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Spend Control for LangGraph

LangGraph turns agents into graphs — and graphs fan out. A single node calling a paid tool in a loop, or a swarm of subagents spending in parallel, compounds costs faster than any prompt can police.

Why LangGraph agents overspend

Subagent fan-out: one graph step can spawn dozens of agents, each with its own tool calls.

Retry loops on a failing node re-run paid tools automatically.

The graph's parallel branches can all hit the same vendor in the same window.

How it works

Call sipi.bot from any node before a spend — via the MCP tool or a one-line HTTP request. The graph continues on APPROVED, short-circuits on BLOCKED, and routes FLAGGED to a human checkpoint.

Rules that fit graph workflows

Shared daily cap across the whole graph — the fleet can't compound one mistake.

Velocity limit per node so a retry loop dies fast.

Category rule so research nodes can buy data but never anything else.

HTTP call from a node

import requests

resp = requests.post(
    "https://sipi.bot/v1/transactions/evaluate",
    json={"amount": 800, "merchant": "data-vendor.com", "category": "data"},
    headers={"Authorization": "Bearer YOUR_KEY"},
)
decision = resp.json()["decision"]  # APPROVED | BLOCKED | FLAGGED

Deterministic, ~5 ms, no model call. Add it in the node that spends.

FAQ

Can sipi.bot limit parallel subagents?

Yes — a shared daily ceiling and velocity limit apply across the whole graph, so parallel branches can't compound one mistake.

Does it add latency to graph nodes?

About 5 ms per spend check — negligible next to tool call latency.

What if a node's legit spend gets flagged?

FLAGGED routes to your human approval queue. The graph can pause at a checkpoint while the human reviews.

Stop the next $12,400 night.

One API call (or MCP tool) in front of every agent transaction — APPROVED, BLOCKED, or FLAGGED, deterministic, ~5 ms, fully logged.

See plans — from $99/mo Try a live check