GitDiagram
Architecture diagrams, explanations and Mermaid source for public GitHub repositories.
See each coding-agent subscription's live limits and offload work to one with headroom.
Pick the AI app you use, then copy the settings.
Passed 3/3 checks · Runs on your computer · ✓ Commands checked Nov 14, 2026
First: which AI do you use?
Pick your app and the steps appear below.
Works with Claude, with some setup first
Install Python (uv) on your computer first (one time) · Only the Claude desktop app (Windows or Mac), not the web or phone
Copy this message into a Claude chat. The AI checks your computer, tells you which file it will change, and waits for your OK every time.
Please install the MCP server AgentPool for Claude on this computer, in this order: 1) Check uv with uv --version. If it is missing, tell me to install it from https://docs.astral.sh/uv/getting-started/installation/; do not install it yourself. 2) Use only this config (already checked by PopNx MCP): { "mcpServers": { "agentpool": { "command": "uvx", "args": [ "agentpool-cli", "mcp" ] } } } 3) Tell me the full path of the file you will change, or the command you will run, and wait for my OK. 4) No key is needed. 5) Do what we agreed, then check that the AgentPool tools really show up.This message has no key in it. If a key is needed, the AI will ask you to paste it yourself into the file or the app’s field.
Already installed? Check first · Open Terminal, type this command and press Enter
uv --versionMac: press ⌘ + Space, type Terminal, press Enter
Windows: open Start, type Windows PowerShell, then Open
Not installed: uv has no click-through installer. Copy the one-line command for your system (macOS or Windows) from uv’s official page into Terminal · no separate Python install needed; uv downloads it when required
When it’s done, close Terminal, open it again and run the same command. You should see a version number: uv --version
Install once; it works for everything that needs uv
SettingsDeveloperEdit Config
{
"mcpServers": {
"agentpool": {
"command": "uvx",
"args": [
"agentpool-cli",
"mcp"
]
}
}
}Use AgentPool and tell me what you can do for me, then show me one thing✓ If Claude says it is using AgentPool or shows a AgentPool tool in the answer, you are connected
Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version
ChatGPT cannot connect AgentPool yet
AgentPool runs on your computer, but ChatGPT can only connect servers that run on the web
A · Use an app that can connect AgentPool
B · Others in Developer tools that work with ChatGPT
Picked from the most used in the same category, only ones that connect by address with no key
Works with Claude Code, with some setup first
Install Python (uv) on your computer first (one time)
Copy this message into a Claude Code chat. The AI checks your computer, tells you which file it will change, and waits for your OK every time.
Please install the MCP server AgentPool for Claude Code on this computer, in this order: 1) Check uv with uv --version. If it is missing, tell me to install it from https://docs.astral.sh/uv/getting-started/installation/; do not install it yourself. 2) Use only this config (already checked by PopNx MCP): claude mcp add --scope user agentpool -- uvx agentpool-cli mcp 3) Tell me the full path of the file you will change, or the command you will run, and wait for my OK. 4) No key is needed. 5) Do what we agreed, then check that the AgentPool tools really show up.This message has no key in it. If a key is needed, the AI will ask you to paste it yourself into the file or the app’s field.
Already installed? Check first · Open Terminal, type this command and press Enter
uv --versionMac: press ⌘ + Space, type Terminal, press Enter
Windows: open Start, type Windows PowerShell, then Open
Not installed: uv has no click-through installer. Copy the one-line command for your system (macOS or Windows) from uv’s official page into Terminal · no separate Python install needed; uv downloads it when required
When it’s done, close Terminal, open it again and run the same command. You should see a version number: uv --version
Install once; it works for everything that needs uv
Mac: press Command+Space and type Terminal · Windows: open PowerShell
claude mcp add --scope user agentpool -- uvx agentpool-cli mcpYou should see AgentPool listed as connected
Use AgentPool and tell me what you can do for me, then show me one thing✓ If Claude Code says it is using AgentPool or shows a AgentPool tool in the answer, you are connected
Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Works with Cursor, with some setup first
Install Python (uv) on your computer first (one time)
Copy this message into a Cursor chat. The AI checks your computer, tells you which file it will change, and waits for your OK every time.
