AgentPool

io.github.sidduHERE由 GitHub 帳號 sidduHERE 發布v0.1.13更新於 Oct 24, 2026

See each coding-agent subscription's live limits and offload work to one with headroom.

已驗證STDIO僅桌面開發者工具AI 與機器學習

概覽

AI 產生的概覽

本機 MCP 伺服器兼命令列工具,顯示各程式代理訂閱的即時用量上限,讓助理把工作交給仍有餘量的供應商執行。

可以做什麼
檢視已設定的程式代理供應商、可用模型,以及附信心標記與重置時間的用量/容量摘要,並讀取委派偏好與入門資源。在指定供應商與儲存庫上明確建立工作階段,可選唯讀或 worktree 隔離,然後觀察、輪詢、傳送訊息、中斷、收集結果與終止工作階段。讀取產物清單並分頁查看工作階段紀錄。可視需要啟用統計、工作階段、租約與 worktree 工具集。
適用情境
適合同時付費訂閱多個程式代理(Codex、Claude Code、Cursor、Copilot、Devin、Droid)的使用者,讓助理在分派工作前先看清哪個訂閱還有餘量。也適合在沒有 shell 存取權的 MCP 原生用戶端中執行並監督委派的工作階段。
執行需求
需在本機安裝 Python 3.11 以上,並透過 PyPI 的 agentpool-cli 套件以 mcp 子命令啟動。預設執行環境需要 PATH 中有 tmux;termctrl、Git、CodexBar 與 ccusage 為選用。即時執行環境支援 macOS 或 Linux(Windows 僅限 WSL)。各供應商 CLI 需已安裝並完成登入;伺服器本身未宣告任何憑證。
安裝前請注意
用量探測會讀取現有 CLI 的登入狀態,重新整理時可能呼叫供應商 API,因此用量資料可能敏感。它會在 SQLite 與 agentpool 家目錄下的檔案中保存工作階段、事件、用量快照、產物與紀錄中繼資料。建立的工作階段會操作你的儲存庫,選擇 worktree 隔離時可修改檔案;終止工作階段與清理 worktree 會改變狀態。供應商需明確選擇,且不會默默接受付費超額。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 AgentPool,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

AgentPool

You pay for several coding-agent subscriptions — Codex, Claude Code, Cursor, Copilot, Devin, Droid — but you work in one at a time. The rest sit idle until your active provider hits its 5-hour or weekly limit, and then you stall.

AgentPool is a local Python CLI and MCP server that reads the live usage limits of every coding-agent subscription you have and lets you — or your primary agent — offload work to whichever one still has headroom. Use the capacity you already pay for, and keep moving instead of hard-stopping at a cap.

It is a control plane, not an auto-router. AgentPool exposes live provider, model, session, artifact, lease, and best-effort usage/capacity state, and runs the work you offload as explicit worker sessions. You or your agent still choose the provider and model — AgentPool makes the limits visible so that choice is informed, never automatic.

The v0.1 alpha posture is conservative:

  • tmux is the default runtime; Terminal Control is optional when configured.
  • Provider selection is explicit; provider=auto is rejected.
  • Usage/capacity summaries are confidence-tagged and keyed by provider id.
  • CodexBar and ccusage are optional usage helpers when installed or configured.
  • AgentPool does not store provider credentials, scrape browser usage pages, rank models, merge code, or push code.

Requirements

  • Python 3.11 or newer.
  • tmux on PATH.
  • Optional: termctrl on PATH for the Terminal Control runtime.
  • Git for worktree isolation and diff collection.
  • macOS or Linux for live runtimes. Windows is not a v0.1 target except through WSL-like shells.

Install

AgentPool publishes to PyPI as agentpool-cli; the installed command is agentpool.

bash
uv tool install agentpool-cli      # recommendedpipx install agentpool-cli         # fallbackuvx agentpool-cli --help           # zero-install try

Then:

bash
agentpool setup codexagentpool doctor --deep --privacy

The agentpool-cli package installs on macOS, Linux, and Windows, but live terminal runtimes are supported on macOS or Linux (Windows via WSL).

