
computegauge/mcp
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The cost intelligence layer for AI agents. Model selection, spend tracking, credibility scoring, and local-to-cloud routing via MCP.
Обзор
Install once, every session is cost-aware and credibility-building. AI agents are powerful but expensive. A single Claude Code session can cost $5-50+. A multi-agent workflow can burn through $100 in minutes. And nobody tells the agent — or the human — until the bill arrives. Any MCP-compatible agent (Claude, Cursor, Windsurf, custom agents) gets: 1. — Know which model is optimal for every task, track spend in real-time 2. — Build a reputation score (0-1000) by making smart decisions. Compete on a leaderboard. 3. — Detect when local inference isn't good enough, route to cloud, earn credibility for smart routing The result: agents that spend 40-70% less, build visible credibility, and know when to route to cloud. Add to ~/.config/claude/claude_desktop_config.json: That's it. Restart Claude. Every conversation now has cost intelligence + credibility tracking. Every smart decision earns credibility points on a 0-1000 scale:
README
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@computegauge/mcp
The cost intelligence + agent credibility layer for AI agents. Install once, every session is cost-aware and credibility-building.
npm install -g @computegauge/mcp
Why This Exists
AI agents are powerful but expensive. A single Claude Code session can cost $5-50+. A multi-agent workflow can burn through $100 in minutes. And nobody tells the agent — or the human — until the bill arrives.
ComputeGauge MCP makes agents cost-aware AND gives them a credibility score. Any MCP-compatible agent (Claude, Cursor, Windsurf, custom agents) gets:
- Cost Intelligence — Know which model is optimal for every task, track spend in real-time
- Agent Credibility — Build a reputation score (0-1000) by making smart decisions. Compete on a leaderboard.
- Local→Cloud Routing — Detect when local inference isn’t good enough, route to cloud, earn credibility for smart routing
The result: agents that spend 40-70% less, build visible credibility, and know when to route to cloud.
Setup — 30 Seconds
Claude Desktop / Claude Code
Add to ~/.config/claude/claude_desktop_config.json:
{
"mcpServers": {
"computegauge": {
"command": "npx",
"args": ["-y", "@computegauge/mcp"]
}
}
}
That’s it. Restart Claude. Every conversation now has cost intelligence + credibility tracking.
With Provider API Keys (Enhanced)
{
"mcpServers": {
"computegauge": {
"command": "npx",
"args": ["-y", "@computegauge/mcp"],
"env": {
"ANTHROPIC_API_KEY": "sk-ant-...",
"OPENAI_API_KEY": "sk-...",
"COMPUTEGAUGE_BUDGET_TOTAL": "50"
}
}
}
}
With Local Inference (Ollama, vLLM, etc.)
{
"mcpServers": {
"computegauge": {
"command": "npx",
"args": ["-y", "@computegauge/mcp"],
"env": {
"OLLAMA_HOST": "http://localhost:11434",
"OLLAMA_MODELS": "llama3.3:70b,qwen2.5:7b,deepseek-r1:14b",
"ANTHROPIC_API_KEY": "sk-ant-...",
"COMPUTEGAUGE_BUDGET_TOTAL": "50"
}
}
}
}
Cursor
Add to Cursor MCP settings:
{
"computegauge": {
"command": "npx",
"args": ["-y", "@computegauge/mcp"]
}
}
Tools Reference
Agent-Native Tools (use automatically every session)
| Tool | When to Call | What It Does | Credibility |
|---|---|---|---|
pick_model |
Before any API request | Returns the optimal model for a task | +8 Routing Intelligence |
log_request |
After any API request | Logs the request cost | +3 Honest Reporting |
session_cost |
Every 5-10 requests | Shows cumulative cost and budget | — |
rate_recommendation |
After completing a task | Rate how well the model performed | +5 Quality Contribution |
model_ratings |
When curious about quality | View model quality leaderboard | — |
Установка
npx -y @computegauge/mcpКонфигурация
{
"mcpServers": {
"computegauge": {
"command": "npx",
"args": ["-y", "@computegauge/mcp"]
}
}
}