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Permission-gated superuser (sysadmin) MCP server: lets AI agents manage a machine behind guardrails, approvals and an append-only audit log. pip install superuser

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Super

A permission-gated superuser agent exposed over the Model Context Protocol (MCP). It gives an AI agent real system-administration powers on this machine — running shell commands, checking system state, and acting on GitHub — while wrapping every action in guardrails: a dangerous-command denylist, a human-approval gate for risky operations, least-privilege GitHub access, an append-only audit log, and Cisco AI Defense runtime inspection of every tool call and response.

The design goal is the version of a "superuser agent" you can actually ship: powerful, but safe, auditable, and compatible with enterprise guardrails.

Landing site: https://fitzyracing1.github.io/super-landing/ (source: fitzyracing1/super-landing). The previous Pages site in this repo is preserved at tag site-v1 / branch site-archive.

Why it's built this way

An agent that can do anything as root is a liability, not a product. Buyers (and marketplace security reviews) expect scoping, approvals, and an audit trail. So capabilities here always pass through a single choke point — the Guard — which enforces, in order:

  1. Cisco AI Defense inspects the tool call (can block).
  2. Cisco Duo Agentic Identity authorizes the tool call per-policy (can block).
  3. Approval gate — anything at or above approval_required_at (default MEDIUM) needs an explicit confirm=true from a human.
  4. The operation runs.
  5. Cisco AI Defense inspects the response before it is returned (catches data leakage).
  6. Stripe meters the successful call (best-effort; never blocks).
  7. The outcome is written to the audit log as human owner -> agent -> tool -> action -> outcome.

This mirrors the enterprise model: your app owns scoping + approvals + local audit; Cisco AI Defense provides runtime threat inspection at the MCP layer; Cisco Duo Agentic Identity provides per-tool-call authorization tied to an accountable human owner; and Stripe turns metered tool calls into revenue.

Cisco Duo Agentic Identity (authorization)

Duo follows a "Duo decides, the gateway enforces" model. This agent registers as a non-human identity, authenticates via the OAuth 2.1 client-credentials grant (with an RFC 8707 resource indicator), and authorizes every tool call either by matching the tool's required scope against what Duo granted, or by calling an explicit Duo decision endpoint. Set DUO_ENABLED=true plus DUO_TOKEN_URL / DUO_CLIENT_ID / DUO_CLIENT_SECRET (see .env.example). When Duo is not configured, calls are allowed but flagged governed: false; in enforce mode authorization errors fail closed.

Stripe usage-based billing (monetization)

Each authorized, successful tool call emits a Stripe meter event (v2 billing meter events API), so the agent can be sold per-action. Configure a meter in Stripe, then set STRIPE_ENABLED=true, STRIPE_API_KEY, STRIPE_CUSTOMER_ID, and STRIPE_METER_EVENT_NAME. Per-tool weights let higher-risk actions cost more. Billing is best-effort: metering failures are logged and never block or fail the tool call (results are annotated billed: true|false).

Tools

Tool Risk Notes
system_status LOW Host, CPU, memory, uptime
disk_usage LOW Per-partition disk usage
list_processes LOW Top processes by memory/cpu
run_command HIGH* Shell command; denylist + approval + audit
github_get_repo LOW Repo metadata (allowlisted repos only)
github_list_issues LOW Issues for an allowlisted repo
github_create_issue_comment HIGH Write; needs approval + GITHUB_ALLOW_WRITES
security_status — Reports the active guardrail configuration

* run_command is LOW risk only when its base command is in command_allowlist; otherwise HIGH (requires confirm=true).

Install

Not yet on PyPI. Install straight from git:

pip install "superuser @ git+https://github.com/fitzyracing1/Super.git"
pip install "superuser[all] @ git+https://github.com/fitzyracing1/Super.git"   # + Cisco AI Defense + Stripe SDKs

From a clone:

Requires Python 3.10+.

pip install -e .              # core agent (Duo authz uses requests; no extra dep)
pip install -e '.[security]'  # + Cisco AI Defense SDK (cisco-aidefense-sdk)
pip install -e '.[billing]'   # + Stripe SDK (usage-based billing)
pip install -e '.[all]'       # security + billing
pip install -e '.[dev]'       # + pytest / ruff

