sentinel-agent-trust-crewai

CrewAI adapter for Sentinel AI — the identity & governance layer for AI agents. Wrap any CrewAI tool so that every call is authorized (and audited) by the Sentinel gateway before it runs: your tool code and your crew stay untouched.

Sentinel is in private beta. For source access, a hosted sandbox organization key, or to collaborate: cosimo@plannest.net

Install

pip install sentinel-agent-trust-crewai

Quickstart

import os
from crewai import Agent
from crewai.tools import tool
from sentinel_crewai import SentinelGuard

@tool("create_refund")
def create_refund(customer: str, amount: float) -> str:
    """Issue a refund to a customer."""
    return billing.refund(customer, amount)

guard = SentinelGuard(
    agent_id="agt_...",
    private_key=os.environ["SENTINEL_AGENT_PRIVATE_KEY"],  # base64 Ed25519 seed
    gateway_url="https://your-gateway.example.com",
)

agent = Agent(
    role="billing assistant",
    goal="handle refunds within policy",
    backstory="…",
    tools=guard.wrap_all([create_refund]),   # ← the only change to your crew
)

Every tool call is signed with the agent's Ed25519 key and checked against your policies in real time. The wrapped tool keeps the same name, description, and argument schema — the LLM sees no difference.

What the model sees

Sentinel's decision comes back as the tool's observation (the underlying tool is never executed unless the gateway approves):

This mapping is what keeps agents out of retry loops: a policy denial reads as a hard "no", an approval-pending reads as "park it", an outage reads as "try again shortly".

Mapping tools to your policy taxonomy

By default a tool named create_refund is authorized as action tool.create_refund on resource tool://create_refund (tool names with spaces are slugified), so a single policy with action_pattern: "tool.*" governs every wrapped tool. For business-level policies, map tools explicitly:

tools = guard.wrap_all(
    [create_refund, read_contact],
    overrides={
        "create_refund": {"action": "crm.refund.create", "resource": "crm://refunds"},
        "read_contact":  {"action": "crm.contact.read",  "resource": "crm://contacts/*"},
    },
)

…and the policy on the Sentinel side:

{
  "action_pattern": "crm.refund.create",
  "constraints": {"max_amount": 5000, "max_total_amount_per_day": 20000},
  "approval_thresholds": {"amount": 500}
}

Each refund ≤ 5000, at most 20 000/day in total, and a human approves anything from 500 up — enforced outside the model, no prompt engineering.

The tool's keyword arguments are sent as the action payload, so constraints like max_amount apply to the actual amount argument the model chose.

Demo

With the repo's demo gateway running (cd gateway && go run .):

pip install -e sdk/python -e sdk/adapters/crewai
python examples/crewai_crm_agent.py

See also

• sentinel-agent-trust-langchain — the LangChain twin of this adapter
• sentinel-agent-trust — the underlying Python SDK (includes proxy mode)

License

Apache 2.0 (the adapter and SDKs). The Sentinel platform is licensed separately under BSL 1.1 — see the repository root.