drift — mandate enforcement for AI agents is answering right now. Last checked 4 min ago. It exposes 3 tools. Last commit 24 Oct 2026.
Block an action a signed mandate does not permit: amount, payee, audience, currency, window, intent.
We read the source, 1 d ago · tools taken from the live server · rules 995398eba69f
What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.
return subprocess.run(cmd, capture_output=True, text=True,
Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.
We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.
Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 4 min ago.
claude mcp add drift --transport http https://drift.rta.lat/mcp
https://drift.rta.lat/mcp
[mcp_servers.drift]
url = "https://drift.rta.lat/mcp"
{
"mcpServers": {
"drift": {
"url": "https://drift.rta.lat/mcp"
}
}
}
{
"servers": {
"drift": {
"type": "http",
"url": "https://drift.rta.lat/mcp"
}
}
}
Read directly from the server with tools/list, grouped by what they act on.
If a tool disappears, we record the date.
drift_check
drift_explain
drift_session
| URL | Transport | State | Latency | Checked |
|---|---|---|---|---|
| https://drift.rta.lat/mcp | streamable-http | answering | 861 ms | 4 min ago |
Intent-bound action authorization for AI agents: policy, human approval, and a signed audit trail.
Pre-action authorization for AI agents: permit, deny or escalate against a signed delegation chain.
Owner-signed permissions for AI agent actions; ALLOW/BLOCK/REVIEW with request-bound receipts.
Check an agent action against its operator's mandate before acting: permit, deny or escalate.
Deterministic payment policy guardrail for AI agents - budgets, allowlists, signed mandates.
Deterministic policy enforcement and MCP management for AI agent tool calls.
MCP enforcement layer that intercepts AI agent actions and blocks rule violations before execution.
AI document intelligence: extract, summarize, claim-check, notarize, and signed action receipts.
Answers built from our own checks of this server.