claude-cost-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| estimate_tokensA | Estimate the number of Claude tokens for a piece of text. Korean/CJK-aware (Korean uses ~1.3x the tokens of equivalent English). No API key needed. |
| estimate_costA | Estimate Claude API cost across Haiku/Sonnet/Opus for given token counts (or raw text). Optional prompt-caching ratio. |
| caching_breakevenA | Compute prompt-caching savings and break-even for a static prompt reused N times. Break-even is ~1.28 reuses. |
| batch_savingsA | Compute Batch API savings (50% off input+output) for a recurring workload. Use when work is async/non-realtime (≤24h SLA acceptable). |
| compare_providersA | Compare API cost across 8 models from Anthropic, OpenAI, and Google for given token counts. Returns a table sorted cheapest-first so you can see where Claude sits vs alternatives. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 5 tools
Each tool has a clear, distinct purpose: batch savings, caching break-even, provider comparison, cost estimation, and token estimation. No overlap between them.
All tool names follow a consistent verb_noun snake_case pattern (e.g., batch_savings, estimate_cost), making them predictable.
Five tools is an appropriate size for a cost-estimation server, each covering a necessary aspect without being excessive or insufficient.
The tool set covers core cost estimation, token counting, batch savings, caching efficiency, and provider comparison. Minor gaps like historical usage tracking exist but are not essential for the stated purpose.