Optional Terminal Control config:

yaml
runtime:  default: tmux  terminal_control:    enabled: true    binary: termctrl    session_prefix: agentpool    cols: 120    rows: 36

Install from source:

bash
git clone https://github.com/sidduHERE/agentpool.gitcd agentpooluv tool install --force .

Or run from a development checkout:

bash
uv venvuv pip install -e ".[dev]"

A GitHub release install (wheel pinned to a tag, no PyPI required) is also supported:

bash
scripts/install.sh latest

See docs/install.md for first-run, upgrade, and MCP setup notes.

Quickstart

For AI agents, start by loading the bundled version-matched skill:

bash
agentpool skills get agentpoolagentpool skills get core --full
bash
agentpool initagentpool setup cursoragentpool config validateagentpool doctor --deep --privacyagentpool setup allagentpool smoke --provider fake-question --repo . --jsonagentpool inventory --jsonagentpool usage-summary --refresh --json

That last command is the one you will run most: it shows every configured subscription's remaining limit, reset time, and a usable flag, so you can see at a glance which provider to offload the next task to.

Start an explicitly selected read-only worker:

bash
agentpool spawn \  --provider <provider-id> \  --repo . \  --task "Inspect the project and ask one clarifying question." \  --isolation read_only
agentpool observe <session-id> --wait-for completed,error,question,approval_prompt --timeout 60 --jsonagentpool send <session-id> "Continue with the smallest useful check."agentpool artifacts <session-id> --jsonagentpool transcript <session-id> --tail-lines 80 --jsonagentpool session show <session-id> --jsonagentpool sessions --recent 10 --jsonagentpool collect <session-id> --jsonagentpool terminate <session-id> --dry-run --jsonagentpool terminate <session-id> --json

spawn defaults --initial-prompt-mode to provider_default. For Codex CLI this resolves to arg, which passes the first task as the Codex prompt argument instead of relying on a paste-and-submit startup cycle. Providers that expose reasoning controls also accept process-local overrides such as --reasoning-effort high; Codex also accepts --service-tier priority. AgentPool does not edit your provider config.

For AgentPool-created edit isolation, choose worktrees explicitly:

bash
agentpool spawn \  --provider <provider-id> \  --repo . \  --task "Make the small patch." \  --role implementer \  --isolation worktree
agentpool worktrees list --repo .agentpool worktrees cleanup --session-id <session-id> --dry-run --jsonagentpool worktrees cleanup --session-id <session-id>

Worktree isolation is not forced by default. Users often have their own worktree setup and cleanup rules, so AgentPool only creates a worktree when requested through --isolation worktree or policy configuration.

Usage And Capacity

bash
agentpool usage-summary --refresh --jsonagentpool usage-summary --refresh --no-interactive --jsonagentpool stats --since 7d --jsonagentpool usage-summary --refresh --backend codexbar --jsonagentpool usage-summary --refresh --backend ccusage --provider claude-code --json

usage-summary returns a providers object keyed by provider id. It is not ordered and it is not a recommendation list. Each row includes usable, unusable_reason, quota windows, confidence, age/staleness, and reset timing when the provider exposes it. The older CLI capacity-summary command is retained as a human convenience alias; MCP also exposes get_capacity_summary as a compatibility alias for get_usage_summary.

The default buffer is policy.min_remaining_percent = 10. If any reported quota window is below that buffer, the provider row is marked unusable for the summary. Staleness is reported as age information only; it does not by itself make a provider unusable. If you want cached summary reads to refresh automatically after a threshold, set policy.usage_auto_refresh_after_seconds in ~/.agentpool/config.yaml. AgentPool still does not pick an alternative provider for you. MCP usage refreshes are intentionally bounded and may return partial=true; use the CLI commands above when a shell-capable agent needs a complete live refresh. Use --no-interactive or AGENTPOOL_NO_INTERACTIVE_USAGE=1 when a shell script must avoid provider TUI fallback probes.

