tokenchit
Related Servers
Alternatives to tokenchit
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityBmaintenanceAnalyzes 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.274MIT
- AlicenseBqualityAmaintenanceLets 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.2MIT
- AlicenseNot gradedqualityDmaintenanceProvides tools for Claude to query local Claude Code token usage and cost data, enabling spend analysis and insights through natural language.171MIT
- AlicenseAqualityAmaintenancePrices your Claude Code and Codex sessions from the transcripts on disk, shows what each agent cost over any period, and tells you in plain English what would have been cheaper. CLI, Browser UI and MCP server.85MIT
- AlicenseAqualityAmaintenanceLocal-first dashboard + MCP server that parses Claude Code and Codex JSONL files into a SQLite cost / token tracker. Per-MCP and per-tool breakdown, session drill-down, dedup by request_id; never talks to vendor APIs51001MIT
- AlicenseNot gradedqualityAmaintenanceEnables 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.1611MIT
This server cannot be deployed
TDQS
Scored across 4 tools
get_usage (windowed totals), get_daily_usage (per-day series), and get_recap (year-in-review aggregates) have partially overlapping subject matter, but each description clearly states its scope and output shape. detect_agents is cleanly distinct. Minor risk that an agent asks for a time range and picks get_usage over get_daily_usage.
Three tools follow a clean get_<noun> snake_case pattern (get_usage, get_daily_usage, get_recap). detect_agents breaks the prefix convention slightly but is still snake_case and readable, so the set is nearly uniform.
Four focused tools cover the analytics surface without redundancy. It is on the lean side but each tool earns its place; nothing feels padded or missing at the count level.
Covers lifetime/window totals, daily series, yearly recap, and agent discovery/diagnostics, which addresses the core questions of a usage-tracking server. Possible gaps like per-project rollups or cross-agent comparison views are not indicated as supported, but no obvious dead end for the stated purpose.