io.github.jeff-atriumn/tokencost-dev

Install in 30 seconds

Claude Code:

claude mcp add tokencost-dev -- npx -y tokencost-dev

Then ask: "How much would 1M input tokens cost on claude-sonnet-4-5?"

Cursor (.cursor/mcp.json):

{
  "mcpServers": {
    "tokencost-dev": {
      "command": "npx",
      "args": ["-y", "tokencost-dev"]
    }
  }
}

No API keys. No accounts. No configuration files. Pricing data is fetched from the LiteLLM community registry and cached locally for 24 hours.

Tools

get_model_details

Look up pricing, context window, and capabilities for any model. Fuzzy matching means "sonnet 4.5" works just as well as "claude-sonnet-4-5-20250514".

> "What are Claude Sonnet 4.5's pricing and capabilities?"

Model: claude-sonnet-4-5
Provider: anthropic | Mode: chat

Pricing (per 1M tokens):
  Input:  $3.00
  Output: $15.00

Context Window:
  Max Input:  200K
  Max Output: 8K

Capabilities: vision, function_calling, parallel_function_calling

calculate_estimate

Estimate cost for a given number of input and output tokens.

> "How much will 1000 input + 500 output tokens cost on Claude Sonnet 4.5?"

Cost Estimate for claude-sonnet-4-5

  Input:  1K tokens × $3.00/1M  = $0.003000
  Output: 500 tokens × $15.00/1M = $0.007500
  ─────────────────────────────
  Total:  $0.0105

compare_models

Find the most cost-effective models matching your requirements.

> "What are the cheapest OpenAI chat models?"

Top 2 most cost-effective models (provider: openai) (mode: chat):

1. gpt-4o-mini
   Provider: openai | Mode: chat
   Input: $0.15/1M | Output: $0.60/1M
   Context: 128K in / 16K out

2. gpt-4o
   Provider: openai | Mode: chat
   Input: $5.00/1M | Output: $15.00/1M
   Context: 128K in / 16K out

refresh_prices

Force re-fetch pricing data from the LiteLLM registry (cache is refreshed automatically every 24h).

Docs

Full documentation at tokencost.dev

License

MIT