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claude-token-analyzer

MCP Tool

li195111/claude-token-analyzer

Diagnoses token waste in Claude Code sessions. 6 anomaly types, cost audit, trend forecasting. Fully local plugin.

Install

$ npx loaditout add li195111/claude-token-analyzer

Platform-specific configuration:

.claude/settings.json
{
  "mcpServers": {
    "claude-token-analyzer": {
      "command": "npx",
      "args": [
        "-y",
        "claude-token-analyzer"
      ]
    }
  }
}

Add the config above to .claude/settings.json under the mcpServers key.

About

Claude Token Analyzer

> Your Claude Code sessions might be burning tokens you can't see. > Diagnoses where your tokens go, why they're wasted, and what to fix first.

Fully local — parses your ~/.claude JSONL files into SQLite. Nothing leaves your machine. No cloud. No telemetry.

[](LICENSE) [](https://github.com/li195111/claude-token-analyzer/releases)

English | 繁體中文

Features
  • Diagnose token waste — Detects 6 statistical anomaly types (HighCost, LowCacheHitRate, CostInefficient, ExcessiveToolUse, HighTokenUsage, UnusualModelMix) with severity scoring
  • Audit costs — Per-session, per-project, and global cost breakdowns with monthly trends
  • Forecast spending — Daily/weekly/monthly usage trends with burn-rate projections
  • Optimize cache — Identifies sessions with poor cache hit rates that inflate costs
  • Prioritize fixes — Severity-scored anomalies so you know what to fix first, not just what's wrong
  • Converse naturally — Ask in plain language: "how much did I spend?" or "scan for anomalies"
Quick Start
# Install (binary auto-downloads, no Rust toolchain needed)
claude plugin install claude-token-analyzer

Then just ask in any Claude Code session:

> cta
> how much did I spend this month?
> scan for anomalies
> analyze this project
> show me usage trends
How It Works
~/.claude/projects/**/*.jsonl       Your session logs (never modified)
    → parser.rs                     Extract + deduplicate responses
    → analyzer.rs                   Cost calculation, 10-dimension metrics
    → storage.rs                    Upsert into local SQLite
    → detector.rs                   6-type anomaly detection + severity scoring
    → MCP tools / Skills            You ask, it answers

All processing happens locally. The SQL

Tags

claudeclaude-codecost-analysismcppluginrusttoken-analysis

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Quality Signals

6
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Installs
Last updated15 days ago
Security: AREADME
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Safety

Risk Levelmedium
Data Access
read
Network Accessnone

Details

Sourcegithub-crawl
Last commit3/31/2026
View on GitHub→

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