token-meter
Related Servers
Alternatives to token-meter
No user-submitted related servers found.
Related Servers
- 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.321 npm1MIT
- AlicenseBqualityFmaintenanceTrack LLM token costs across Claude, GPT and Gemini. MCP server + CLI with optimization hints and $ savings estimates.88 npm1MIT
- FlicenseNot gradedqualityBmaintenanceRead-only MCP server for querying AI usage metrics (exact tokens, cost, latency, errors, productivity) from a local SQLite database, enabling charts and analysis in Claude Code and Cursor.-
- FlicenseAqualityCmaintenanceA local MCP server that tracks token usage and costs for Claude Desktop and Claude Code, providing a live dashboard at localhost:6789.59 npm-
- AlicenseNot gradedqualityCmaintenanceReal-time analytics dashboard for Claude Code, tracking sessions, tool usage, file changes, and token costs via an MCP server.2 npm1MIT
- AlicenseAqualityAmaintenanceA local-first, multi-provider cost meter for LLM usage, exposed as MCP tools. Captures every call into a local SQLite ledger and lets any coding agent query spend, compare providers, and get recommendations — no cloud, no account. First-class support for Chinese providers (Qwen, DeepSeek) alongside Anthropic and OpenAI.731 PyPI5MIT
TDQS
Scored across 5 tools
Each tool has a distinct focus: aggregate usage, session listing, per-session tool stats, subagent cost split, and data refresh. There is mild overlap between usage_summary and subagent_costs since both report spend, but the descriptions clearly delineate the scope.
All names use snake_case and mostly follow a noun-phrase pattern like usage_summary, recent_sessions, and session_tools. refresh_data breaks the pattern as an imperative verb, but the overall naming style is still coherent and predictable.
Five tools is a well-scoped count for a focused usage/cost monitoring server. Each tool addresses a distinct analytical need without unnecessary bloat.
The tool surface covers the core workflow: refresh local data, view aggregate usage, list sessions, inspect per-session tool activity, and analyze subagent costs. Missing advanced capabilities like time-range filtering or raw data export feel like minor gaps rather than fundamental omissions.