
AgentPool
io.github.sidduHEREPublished by GitHub account sidduHEREv0.1.13Updated Oct 24, 2026
See each coding-agent subscription's live limits and offload work to one with headroom.
Overview
A local MCP server and CLI that shows live usage limits of coding-agent subscriptions and lets an assistant spawn work on a chosen provider with headroom.
- What you can do
- Inspect configured coding-agent providers, their models and usage/capacity summaries with confidence and reset timing, plus delegation preferences and onboarding resources from the MCP server itself. Spawn explicit worker sessions on a named provider and repo, with read-only or worktree isolation, then observe, poll, send to, interrupt, collect from and terminate them. Read artifact manifests and page through session transcripts. Optionally add stats, sessions, leases and worktree toolsets.
- When to use it
- Useful when you pay for several coding-agent subscriptions (Codex, Claude Code, Cursor, Copilot, Devin, Droid) and want an assistant to see which one still has quota before offloading a task. Also for running and supervising delegated worker sessions from an MCP-native host without shell access.
- Requirements
- Local Python 3.11+ install of the agentpool-cli PyPI package, started with the mcp subcommand. tmux on PATH is the default runtime; termctrl, Git, CodexBar and ccusage are optional. macOS or Linux for live runtimes (Windows only via WSL). Provider CLIs must already be installed and authenticated; no credentials are declared for the server itself.
Installation
In SourceWeft
- Open AgentPool in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
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=autois 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:
termctrlonPATHfor 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.
Then:
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:
Install from source:
Or run from a development checkout:
A GitHub release install (wheel pinned to a tag, no PyPI required) is also supported:
See docs/install.md for first-run, upgrade, and MCP setup notes.
Quickstart
For AI agents, start by loading the bundled version-matched skill:
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:
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:
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
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
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/artifactsby default; - generated runtime settings that are not credentials.
Run:
See SECURITY.md and docs/usage-detection.md.
MCP
Start the MCP server:
Example host config:
Verified install helpers (deeplink or one-liner shell command):
Raw config generators:
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.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.
Source: README.md at commit de87ff2
Tools
0Version history
1- v0.1.13LatestSep 16, 2026
Score
50% of the applicable checks met
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- Reached in the last 30 days25 pts
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- Tools listed15 pts
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- DescriptionRequired15 pts
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