compare_pricing

Instructions

Implementation Reference

• src/index.ts:228-281 (registration)

  Registration of the 'compare_pricing' tool via server.tool() with name 'compare_pricing' and description 'Rank AI models by total cost for a given token workload.'

  server.tool(
    'compare_pricing',
    'Rank AI models by total cost for a given token workload. Useful for finding the cheapest model for your use case.',
    {
      input_tokens: z.number().int().min(1).describe('Number of input tokens per request'),
      output_tokens: z.number().int().min(0).default(0).describe('Number of output tokens per request'),
      filter: z.string().optional().describe('Narrow to a provider or model family — e.g. "claude", "gpt", "gemini"'),
      top: z.number().int().min(1).max(30).optional().describe('Show only the N cheapest models (default 10)'),
    },
    async ({ input_tokens, output_tokens, filter, top = 10 }) => {
      const data = await fetchJSON<{ models: PricingRow[] }>('/pricing')
      let models = data.models
      if (filter) {
        const q = filter.toLowerCase()
        models = models.filter(
          (m) => m.model_name.toLowerCase().includes(q) || m.tool_name.toLowerCase().includes(q)
        )
      }
  
      const ranked = models
        .map((m) => ({
          ...m,
          total: (input_tokens / 1_000_000) * m.input_per_1m + (m.output_per_1m !== null ? (output_tokens / 1_000_000) * m.output_per_1m : 0),
        }))
        .sort((a, b) => a.total - b.total)
        .slice(0, top)
  
      if (!ranked.length) {
        return { content: [{ type: 'text' as const, text: 'No models found for that filter.' }] }
      }
  
      const cheapest = ranked[0].total
      const fmt = (n: number) => n < 0.001 ? `$${n.toFixed(6)}` : `$${n.toFixed(4)}`
      const col = (s: string, w: number) => s.length > w ? s.slice(0, w - 1) + '…' : s.padEnd(w)
  
      const header = `${'#'.padStart(2)}  ${col('Model', 36)} ${col('Tool', 18)} ${'Cost'.padStart(10)}  vs cheapest`
      const sep = '─'.repeat(header.length)
      const rows = ranked.map((m, i) => {
        const mult = i === 0 ? '(cheapest)' : `${(m.total / cheapest).toFixed(1)}× more`
        return `${String(i + 1).padStart(2)}  ${col(m.model_name, 36)} ${col(m.tool_name, 18)} ${fmt(m.total).padStart(10)}  ${mult}`
      })
  
      return {
        content: [{
          type: 'text' as const,
          text: [
            `Cost for ${input_tokens.toLocaleString()} input + ${output_tokens.toLocaleString()} output tokens:`,
            '', header, sep, ...rows, '',
            'Full calculator: https://tickerr.ai/token-counter',
          ].join('\n'),
        }],
      }
    }
  )

• src/index.ts:231-236 (schema)

  Input schema for compare_pricing: input_tokens (required int), output_tokens (default 0), filter (optional string), top (optional int, default 10).

  {
    input_tokens: z.number().int().min(1).describe('Number of input tokens per request'),
    output_tokens: z.number().int().min(0).default(0).describe('Number of output tokens per request'),
    filter: z.string().optional().describe('Narrow to a provider or model family — e.g. "claude", "gpt", "gemini"'),
    top: z.number().int().min(1).max(30).optional().describe('Show only the N cheapest models (default 10)'),
  },

• src/index.ts:237-280 (handler)

  Handler function that fetches /pricing, filters models by optional filter string, calculates total cost per model based on input/output tokens, sorts by cheapest, and returns a ranked table of the top N models.

  async ({ input_tokens, output_tokens, filter, top = 10 }) => {
    const data = await fetchJSON<{ models: PricingRow[] }>('/pricing')
    let models = data.models
    if (filter) {
      const q = filter.toLowerCase()
      models = models.filter(
        (m) => m.model_name.toLowerCase().includes(q) || m.tool_name.toLowerCase().includes(q)
      )
    }
  
    const ranked = models
      .map((m) => ({
        ...m,
        total: (input_tokens / 1_000_000) * m.input_per_1m + (m.output_per_1m !== null ? (output_tokens / 1_000_000) * m.output_per_1m : 0),
      }))
      .sort((a, b) => a.total - b.total)
      .slice(0, top)
  
    if (!ranked.length) {
      return { content: [{ type: 'text' as const, text: 'No models found for that filter.' }] }
    }
  
    const cheapest = ranked[0].total
    const fmt = (n: number) => n < 0.001 ? `$${n.toFixed(6)}` : `$${n.toFixed(4)}`
    const col = (s: string, w: number) => s.length > w ? s.slice(0, w - 1) + '…' : s.padEnd(w)
  
    const header = `${'#'.padStart(2)}  ${col('Model', 36)} ${col('Tool', 18)} ${'Cost'.padStart(10)}  vs cheapest`
    const sep = '─'.repeat(header.length)
    const rows = ranked.map((m, i) => {
      const mult = i === 0 ? '(cheapest)' : `${(m.total / cheapest).toFixed(1)}× more`
      return `${String(i + 1).padStart(2)}  ${col(m.model_name, 36)} ${col(m.tool_name, 18)} ${fmt(m.total).padStart(10)}  ${mult}`
    })
  
    return {
      content: [{
        type: 'text' as const,
        text: [
          `Cost for ${input_tokens.toLocaleString()} input + ${output_tokens.toLocaleString()} output tokens:`,
          '', header, sep, ...rows, '',
          'Full calculator: https://tickerr.ai/token-counter',
        ].join('\n'),
      }],
    }
  }