I spent the last 30 days logging every MCP tool call I made across
Cursor, Claude Code, and Claude Desktop. Some surprises: 1. Read tool calls dominate by volume but tokens are tiny they're cheap. The cost spike comes from a handful of big calls (web search, image processing, large file reads). 2. ~14% of tool calls fail or timeout. They still cost something on the LLM side because the model already burned input tokens. 3. There's no native way in Cursor/Claude/Windsurf to see which project or which session caused the spend. You only see totals. 4. Per-agent attribution flips assumptions: "the Claude Code in my dev folder" vs. "the Cursor in my marketing folder" had a 7x cost delta for the same number of files touched. I turned the logger into a product (MCPSpend) and we're launching on
PH tomorrow. Free tier 25k calls/month if anyone wants to test:
npx --yes @mcpspend/proxy@latest init --key mcps_live_xxx Curious anyone else tracking their MCP spend manually? What's
your stack?
MCPSpend is the observability proxy for Model Context Protocol tools. Track tokens, attribute spend per team and customer, and ship AI to production with audit-grade visibility.