Retired. Use io.github.BuyWhere/buywhere-mcp instead.
BuyWhere MCP Server — Catalog API (ai.buywhere/catalog-api)
This MCP server is retired. The catalog API is documented as “ai.buywhere/catalog-api” and points to an alternative repository: io.github.BuyWhere/buywhere-mcp. The provided excerpt describes product search and price comparison for AI agents across Singapore and US merchants in real time.
🛠️ Key Features
Product search for AI agents
Price comparison across merchants
Real-time deal discovery
Coverage: Singapore and US
🚀 Use Cases
Enabling agents to find products and compare prices
Supporting commerce-oriented workflows for shopping and deals
Using the server from MCP-compatible clients
⚡ Developer Benefits
Install via npm (@buywhere/mcp-server) using BUYWHERE_API_KEY
Intended for Claude Desktop, Cursor, VS Code Copilot, Cline, Windsurf, OpenCode, Codex, Continue.dev
Available resources: npm page, GitHub repo, and MCP registry listing
⚠️ Limitations
“Retired”: use io.github.BuyWhere/buywhere-mcp instead
Works with Claude Desktop, Cursor, VS Code Copilot, Cline, Windsurf, OpenCode, Codex, Continue.dev, and any MCP-compatible client. Also supports Agent-to-Agent (A2A) protocol.
User: "Find me wireless earbuds under $50 available in Singapore"
Agent: [calls search_products → returns 5 matching products]
User: "Compare the top 3"
Agent: [calls compare_products → side-by-side with best-value pick]
Quick Start
Get a key in 3 seconds — no signup, no email:
bash
# 1. Register (one call, returns api_key instantly)
curl -X POST https://api.buywhere.ai/v1/auth/register \
-H "Content-Type: application/json" \
-d '{"agent_name":"your-agent"}'# → {"api_key":"bw_...","tier":"unverified","rate_limit":{"rpm":20,"daily":1000}}# 2. Use the keyexport BUYWHERE_API_KEY=bw_...
npx -y @buywhere/mcp-server
Use BuyWhere tools in LangChain agents via the MCP adapter:
python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_anthropic import ChatAnthropic
asyncdefmain():
asyncwith MultiServerMCPClient({
"buywhere": {
"url": "https://api.buywhere.ai/mcp",
"transport": "streamable_http",
"headers": {"Authorization": f"Bearer {BUYWHERE_API_KEY}"},
}
}) as client:
tools = await client.get_tools()
agent = create_react_agent(ChatAnthropic(model="claude-sonnet-4-5"), tools)
result = await agent.ainvoke({"messages": [("user", "Find the cheapest Sony headphones in Singapore")]})
LlamaIndex
Connect BuyWhere via LlamaIndex MCP client:
python
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.agent.openai import OpenAIAgent
asyncdefmain():
mcp_client = BasicMCPClient(
command_or_url="https://api.buywhere.ai/mcp",
headers={"Authorization": f"Bearer {BUYWHERE_API_KEY}"},
)
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = mcp_tool_spec.to_tool_list()
agent = OpenAIAgent.from_tools(tools)
response = await agent.achat("Compare prices for iPhone 16 Pro across Singapore and US")
CrewAI
Use BuyWhere in a CrewAI agent with MCP tool integration:
python
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
buywhere_server = MCPServerAdapter(
server_params={
"url": "https://api.buywhere.ai/mcp",
"headers": {"Authorization": f"Bearer {BUYWHERE_API_KEY}"},
"transport": "streamable-http",
}
)
shopping_agent = Agent(
role="Shopping Research Analyst",
goal="Find the best deals across Singapore and US markets",
tools=[buywhere_server],
)
task = Task(
description="Find the best price for Sony WH-1000XM5 headphones across all available markets",
agent=shopping_agent,
expected_output="Product comparison with prices and merchant links",
)
crew = Crew(agents=[shopping_agent], tasks=[task])
result = crew.kickoff()
Configuration
Variable
Default
Description
BUYWHERE_API_KEY
(required)
API key (no signup: POST /v1/auth/register {"agent_name":"<name>"}) — returns instantly, no email verification
BUYWHERE_API_URL
https://api.buywhere.ai/mcp
Custom API base URL
Install
bash
# Run directly (no install)
npx -y @buywhere/mcp-server
# Install globally
npm install -g @buywhere/mcp-server
buywhere-mcp
Use Cases
Shopping agents — build AI agents that search, compare, recommend products across markets
Price comparison — multi-market pricing in a single query across Lazada, Shopee, Amazon, local retailers
Deal discovery — find best-value products with real-time pricing and inventory
Ecommerce automation — integrate product search into any MCP-compatible app
Cross-border commerce — compare prices between Singapore, US, Malaysia, Thailand, and Vietnam markets
Agent-to-Agent commerce — delegate shopping tasks between agents via A2A protocol
git clone https://github.com/BuyWhere/buywhere-mcp.git
cd buywhere-mcp
npm install
npm run build
npm start
Why BuyWhere?
BuyWhere is a product search API for AI agents. We aggregate product data from Singapore, US, Malaysia, Thailand, and Vietnam merchants into a single, agent-friendly interface — no store management, no Shopify integration. Just search and compare products in real time.
One API — all markets, all retailers
Agent-native — built for MCP from day one
Real-time — live pricing and availability
Developer-first — no SDK needed, just add the server
Works Well With
These complementary MCP packages extend BuyWhere into powerful multi-tool workflows:
@modelcontextprotocol/server-filesystem — Save shopping results and product research to your local filesystem. Combine with BuyWhere to export deal lists, price comparisons, and product specs as structured files.
@supabase/mcp-server-supabase — Store favorite products, user preferences, and price alerts in Supabase. Persist shopping history across agent sessions.
n8n-mcp — Automate price monitoring workflows. Build no-code pipelines that watch BuyWhere prices and trigger notifications on price drops.
tavily-mcp — Research products before buying. Use Tavily to find reviews and comparisons, then use BuyWhere to get current prices and purchase links.
@playwright/mcp — E2E test your shopping agent interactions. Verify that product search, price comparison, and checkout flows work correctly in browser automation.
