AgentBill
AgentBill is an MCP server that provides preflight spend checks and post-execution usage billing for AI agents.
About
io.github.marketinglior-pixel/agentbill-mcp (AgentBill) is MCP billing infrastructure for AI agents: it supports checking whether a run is within budget before execution and recording usage afterward for billing. developers shipping agent products often validate pricing late and get surprised by token or tool costs—this server is meant to sit in the MCP graph so Claude Code or custom agents can ask “can we afford this?” and then report consumption. It fits Validate when you are modeling per-seat, per-task, or metered AI pricing and need a protocol-native hook rather than a one-off spreadsheet. Early v0.1.1 signals evolving APIs; treat it as integration glue paired with your AgentBill account and product rules. Category is Finance because the outcome is controlled spend and billable usage events.
- AgentBill MCP (agentbill-mcp on PyPI, v0.1.1) with stdio transport
- Preflight spend checks before expensive agent runs
- Post-execution usage billing to record what actually consumed budget
- Billing infrastructure aimed at AI agents, not generic e-commerce carts
AgentBill by the numbers
- Data as of Jul 7, 2026 (Skillselion catalog sync)
claude mcp add agentbill-mcp -- uvx agentbill-mcpAdd your badge
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| Package | agentbill-mcp |
|---|---|
| Transport | STDIO |
| Auth | None |
What it does
Attach preflight spend checks and post-execution usage billing to agent workflows before you scale paid AI features.
Who is it for?
Best when you're prototyping metered or usage-based AI products and want billing hooks in the agent loop early.
Skip if: Static sites with no agent spend, or teams that already use a full payments stack without MCP integration needs.
What you get
After install, agents can run preflight spend checks and emit post-execution usage events through MCP for pricing experiments.
- Preflight spend decision before agent execution
- Post-execution usage records for billing analysis
- MCP-native billing layer for agent prototypes
By the numbers
- [object Object]
- [object Object]
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Agent usage billing MCP, not a generic Stripe checkout skill or infrastructure monitor.
FAQ
Who is AgentBill for?
Developers and small teams shipping AI agents who need spend guardrails and usage billing wired through MCP during pricing validation.
When should I use AgentBill?
Use it while validating pricing—before scaling paid agent features—when you need preflight budget checks and post-run usage capture.
How do I add AgentBill to my agent?
Install agentbill-mcp from PyPI, configure stdio MCP in your agent per AgentBill docs, supply API credentials from your billing account, and invoke preflight then post-execution billing tools in your workflow.