Tokencost Dev MCP server

by jeff-atriumn·io.github.jeff-atriumn/tokencost-dev·v0.1.3·1 stars

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LLM pricing oracle — model lookup, cost estimation, and comparison via LiteLLM

A89/100grade A

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Safety scan

A89/100

full report

Adoption

New

1 stars

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If you have run it, two minutes of your experience saves the next person an afternoon.

Tokencost Dev tools (4)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

calculate_estimate
Estimate the cost for a given number of input and output tokens on a specific model. Supports optional cached_tokens for prompt caching discounts.
compare_models
Filter and compare models by provider, minimum context window, or mode. Returns top 5 most cost-effective matches.
get_model_details
Look up pricing, context window, and capabilities for an LLM model. Uses fuzzy matching so you don't need the exact model key.
refresh_prices
Force a re-fetch of pricing data from the LiteLLM registry. Use this if you suspect the cached data is stale.

Public scan report

scanner v0.1.10 · 2026-09-28 · same rubric, same numbers if you re-run it

no findings

Code scan9 source files scanned25/25
–Live reliabilityno gateway calls yet and no remote to proben/a
–Tool poisoningtools not inspected (local package is not executed); not countedn/a
Auth qualitylocal package, no credentials required12/15
Maintenancelast push 6 days ago15/15
Maintainer identitynamespace and repository owner differ; GitHub account older than a year6/10

Overall 89/100. Components that don't apply are left out of the denominator. Any critical finding is an F.Rubric Appeal a finding JSON

How Tokencost Dev compares

Against every graded AI and agents MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score: 89/100; higher than 83% of 4,460 AI and agents servers
Tools: 4; the typical AI and agents server has 6
Tools that change things: 0%; typical: 0%. Fewer write tools means less an agent can break
GitHub stars: 1; more than 50% of 2,711 AI and agents servers

What its tools let an agent do: 4 read

Install Tokencost Dev in Claude Code, Cursor or VS Code

Runs npx -y tokencost-dev on your machine. Read the scan report first; the gateway never runs local packages.

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

Add to Cursor

What the publisher says

From the Tokencost Dev repository's README, as published. We do not edit it. Read it on GitHub

tokencost Ask your AI assistant "how much does GPT-4o cost?" — get an instant, accurate answer.

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

getmodeldetails

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

Nothing above is checked by us. What we check is on the safety report.

Tokencost Dev: common questions

Is Tokencost Dev MCP server safe?: Yes, by our scan: it is graded A (89/100). Read the Tokencost Dev safety report
How do I install Tokencost Dev?: It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does Tokencost Dev need an API key?: Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is Tokencost Dev maintained?: The last commit was 43 days ago (2026-09-22). The latest release is v0.1.3.
What can I use instead of Tokencost Dev?: Servers from other publishers that do the same job: llmtrim MCP server.
How does Tokencost Dev compare with other AI and agents MCP servers?: safety score 89/100 (higher than 83% of 4,460 AI and agents servers); tools 4 (the typical AI and agents server has 6); tools that change things 0% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.

Alternatives to Tokencost Dev

Same job from other publishers: the closest match first, then the best rated.

llmtrim
MCP server and proxy that compresses LLM prompts, tool output, and replies to cut token cost.
not reviewed
Established
A