MCP server for AI agent token-cost telemetry across providers: per-agent + anomaly + routing.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"openclaw-cost": {
"env": {
"OPENCLAW_COST_BACKEND": "mock"
},
"args": [
"-m",
"openclaw_cost_tracker_mcp"
],
"command": "python"
}
}
}Are you the author?
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MCP server for AI agent token-cost telemetry across providers: per-agent + anomaly + routing.
Run this in your terminal to verify the server starts. Then let us know if it worked — your result helps other developers.
uvx 'openclaw-cost-tracker-mcp' 2>&1 | head -1 && echo "✓ Server started successfully"
After testing, let us know if it worked:
Five weighted categories — click any category to see the underlying evidence.
No known CVEs.
Checked openclaw-cost-tracker-mcp against OSV.dev.
Click any tool to inspect its schema.
cost_overview7-day snapshot
cost://overview
cost_forecast30-day projection
cost://forecast
cost_anomaliesRecent flagged anomalies
cost://anomalies
diagnose-cost-spikeWalk a recent spike to its root cause + corrective action
weekly-cost-digest200-word weekly cost digest
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MCP server for AI agent token-cost telemetry — built for the operator who woke up to a surprise bill. Catches the failure modes vendor dashboards miss: silent re-routing to API billing (HERMES.md bug, 1,464 upvotes), unattended
/loopovernight burns ($6k in 26 hours, real story), per-agent attribution buried behind aggregate provider totals, multi-day dashboard lag that surfaces the spike after the money is gone. Cross-provider: Anthropic, OpenAI, Gemini, Ollama, AWS Bedrock. Per-agent + per-provider attribution, spend-spike anomaly detection (per-agent median × threshold), cheaper-routing recommendations with 30-day savings estimates, monthly forecast. Reads any cost-log JSONL with the standard{request_id, timestamp, provider, model, agent_id, prompt_tokens, completion_tokens, cost_usd}schema. OpenClaw operators get native~/.openclaw/cost-logs/parsing; other deployments wrap their provider calls with the included logging shim or commission a Custom MCP Build adapter. Keywords: Claude API cost surprise, /loop overnight burn, HERMES.md billing routing, dashboard lag, AI agent FinOps, LLM cost attribution, token spend monitoring.
Production AI deployments are leaking money in ways the vendor dashboards don't surface in time. Real stories from the last 30 days on r/ClaudeAI:
/loop command running 26 hours unattended on Claude Opus 4.7 (1,175 upvotes, 314 comments, May 1 2026). The Anthropic dashboard lagged by days; the spike was invisible until the limit email landed. Verbatim from the OP: "By the time it shows a spike, the money is already spent."claude-code-guide agent recommended a command that bypasses Max-plan billing.In every case the dashboard lagged, the per-agent attribution was invisible, and Anthropic's own hard-cap mechanism either failed or arrived too late. This MCP server surfaces per-agent + per-provider cost attribution live, q