
Example output (shape shown below; your real numbers come from your own org's API data):
teamspend snapshot -- migration cost comparison Tools: cursor -> claude-code
BEFORE (cursor) Total spend: $2,140.00 (exact, usage-based) Active users: 14
AFTER (claude-code) Total spend: $1,860.00 (exact, usage-based) Active users: 14
DELTA: -$280.00 (-13.1%)
Full report: ./teamspend-snapshot-2026-07-11T142842.json
That's the whole product. One command, one honest number, zero spreadsheets.
$0 for a user with real token activity. teamspend detects that pattern and marks the number estimated rather than showing a misleading zero.fetch, native argument parsing, native file I/O.teamspend ships two independent, equally first-class packages -- pick whichever fits your toolchain, or install both. They talk to the same six data sources and compute the same before/after delta.
# npm -- JavaScript/TypeScript CLI + library
npm install -g teamspend-cli
pip install teamspend-cli
Both packages are named teamspend-cli (the older plain teamspend name was renamed to match this project's other packages, then fully unpublished from both registries as of 2026-08-03 -- same maintainer, same repo, but no longer installable under any version). Either way, the installed command is teamspend.
Give it the two API keys for the tools you're comparing:
export TEAMSPEND_CURSOR_TOKEN=<your Cursor Admin API key>
export TEAMSPEND_CLAUDE_CODE_TOKEN=
Both need org-admin-level access on their platform. If you can already see billing for your org, you have what you need.
teamspend --tools cursor,claude-code --before 2026-04-01:2026-04-30 --after 2026-06-01:2026-06-30
Add --json to print the full JSON report to stdout instead of the human-readable summary above -- useful for piping into another script or a CI step. The JSON report file on disk is written either way; --json only changes what prints to the terminal.
Comparing against GitHub Copilot instead? See "GitHub Copilot support" below -- it needs two more environment variables than Cursor/Claude Code do, for reasons that are worth reading before you point it at a real org.
Both CLIs accept the same comparison flags (--tools, --before, --after, --json, --before-csv, --after-csv, --breakdown, --help/-h, --version/-V) and print the same output shape. See the Commands section below for the full flag reference, python/README.md for the Python package's library API, and docs/getting-started.md for the full guide covering both distributions.
A tool that touches your team's spend and email data should earn that trust in the open. Here's what's actually true about this codebase, checked on every commit, not asserted in a marketing paragraph:
| Runtime dependencies | Zero |
| Package size | 56.8 kB packed, 193.1 kB unpacked |
| Cold install to first response | Under 1 second, measured with a cleared npm/npx cache |
| Tests | 102 passing (npm), 116 passing (PyPI), 97% line coverage on the TypeScript suite |
| Known vulnerabilities | Zero, per npm audit |
| File permissions | Report files are owner-only (0600) and auto-gitignored, since they hold per-user emails and spend |
date,user_email,cost_usd,is_estimated 2025-11-01,jane@example.com,12.50,false
npx teamspend-cli --tools cursor,claude-code --before 2025-11-01:2025-11-30 --after 2026-06-01:2026-06-30 --before-csv ./before.csv
export TEAMSPEND_COPILOT_TOKEN= export TEAMSPEND_COPILOT_ORG= export TEAMSPEND_COPILOT_SEAT_PRICE_USD=19 # optional, see below
npx teamspend-cli --tools cursor,copilot --before 2026-04-01:2026-04-30 --after 2026-06-01:2026-06-30
Credential: TEAMSPEND_COPILOT_TOKEN needs the read:org scope (a classic PAT) or the fine-grained "View Organization Copilot Metrics" permission, and the org must be on Copilot Business or Enterprise. TEAMSPEND_COPILOT_ORG is required too -- unlike Cursor's and Claude Code's admin APIs, GitHub's Copilot metrics endpoint is scoped to a specific org login in the URL path itself, not just the token.
How teamspend derives a dollar figure, honestly: GitHub's real, current Copilot usage metrics API (GET /orgs/{org}/copilot/metrics/reports/ users-1-day, confirmed against GitHub's own docs while building this -- the older /orgs/{org}/copilot/metrics endpoint some other tools still reference was sunset by GitHub on 2026-04-02 and no longer works) has no cost or spend field anywhere. Copilot Business/Enterprise is flat-seat billing ($19 or $39 per seat per month, bundling a matching monthly AI-credit allowance), and GitHub does not expose an org's actual contracted seat price through any API -- the same structural gap Cursor's and Claude Code's flat-seat billing tiers already have in this tool.
What the API *does* return per user is ai_credits_used. teamspend converts that to USD at GitHub's own published, fixed rate of 1 AI credit = $0.01 USD -- not invented, and not a negotiated per-org price. If you set TEAMSPEND_COPILOT_SEAT_PRICE_USD, that flat price is added once per active user for the whole comparison window (never once per day) to also reflect the license cost the credits-only figure excludes; if you don't set it, the reported number is credits-usage cost only and explicitly does not include the seat fee.
Because there is no vendor-reported cost field to begin with, every Copilot result -- with or without a seat price -- is marked isEstimated: true. This is a stronger caveat than Cursor's and Claude Code's suspicious-zero flag, which only fires on a specific zero-cost pattern: Copilot has no native dollar figure to trust in the first place, so teamspend never claims one. See docs/concepts.md for the full mechanics, including why one comparison window means one API call per calendar day rather than one call for the whole range.
OpenCode (formerly sst/opencode) has no admin, team, or billing API at all -- it's a local CLI with no organization-level usage endpoint, confirmed against its own README. There is nothing for TEAMSPEND_OPENCODE_TOKEN to authenticate, so it doesn't exist; teamspend instead reads OpenCode's own local session logs directly off disk (~/.local/share/opencode/storage/message/, or $OPENCODE_DATA_DIR if set), the same file format OpenCode itself writes and that [ccusage's OpenCode guide](https://ccusage.com/guide/openc
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