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Tokencap

Token budget enforcement across your AI agents

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I built this after hitting the same wall repeatedly — no good way to enforce token budgets in application code. Provider caps are account-level and tell you what happened, not what is happening.Two ways to add it: # Direct client wrapper client = tokencap.wrap(anthropic.Anthropic(), limit=50_000) # LangChain, CrewAI, AutoGen, etc. tokencap.patch(limit=50_000) Four actions at configurable thresholds: WARN, DEGRADE (transparent model swap), BLOCK, and WEBHOOK. SQLite out of the box, Redis for multi-agent setups.One design decision worth mentioning: tokencap tracks tokens, not dollars. Token counts come directly from the provider response and never drift with pricing changes.Happy to answer any questions.

HN · launched Apr 4, 2026 · 7 upvotes (top 61%) · 0 views

Niche: llm cost monitoring tools · 49 launches, 2 in the last 7 days ▼ -60% · Explore this niche →

Category and tags

  • Horizontal
  • Compliance & governance
  • Developer
  • AI-native
  • Commercial product

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Could you build this?

Yes It is an SDK middleware/wrapper around LLM client libraries that tracks token usage per request and enforces client-side spending limits.

Discussion

No comments on this launch.

Competitors

Other products that read as similar to this one : 265 launches clear the similarity bar, closest 8 shown.

Attention rank: #123 of 266 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 155 days after the earliest competitor.

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