Feature Suggestion: Optional token metering & paid API key support via `neuforge-pay`
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- Dominant language
- Python
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Description
Hi @Zipstack,
Love the work on Zipstack/unstract! 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!
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue names no repository files or tests; start by locating the API or MCP server entry points corresponding to the example /v1/query endpoint. Review how optional integrations and API keys are handled, then define the scope for token metering, paid keys, and session budget enforcement before implementation. Done should include agreed behavior and tests for the optional integration.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- api, backend
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100