Please install the MCP server AgentPool for Cursor on this computer, in this order: 1) Check uv with uv --version. If it is missing, tell me to install it from https://docs.astral.sh/uv/getting-started/installation/; do not install it yourself. 2) Use only this config (already checked by PopNx MCP): { "mcpServers": { "agentpool": { "command": "uvx", "args": [ "agentpool-cli", "mcp" ] } } } 3) Tell me the full path of the file you will change, or the command you will run, and wait for my OK. 4) No key is needed. 5) Do what we agreed, then check that the AgentPool tools really show up.This message has no key in it. If a key is needed, the AI will ask you to paste it yourself into the file or the app’s field.
Already installed? Check first · Open Terminal, type this command and press Enter
uv --versionMac: press ⌘ + Space, type Terminal, press Enter
Windows: open Start, type Windows PowerShell, then Open
Not installed: uv has no click-through installer. Copy the one-line command for your system (macOS or Windows) from uv’s official page into Terminal · no separate Python install needed; uv downloads it when required
When it’s done, close Terminal, open it again and run the same command. You should see a version number: uv --version
Install once; it works for everything that needs uv
Use AgentPool and tell me what you can do for me, then show me one thing✓ If Cursor says it is using AgentPool or shows a AgentPool tool in the answer, you are connected
Menu names checked against Cursor’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Works with VS Code, with some setup first
Install Python (uv) on your computer first (one time)
Copy this message into a VS Code chat. The AI checks your computer, tells you which file it will change, and waits for your OK every time.
Please install the MCP server AgentPool for VS Code on this computer, in this order: 1) Check uv with uv --version. If it is missing, tell me to install it from https://docs.astral.sh/uv/getting-started/installation/; do not install it yourself. 2) Use only this config (already checked by PopNx MCP): { "servers": { "agentpool": { "type": "stdio", "command": "uvx", "args": [ "agentpool-cli", "mcp" ] } } } 3) Tell me the full path of the file you will change, or the command you will run, and wait for my OK. 4) No key is needed. 5) Do what we agreed, then check that the AgentPool tools really show up.This message has no key in it. If a key is needed, the AI will ask you to paste it yourself into the file or the app’s field.
Already installed? Check first · Open Terminal, type this command and press Enter
uv --versionMac: press ⌘ + Space, type Terminal, press Enter
Windows: open Start, type Windows PowerShell, then Open
Not installed: uv has no click-through installer. Copy the one-line command for your system (macOS or Windows) from uv’s official page into Terminal · no separate Python install needed; uv downloads it when required
When it’s done, close Terminal, open it again and run the same command. You should see a version number: uv --version
Install once; it works for everything that needs uv
Use AgentPool and tell me what you can do for me, then show me one thing✓ If VS Code says it is using AgentPool or shows a AgentPool tool in the answer, you are connected
Menu names checked against VS Code’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Claude Code
claude mcp add --scope user agentpool -- uvx agentpool-cli mcpClaude Desktop (claude_desktop_config.json)
{
"mcpServers": {
"agentpool": {
"command": "uvx",
"args": [
"agentpool-cli",
"mcp"
]
}
}
}Cursor (~/.cursor/mcp.json)
{
"mcpServers": {
"agentpool": {
"command": "uvx",
"args": [
"agentpool-cli",
"mcp"
]
}
}
}VS Code (mcp.json)
{
"servers": {
"agentpool": {
"type": "stdio",
"command": "uvx",
"args": [
"agentpool-cli",
"mcp"
]
}
}
}These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
pypi: agentpool-cliBased on how this server connects and on each app’s own docs, checked Nov 10, 2026.
Run on your computer in
ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 15, 2026
The registry name was verified with the GitHub account sidduHERE, which owns the repo
Code last changed 3 months ago
Uses MIT
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Not checked yet
Ask, share a tip or report that it does not work. Sorted by what people marked helpful.
No posts yet. Be the first to ask or share.
Posts here are written by users, not the PopNx team.
No reviews yet
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 3 of 3 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed 3 months ago, and the latest version (0.1.13) reached the registry 5 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: GitDiagram, Appllama, Cloudflare MCP, Omnara, Repowise
Same category, other makers, commands already checked. Official ones first, then by stars.
Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Architecture diagrams, explanations and Mermaid source for public GitHub repositories.
Study screens, flows and paywalls from top-earning iOS apps, then build from what wins.
Cloudflare MCP servers
Deploy durable AI agents with Omnara, an open-source managed-agent platform.
Codebase intelligence for AI coding agents: graph, git history, docs, decisions, code health.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
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.