Hi @KnockOutEZ,
Love the work on KnockOutEZ/wigolo! As usage grows across AI agent frameworks, server compute costs can start adding up quickly. We've also seen developers report that their autonomous agents accidentally burn through thousands of dollars in a single session because traditional payment rails lack built-in agent guardrails.
Would you be open to adding an optional usage metering & billing decorator using neuforge-pay? It acts as a proactive Spend Firewall and Merchant of Record for MCP servers. In 3 lines of code, it meters tokens, calculates live LLM COGS, and proactively blocks agent transactions that exceed a strict session budget limit (to prevent surprise bills).
Example Integration:
from neuforge_pay import meter_endpoint
@app.get("/v1/query")
@meter_endpoint(price_charged_usd=0.05, model_name="claude-3-5-sonnet", session_budget_usd=10.00)
async def query_endpoint():
...Happy to submit a clean PR if this aligns with your roadmap!
Hi @KnockOutEZ,
Love the work on
KnockOutEZ/wigolo! As usage grows across AI agent frameworks, server compute costs can start adding up quickly. We've also seen developers report that their autonomous agents accidentally burn through thousands of dollars in a single session because traditional payment rails lack built-in agent guardrails.Would you be open to adding an optional usage metering & billing decorator using
neuforge-pay? It acts as a proactive Spend Firewall and Merchant of Record for MCP servers. In 3 lines of code, it meters tokens, calculates live LLM COGS, and proactively blocks agent transactions that exceed a strict session budget limit (to prevent surprise bills).Example Integration:
Happy to submit a clean PR if this aligns with your roadmap!