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claude-spend

by mpalermiti

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    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI coding agents such as Claude Code, Cursor, Codex, and OpenCode to query local token usage, costs, quotas, projects, and models through six strictly read-only tools. All data stays on the local machine, drawn from passively parsed session logs rather than uploaded telemetry.
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables local-first tracking of AI token usage and costs from Claude Code and OpenCode, answering queries about tokens, models, sessions, and cost through MCP tools and a CLI, with no network calls.
      457 npm
      1
      MIT
    • F
      license
      Not graded
      quality
      D
      maintenance
      Exposes tools to query and analyze energy monitoring sessions stored in CSV files, enabling users to get consumption stats, compare sessions, and view historical data through natural language in Claude Desktop.
      -
    • A
      license
      Not graded
      quality
      C
      maintenance
      Analyzes Claude Code session token usage and cost locally — where spend actually lands across cache-read, cache-write and output, and what is consuming the context window. Read-only and offline: it parses your own session files and exposes analyze_claude_cost, get_cost_benchmark and tokenscope_share_summary.
      39 npm
      4
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Exposes a local inference ledger over MCP stdio, letting agents query request counts, token usage, TTFT, energy consumption, local costs, cloud-equivalent costs, savings percentages, and per-model breakdowns from an OpenAI-compatible proxy's SQLite ledger. Provides four read-only tools so coding agents can answer questions about home GPU inference economics without opening a browser.
      4
      1
      MIT
    • A
      license
      B
      quality
      B
      maintenance
      Lets a coding agent inspect its own run efficiency mid-session from local Claude Code transcripts, exposing the share of paid tokens that became model output versus context re-reading. Ships two stdio tools — one returning the shares as structured data and one returning the full cost-weighted report — with no network calls.
      2
      38 PyPI
      MIT