Provider Matrix

Provider idCommandUsage status in v0.1Model pinning
codex-clicodexnative local app-server rate-limit probe; CodexBar optional--model + config-scoped reasoning/service tier
cursor-cliagent or cursor-agentoptional CodexBar Cursor usage; native CLI usage is interactive /usage only--model + read-only --mode ask
claude-codeclaudetemporary /usage probe; ccusage telemetry optional--model + --effort
devin-clidevinDevin/Windsurf plan-status API from existing CLI auth, with /usage fallback--model
copilot-cligh copilotGitHub Copilot usage API from env or gh auth tokenforwarded --model
droid-clidroidunknown unless surfaced by future safe probeprocess-local settings file + --reasoning-effort
opencodeopencodeconfigured adapter; usage unknown in this alpha--model with provider/model ids

Compatibility note: the PRD calls Factory's coding product factory-droid, but AgentPool exposes it as droid-cli because the installed command is droid. Do not add a duplicate factory-droid inventory row unless a distinct harness appears.

Privacy Posture

AgentPool is local-first, but usage probes can still be sensitive because they read existing CLI auth state and may call provider APIs on explicit refresh.

AgentPool does not:

  • store provider credentials;
  • read browser cookies by default;
  • scrape browser dashboards;
  • trigger login flows;
  • silently accept paid overage.

AgentPool does store:

  • SQLite session, event, usage snapshot, artifact, and lease metadata;
  • transcript and artifact files under ~/.agentpool/artifacts by default;
  • generated runtime settings that are not credentials.

Run:

bash
agentpool doctor --privacy --json

See SECURITY.md and docs/usage-detection.md.

MCP

Start the MCP server:

bash
agentpool mcpagentpool mcp --toolsets default,statsAGENTPOOL_MCP_LOCKDOWN=1 agentpool mcp

Example host config:

bash
agentpool mcp-config --client generic
json
{  "mcpServers": {    "agentpool": {      "command": "agentpool",      "args": ["mcp"]    }  }}

Verified install helpers (deeplink or one-liner shell command):

bash
agentpool mcp-config --client cursor --absolute-command --installagentpool mcp-config --client claude-code --absolute-command --installagentpool mcp-config --client codex --absolute-command --installagentpool mcp-config --client copilot-cli --absolute-command --install

Raw config generators:

bash
agentpool mcp-config --client claude-code --jsonagentpool mcp-config --client codexagentpool mcp-config --client cursoragentpool mcp-config --client claude-desktop --json

Use --absolute-command if the MCP host does not inherit your shell PATH. Verified per-host steps live in docs/mcp-clients.md. Team templates: .cursor/mcp.json.example, .mcp.json.example, and docs/examples/README.md. MCP Registry metadata: server.json. It advertises the agentpool-cli PyPI package and should be bumped with each release. Release checklist: docs/release.md. Provider setup guides: Cursor, Cursor Agent CLI, Codex, Claude Code, Copilot, Droid, and Devin.

MCP-connected agents should read these once on connect:

  • agentpool://onboarding
  • agentpool://skill.md
  • agentpool://preferences.md

Then use tools for live operations. The user-owned preferences file also shows up through agentpool preferences and get_delegation_preferences(). It may say to use your native subagent system instead of AgentPool for some tasks. The default MCP toolset is deliberately small: inventory, usage snapshot, usage summary, provider models, preferences, spawn, observe, poll, send, interrupt, collect, artifact manifest, transcript paging, and terminate. Add opt-in toolsets with agentpool mcp --toolsets default,stats,sessions,leases,worktrees.

Shell-capable agents can use agentpool skills get agentpool instead of MCP resources to load the same core usage guidance from the installed CLI.

Coding agents with shell access should prefer the CLI path. It is more token-efficient because large worker output stays in artifact files and observe/collect return compact manifests by default. MCP remains first-class for MCP-native hosts and no-shell environments. See docs/agent-cli-and-mcp.md.

Development Checks

Development and CI checks are documented in CONTRIBUTING.md.

來源:README.md,提交 de87ff2

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v0.1.13最新Sep 16, 2026

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