Configure

Copy .env.example to .env (or use a YAML file — see superuser.example.yaml) and set values. Key settings:

  • SUPERUSER_HUMAN_OWNER — the human accountable for the agent's actions.
  • SUPERUSER_APPROVAL_AT — risk threshold for the approval gate (LOW…CRITICAL).
  • AI_DEFENSE_* — Cisco AI Defense credentials/mode (see below).
  • DUO_* — Cisco Duo Agentic Identity authorization (see below).
  • STRIPE_* — Stripe usage-based billing (see below).
  • GITHUB_TOKEN, GITHUB_ALLOWED_REPOS, GITHUB_ALLOW_WRITES — least-privilege GitHub.

For a full console-value → env-var mapping for all three services, see docs/INTEGRATIONS.md.

Cisco AI Defense

Install the SDK (pip install 'superuser[security]') and provide credentials:

  • Explicit inspection of this server's own tool calls/responses: set AI_DEFENSE_INSPECTION_API_KEY.
  • Runtime protection (agentsec.protect() auto-patches LLM + MCP clients): set AI_DEFENSE_API_MODE_LLM_ENDPOINT + AI_DEFENSE_API_MODE_LLM_API_KEY, or point AI_DEFENSE_AGENTSEC_CONFIG at an agentsec.yaml (see agentsec.example.yaml).
  • AI_DEFENSE_MODE: enforce (block), monitor (log only), or off.

If the SDK is not installed or no credentials are set, the agent still runs but every result is annotated protected: false / UNPROTECTED — the gap is never silent. In enforce mode, inspection errors fail closed (the call is blocked); in monitor mode they fail open (logged, allowed).

Environment variables

Area Variables
Core SUPERUSER_CONFIG, SUPERUSER_HUMAN_OWNER, SUPERUSER_APPROVAL_AT, SUPERUSER_COMMAND_TIMEOUT, SUPERUSER_AUDIT_LOG
Cisco AI Defense AI_DEFENSE_ENABLED (default true; set false for local dev), AI_DEFENSE_MODE, AI_DEFENSE_INSPECTION_API_KEY, AI_DEFENSE_API_MODE_LLM_ENDPOINT, AI_DEFENSE_API_MODE_LLM_API_KEY, AI_DEFENSE_AGENTSEC_CONFIG
Cisco Duo DUO_ENABLED, DUO_MODE, DUO_AGENT_ID, DUO_TOKEN_URL, DUO_CLIENT_ID, DUO_CLIENT_SECRET, DUO_AUTHORIZATION_URL, DUO_RESOURCE, DUO_SCOPES
Stripe STRIPE_ENABLED, STRIPE_API_KEY, STRIPE_CUSTOMER_ID, STRIPE_METER_EVENT_NAME, STRIPE_DEFAULT_VALUE
GitHub GITHUB_TOKEN, GITHUB_ALLOWED_REPOS, GITHUB_ALLOW_WRITES, GITHUB_API_URL

With no keys set the server still runs: Duo and Stripe are off by default, and Cisco AI Defense runs unprotected (clearly flagged) if the SDK/keys are missing.

Run

# Validate configuration and print guardrail/Cisco status, then exit:
superuser --check

# Start the MCP server (stdio transport, for MCP clients like Cursor/Claude):
superuser
# or: python -m superuser

Register with an MCP client

Example client config (stdio):

{
  "mcpServers": {
    "superuser": {
      "command": "superuser",
      "env": {
        "SUPERUSER_HUMAN_OWNER": "you@example.com",
        "AI_DEFENSE_MODE": "enforce",
        "AI_DEFENSE_INSPECTION_API_KEY": "..."
      }
    }
  }
}

Test

pytest

Security notes

  • The dangerous-command denylist is a backstop, not the primary control. The primary controls are Cisco AI Defense inspection and the approval gate.
  • GitHub access fails closed: no token or an empty repo allowlist means no access. Use a fine-grained, least-privilege token.
  • Secrets are redacted in the audit log. Keep .env / *.yaml config files out of version control (already in .gitignore).

License

Apache-2.0.

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Permission-gated superuser (sysadmin) MCP server: lets AI agents manage a machine behind guardrails, approvals and an append-only audit log. pip install superuser

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