Products

TokenHunger

AI-nativeMCP

Find the cheapest model that actually passes your tests.

tokenhunger.com SourceAI Models & Agents / Prompts, Evals & LLM Observability

AI Benchmark
Desktop
Mobile
Monthly visits
None yet
No traffic data yet
Public revenue
Undisclosed
No public revenue evidence yet
Entry price
Usage-based
No monthly subscription pricing
Launched
5mo ago
2026-06-30 · Est.

Traffic

Last 12 months
Monthly visits

No traffic data yet.

Events1 marketing move

Marketing moves

Launches, search & content, referrals, promotions
  • Launched on Product HuntLaunch

    Find the cheapest model that still passes your task

    Jun 30 · 5mo agoLaunch page

Open Source & Agent Ecosystem

GitHub · MCP / Skill
Last commit 2026-07-02
GitHub Stars
Public repo
Forks
—
License
See repository
Primary language
—

Agent, MCP & Developer Integration

MCP ServerCLI / SDK
Integration docs
Ecosystem & integrations:
GitHubQualityMax
Browse all MCP Server products →

Traffic sources

Traffic breakdown

No traffic channel or country breakdown data for this website yet.

Search

Domain authority —Domain registered 2026-06-12

No search keyword data for this website yet.

Traffic data: Vaneform

Pricing

Usage-based pricing; no fixed plans listed on website.

Trial: None · Observed 2026-11-06 · Source page

Pages & changes

Tracked since 2026-06-30

Key pages

Weekly snapshots
tokenhunger.com/ Snapshot 2026-11-06

Changes

No pricing, plan, or positioning changes detected since tracking started.

Questions & evidence

What is TokenHunger and what platforms does it support?
TokenHunger is catalogued under Prompts, Evals & LLM Observability: Find the cheapest model that actually passes your tests.. Supported platforms: MCP Server, CLI / SDK.
Is TokenHunger open source?
TokenHunger has a public repository (https://github.com/Desperado/token-hunger) with its source repository published.Source

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AI Models & Agents / Prompts, Evals & LLM Observability

These products share a catalog category. Compare customer tasks, features and deployment requirements before treating them as alternatives.