Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
See each coding-agent subscription's live limits and offload work to one with headroom.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"agentpool": {
"command": "uvx",
"args": [
"agentpool-cli",
"mcp"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add agentpool -- uvx agentpool-cli mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"agentpool": {
"command": "uvx",
"args": [
"agentpool-cli",
"mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"agentpool": {
"type": "stdio",
"command": "uvx",
"args": [
"agentpool-cli",
"mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 GitHub 계정 sidduHERE 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.1.13)은 4개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, Dechonet MCP
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
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.
30 security tools for AI agents: phishing links, exposure maps, DNS, SSL, PQC, history, pivots.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
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:
provider=auto is rejected.PATH.termctrl on PATH for the Terminal Control runtime.AgentPool publishes to PyPI as agentpool-cli; the installed command is agentpool.
uv tool install agentpool-cli # recommended
pipx install agentpool-cli # fallback uvx agentpool-cli --help # zero-install try
Then:
agentpool setup codex
agentpool 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:
runtime:
default: tmux terminal_control: enabled: true binary: termctrl session_prefix: agentpool cols: 120 rows: 36
Install from source:
git clone https://github.com/sidduHERE/agentpool.git
cd agentpool uv tool install --force .
Or run from a development checkout:
uv venv
uv pip install -e ".[dev]"
A GitHub release install (wheel pinned to a tag, no PyPI required) is also supported:
scripts/install.sh latest
See docs/install.md for first-run, upgrade, and MCP setup notes.
For AI agents, start by loading the bundled version-matched skill:
agentpool skills get agentpool
agentpool skills get core --full
agentpool init
agentpool setup cursor agentpool config validate agentpool doctor --deep --privacy agentpool setup all agentpool smoke --provider fake-question --repo . --json agentpool inventory --json agentpool 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:
agentpool spawn \
--provider \ --repo . \ --task "Inspect the project and ask one clarifying question." \ --isolation read_only
agentpool observe --wait-for completed,error,question,approval_prompt --timeout 60 --json agentpool send "Continue with the smallest useful check." agentpool artifacts --json agentpool transcript --tail-lines 80 --json agentpool session show --json agentpool sessions --recent 10 --json agentpool collect --json agentpool terminate --dry-run --json agentpool terminate --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:
agentpool spawn \
--provider \ --repo . \ --task "Make the small patch." \ --role implementer \ --isolation worktree
agentpool worktrees list --repo . agentpool worktrees cleanup --session-id --dry-run --json agentpool worktrees cleanup --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.
agentpool usage-summary --refresh --json
agentpool usage-summary --refresh --no-interactive --json agentpool stats --since 7d --json agentpool usage-summary --refresh --backend codexbar --json agentpool 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 id | Command | Usage status in v0.1 | Model pinning |
|---|---|---|---|
codex-cli | codex | native local app-server rate-limit probe; CodexBar optional | --model + config-scoped reasoning/service tier |
cursor-cli | agent or cursor-agent | optional CodexBar Cursor usage; native CLI usage is interactive /usage only | --model + read-only --mode ask |
claude-code | claude | temporary /usage probe; ccusage telemetry optional | --model + --effort |
devin-cli | devin | Devin/Windsurf plan-status API from existing CLI auth, with /usage fallback | --model |
copilot-cli | gh copilot | GitHub Copilot usage API from env or gh auth token | forwarded --model |
droid-cli | droid | unknown unless surfaced by future safe probe | process-local settings file + --reasoning-effort |
opencode | opencode | configured 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.
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:
AgentPool does store:
~/.agentpool/artifacts by default;Run:
agentpool doctor --privacy --json
See SECURITY.md and docs/usage-detection.md.
Start the MCP server:
agentpool mcp
agentpool mcp --toolsets default,stats AGENTPOOL_MCP_LOCKDOWN=1 agentpool mcp
Example host config:
agentpool mcp-config --client generic
{
"mcpServers": { "agentpool": { "command": "agentpool", "args": ["mcp"] } } }
Verified install helpers (deeplink or one-liner shell command):
agentpool mcp-config --client cursor --absolute-command --install
agentpool mcp-config --client claude-code --absolute-command --install agentpool mcp-config --client codex --absolute-command --install agentpool mcp-config --client copilot-cli --absolute-command --install
Raw config generators:
agentpool mcp-config --client claude-code --json
agentpool mcp-config --client codex agentpool mcp-config --client cursor agentpool 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://onboardingagentpool://skill.mdagentpool://preferences.mdThen 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 and CI checks are documented in CONTRIBUTING.md.