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TokenZero

by io.github.tokenzero-ai
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Server Details

LLM cost optimization gateway, repo token-waste auditor & model arbitrage MCP server.

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Status
Healthy
Uptime
100.0% over the last 24 hours
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
URL
Repository
tokenzero-ai/tokenzero
GitHub Stars
0
Server Listing
@tokenzero/mcp
ChatGPT
–
Claude
–

TDQS

A4/5.0

Scored across 6 tools

Disambiguation4/5

The tools mostly have distinct purposes: auditing a repo, pricing model options, rewriting a request payload, creating a workspace, trying the service, and viewing workspace metrics. There is some overlap between try_tokenzero and optimize_prompt_payload/calculate_model_arbitrage because the trial demonstrates similar savings engines, but the descriptions clarify that one is a demo/first-call and the others are concrete operations.

Naming Consistency4/5

Most names follow a readable snake_case verb_noun or action_target pattern: audit_repo_token_waste, calculate_model_arbitrage, optimize_prompt_payload, provision_workspace. try_tokenzero is less descriptive, and workspace_metrics is noun-only rather than verb-led, but the overall convention is predictable.

Tool Count5/5

Six tools is well-scoped for a token-optimization service: one audit, one pricing calculator, one payload optimizer, one provisioning tool, one trial tool, and one metrics dashboard. Each tool appears to earn its place without excessive surface area.

Completeness4/5

The surface covers the key lifecycle: try the product, audit waste, price alternatives, optimize payloads, provision a workspace, and monitor metrics. Minor gaps exist around workspace management, such as listing or deleting workspaces and rotating keys, but the core workflows are present.

Available Tools

6 tools
audit_repo_token_wasteAudit a repo for LLM token wasteAInspect

No API key needed. Static-analyze a public GitHub repo (e.g. {"repo": "owner/name"}) or a set of source files for LLM token waste: uncached static prompts, frontier models on extraction tasks, hot loops, non-deterministic repeat calls, and prompt-caching mis-integration (caching gated on model names, volatile values in the system prompt, random ids in history, wrong-provider cache markers, misplaced breakpoints, cost math that ignores cached tokens). Returns findings with fixes and an estimated recoverable percentage.

Inputs: repo, files.

calculate_model_arbitragePrice a workload across modelsA
Read-onlyIdempotent
Inspect

No API key needed; only model is required (e.g. {"model": "gpt-6.1-sol"}, defaults 2,000 tokens in and 400 out). Price a workload at list prices across models: cost per request and per month for the requested model, its cheaper sibling, and the effect of prompt caching. The result names the pricing table version it used.

Inputs: model (required), compare_to, input_tokens, output_tokens, +2 more.

optimize_prompt_payloadMake a request body cache-friendlyA
Read-onlyIdempotent
Inspect

No API key needed. Rewrite an OpenAI Chat/Responses or Anthropic Messages request body so its static prefix is provider-cacheable (Anthropic cache_control breakpoints, OpenAI prompt_cache_key). Returns the optimized body, what changed, the token profile and the projected per-request saving. Never changes the tokens the model sees.

Inputs: body (required), endpoint, strategy.

provision_workspaceCreate a free TokenZero workspaceAInspect

Create a TokenZero workspace and key with no form. Returns the key once, the base URLs that route through it (OPENAI_BASE_URL / ANTHROPIC_BASE_URL), the one-click dashboard link and the badge URL. Free up to the monthly free tier; nothing is billed.

Inputs: name.

try_tokenzeroTry TokenZero (no key needed)A
Read-only
Inspect

Call this first: no API key, no signup, no setup. Shows what TokenZero would do to one of your LLM calls: it runs the four savings engines (prompt-cache formatting, edge cache, cascade advice, signed receipt) on a sample or your own prompt and model, and returns the list-price saving, the signed receipt and a copy-paste keyless curl that makes a real call on a free model. Pass {} for the default, or {"model": "gpt-6.1-sol", "system": "...", "prompt": "..."}.

Inputs: model, prompt, system.

workspace_metricsRead a workspace savings scorecardA
Read-onlyIdempotent
Inspect

Live value scorecard for a TokenZero workspace: hard savings and net ROI per window, the four engines' contribution, speed, parity, availability and privacy posture, per-model breakdown and one-click recommendations. Needs the workspace key (tz_live_…); pass demo: true for a labelled sample.

Inputs: key, demo, window.

Tool Schema Changelog

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