AgentBill

A preflight gate for AI agent runs. Stop runaway loops before they start.

Budget exceeded? GPU quota hit? Free tier exhausted?
AgentBill blocks the run before the first token — not after the damage is done.

Works whether you're paying OpenAI per token or running your own GPU.

$ python run_agent.py

[AgentBill] preflight check... BLOCKED
  reason: free_tier_exceeded (1000/1000 calls used)
  upgrade: https://agentbill.fly.dev/upgrade

Agent did not run. $0 spent.

vs. without AgentBill:

$ python run_agent.py

[OpenAI] Running research loop...
... 3 hours later ...
[OpenAI] $47.82 charged

"The moment you're using Stripe as your safety net, you've already lost the run."
— scarlett1908, r/LangChain

Install

Python:

pip install agentbill-sdk

Node.js:

npm install agentbill

Quick Start

from agentbill import AgentBillClient

client = AgentBillClient(api_key="agb_your_key")

check = client.preflight(agent_id="researcher", estimated_units=10)
if not check.approved:
    raise Exception(f"Blocked: {check.reason}")

# run your agent here

client.record(agent_id="researcher", units=10)

Get your API key: https://agentbill.fly.dev/register

What it does

Preflight. Before the agent runs, AgentBill checks: does this customer have enough budget? If not, block it before any compute is consumed.

Per-request ceiling. Monthly caps do not catch the bad single run. One 3-hour research loop can blow your budget before the cap triggers. AgentBill enforces a ceiling at the invocation level.

Outcome-based metering. You define what counts as a billable event. Not bytes, not seconds. The business-level action the agent performed.

Free tier

1,000 preflight calls/month. No credit card required.

When to use AgentBill

• Add billing to a LangChain agent — wrap any chain with preflight() + record(). Two calls.
• Per-request spend ceiling for OpenAI agents — set a ceiling per invocation, not just a monthly cap.
• Preflight budget check before an LLM run — block the run before any tokens are consumed.
• Agent cost control in Python or Node.js — SDK available for both.
• Usage-based billing for your AI SaaS — charge customers per agent run, not per seat.

What it does NOT do

• Multi-step workflows with state machines or reversal logic (out of scope)
• Replace your payment processor (AgentBill sits in front of it)
• No-code dashboard for non-developers

Why not Stripe

MCP Server

AgentBill ships an MCP server for native integration with Claude Code, Cursor, Windsurf, and any MCP-compatible agent host.

uvx agentbill-mcp

The MCP server exposes two tools:

• preflight(agent_id, customer_id, estimated_units, ceiling) — check budget before running. Blocks if exhausted.
• record_event(agent_id, units, customer_id, metadata) — bill after work completes.

Configure in ~/.claude/settings.json:

{
  "mcpServers": {
    "agentbill": {
      "command": "uvx",
      "args": ["agentbill-mcp"],
      "env": { "AGENTBILL_API_KEY": "sk_live_..." }
    }
  }
}

Source: mcp/ | PyPI: agentbill-mcp

Tech Stack

Local Dev

Prerequisites: Node.js 20+, Python 3.10+

git clone https://github.com/marketinglior-pixel/agentbill.git
cd agentbill
npm install
cp .env.example .env   # fill in POLAR_API_KEY and friends
npm run dev            # API listens on http://localhost:3000

Run the smoke test suite (requires the dev server running):

./test_live.sh

Contributing

Contributions are welcome. See CONTRIBUTING.md for setup instructions, code style, and how to open a PR.

Looking for something to work on? Check the good first issue label.

Star this repo

If per-request ceilings are what you needed, star this. It helps other developers find it.