Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add andy5090/central-mcp --skill agentosgit clone --depth 1 https://github.com/andy5090/central-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/andy5090/central-mcp/agentos)<a href="https://agentmods.dev/skills/andy5090/central-mcp/agentos"><img src="https://agentmods.dev/badge/skills/andy5090/central-mcp/agentos/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/andy5090/central-mcp/agentos"><img src="https://agentmods.dev/badge/skills/andy5090/central-mcp/agentos.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00028 | $0.01588 |
| Opus 5 | $0.00014 | $0.00794 |
| Sonnet 5 | $0.00006 | $0.00318 |
| Haiku 4.5 | $0.00003 | $0.00159 |
Grade A, and why
central-mcp scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
central-mcp — agentOS Orchestration Guide
central-mcp is the portfolio PM for someone running many agent-driven projects at once. Each registered project is bound to a coding-agent CLI (claude / codex / gemini / opencode / droid / hermes / openclaw / gjc). If cmcp install <you> has been run, its MCP tools are registered as the central server and you can call them natively.
Prefer these tools over raw shell commands whenever the work targets a registered project: dispatches get logging, history, token accounting, quota-aware fallback, and observation surfaces for free. Use your shell for ad-hoc work outside the registry.
Core loop
list_projects— see the portfolio (name, agent, path, tags). Passworkspace="__all__"for every workspace.dispatch(name, prompt)— run the project's agent non-interactively in its cwd. Non-blocking: returns adispatch_idin <100 ms while the agent works in the background.check_dispatch(dispatch_id)— poll.{status: "running", elapsed_sec}while alive; the full result (output,tokens,duration_sec) once finished.cancel_dispatch(dispatch_id)— abort a runaway dispatch.
dispatch(name="my-app", prompt="Run the test suite and fix any failures")
→ {dispatch_id: "a1b2c3d4"}
check_dispatch(dispatch_id="a1b2c3d4")
→ {status: "running", elapsed_sec: 42.0} # later: full result
Coding dispatches routinely take 1–15 minutes. Do not busy-wait: check once ~every 3 s only if the user is waiting on the answer; otherwise report the dispatch_id, move on, and re-check on your next turn, heartbeat, or cron tick. Every central-mcp tool response also piggybacks completions that finished since your last call, so any later tool use surfaces finished work automatically.
Fan-out
dispatch(name="@workspace-name", prompt=...) sends one prompt to every project in that workspace at once and returns one dispatch_id per project. Good for portfolio-wide chores ("update CI config", "audit dependencies").
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 89 lines · 28 tokens per session scan A 62744cd4ae33
central-mcp is a skill published in the GitHub repository andy5090/central-mcp (5 stars, last pushed yesterday), licensed MIT. It adds 28 tokens to every session and 1,588 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-08.
Other skills, from other repositories
dispatch
Use when a task file exists in .hyperflow/tasks/ and workers need dispatching. Fans out parallel workers under per-batch Reviewers, runs a final integration review, and commits per sub-task. Endpoint of the auto-chain — no auto-deploy. Trigger with /hyperflow:dispatch, "run the plan", "execute the task", "build it"…
atmos-migration
This skill helps you migrate a repository to Atmos. It covers native Terraform, Terraform Workspaces, Terramate, Terragrunt, Makefiles, Justfiles, and Taskfiles. It gives minimum-disruption paths, file-layout options, workspace mapping, task-to-command mapping, generatehcl/script decomposition, and the remote-state…
atmos-modernization
Atmos Modernization: migrate deprecated or legacy Atmos patterns to current names, Native CI, Atmos Pro drift detection, dependencies.components, nametemplate, and declared secrets.
atmos-init
Bootstrapping new Atmos projects with atmos init: built-in template catalog, differences from atmos scaffold generate, project record, and update-safe 3-way merge.
atmos-workflows
Workflow automation: native step types, multi-step workflows, parallel/matrix/wait/container/emulator steps, when: conditions (CEL), require/assert preconditions, output steps, retries, dependencies, and cross-component orchestration.
atmos-config
Atmos root configuration: atmos.yaml discovery, precedence, deep merging, basepath, imports, minimal bootstrap, and routing to narrower Atmos skills.