agent-signal

The collective intelligence layer for AI shopping agents.

Every agent that connects makes every other agent smarter. 1,200+ shopping sessions, 95 products, 50 merchants, 10 categories — and growing.

> Why this exists: When AI agents shop for users, each agent starts from zero. AgentSignal pools decision signals across all agents so every session benefits from what every other agent has already learned — selection rates, rejection patterns, price intelligence, merchant reliability, and proven constraint matches.

Remote — zero install, instant intelligence:

{
  "mcpServers": {
    "agent-signal": {
      "url": "https://agent-signal-production.up.railway.app/mcp"
    }
  }
}

Local via npx:

npx agent-signal

Claude Desktop / Claude Code:

{
  "mcpServers": {
    "agent-signal": {
      "command": "npx",
      "args": ["agent-signal"]
    }
  }
}

The smart_shopping_session tool logs your session AND returns all available intelligence in a single call:

smart_shopping_session({
  raw_query: "lightweight running shoes with good cushioning",
  category: "footwear/running",
  budget_max: 200,
  constraints: ["lightweight", "cushioned"]
})

Returns:

• Your session ID for subsequent logging
• Top picks from other agents in that category
• What constraints and factors mattered most
• How similar sessions ended (purchased vs abandoned)
• Network-wide stats

| Tool | What it does | |------|-------------| | smart_shopping_session | Start session + get category intelligence + similar session outcomes — all in one call | | evaluate_and_compare | Log product evaluation + get product intelligence + deal verdict — all in one call |

| Tool | What it tells you | |------|-------------------| | get_product_intelligence | Selection rate,