For AI Agent Builders

Give your AI agent
product intelligence

AI agents need structured product data to answer real questions — not web scraping, not hallucinated specs, not stale training data. Covala gives your agent a reliable product knowledge base it can query directly.

Without structured data, agents fail

When your agent needs to answer a product question, it has three bad options: guess from training data, scrape a retailer website, or tell the user it doesn't know.

Agents guess

Without structured data, agents hallucinate specs, prices, and availability. A user asks for the noise level of a dishwasher and gets a plausible but wrong number.

Context is limited

Training data is stale. Web search returns unstructured HTML that needs parsing. Neither gives the agent clean, typed data it can reason over.

No product relationships

Agents can't find alternatives, successors, or compatible accessories. They have no graph of how products relate to each other across brands and retailers.

How Covala powers AI agents

Structured tools, not web scraping

MCP Server

Native tool use. Your agent calls search_products, lookup_product, and compare_prices directly through the Model Context Protocol. No custom integration needed — just add the server to your config.

npx @covala/mcp-server

Structured responses

Every response is clean JSON with typed fields. Product name, brand, specifications, pricing, and relationships — all in a consistent schema. No parsing HTML, no extracting data from paragraphs of text.

Content-Type: application/json

AI-optimized format

Request format=ai for 300-token condensed summaries that fit in any context window, or use the full JSON response when your agent needs detailed specifications and pricing data.

?format=ai

Knowledge layer

Error codes, maintenance schedules, buying guides, lifespan data, and cost of ownership — structured data your agent can reason over, not just paragraphs of text to summarize.

9 knowledge types per category
Setup

Add Covala to your agent in one config

Point your MCP-compatible agent at the Covala server. It gets access to product search, lookup, price comparison, and knowledge queries — no custom code needed.

claude_desktop_config.json
{
  "mcpServers": {
    "covala": {
      "command": "npx",
      "args": ["@covala/mcp-server"],
      "env": {
        "COVALA_API_KEY": "sk_cvl_live_..."
      }
    }
  }
}
In practice

Your agent answers with real data

Instead of guessing or saying "I don't have that information," your agent calls Covala and returns structured, accurate answers.

conversation
User: What's the quietest Samsung dishwasher
under $700?
Agent calls search_products:
brand: "Samsung"
category: "Dishwashers"
sort: "noise_level:asc"
max_price: 700
Agent: The Samsung DW80CG4021SR is the
quietest option at 42 dBA. It's
currently $549 at Best Buy
and $579 at Home Depot.
50K+
Products
19
Retailers
620+
Product Types
9
Knowledge Types

Start building with
product intelligence

Give your AI agent a reliable product knowledge base. Join the developers.covala.com for API access, or explore the docs to see what you can build.

MCP server + REST API + AI-optimized responses