BuyWhere Product Search MCP
Give AI agents cross-market product search, price comparison, and deal discovery.
- Source repo
- BuyWhere/buywhere-mcp
- Stars
- ★ 14
- Last updated
- 4d ago
- License
- MIT
- Primary language
- TypeScript
- FA score
- 58/100 · Major gaps
At a glance
- How it runs
- Works with
- Universal · cross-platformCodex
- Cost
- Free, no paid service needed
- Setup effort
- Low · running in minutes
- You'll need
- Typical use
- A shopping-assistant developer needs to find wireless earbuds within a Singapore customer's budget and return purchasable candidates.
- Not a fit if
- Teams that require fully offline product search
- Merchants needing store or Shopify management
- Environments that cannot send queries to the BuyWhere API
- Source review
- 58/100 · Major gaps 1 safety controls not found
What does this agent do, and when should you use it?
BuyWhere MCP Server exposes BuyWhere's product catalog and real-time pricing capabilities to Model Context Protocol clients. It can run as a Node.js stdio process for Claude Desktop, Cursor, VS Code, Cline, Windsurf, OpenCode, Codex, and Continue.dev, while a hosted JSON-RPC 2.0 endpoint is available at `https://api.buywhere.ai/mcp`. Agents can search a catalog of more than 300 million products, retrieve details, compare 2–10 items, find the cheapest deliverable listing, discover price drops, locate similar products, and submit URLs for ingestion. Its documented coverage spans Singapore, the US, Malaysia, Thailand, and Vietnam, including Lazada, Shopee, Amazon, and local retailers. It suits shopping-research and cross-border comparison agents, but it is not a store-management system or Shopify integration, and live queries depend on BuyWhere's hosted API, network access, and an API key.
An MCP client starts @buywhere/mcp-server over stdio or connects to the remote MCP endpoint over HTTP with a Bearer credential. The server accepts structured tool calls and sends them to the product catalog at api.buywhere.ai. search_products filters by keyword, category, price, and country; get_product returns prices, specifications, and images; compare_products compares 2–10 products side by side; find_best_price finds the cheapest deliverable merchant listing; get_deals returns products with significant price drops; list_categories exposes the catalog taxonomy; find_similar performs vector-similarity discovery; and ingest_products submits product URLs for catalog ingestion. Corresponding v2 search, detail, comparison, deal, and best-price tools add delivery-country handling through deliver_to. The result is structured product, price, merchant, and delivery data that the calling agent can rank, summarize, or recommend.
- A shopping-assistant developer needs to find wireless earbuds within a Singapore customer's budget and return purchasable candidates.
- A cross-border shopper wants to compare the same product across US, Singapore, and Southeast Asian merchants.
- A research agent needs to search a category and then run
compare_productson 2–10 shortlisted items. - An automation team wants to call
get_dealsorfind_best_priceperiodically and pass price changes into another workflow. - A merchant or catalog contributor wants to submit product URLs through
ingest_productsfor BuyWhere ingestion. - A multi-agent system needs to delegate product-search and comparison tasks through the documented A2A Agent Card.
How do you install or deploy this agent?
Node.js 18 or newer is required. First obtain a free key without email verification:
curl -X POST https://api.buywhere.ai/v1/auth/register \
-H "Content-Type: application/json" \
-d '{"agent_name":"your-agent"}'The response immediately includes an api_key, tier, and rate limits. Export the key and run the MCP server directly:
export BUYWHERE_API_KEY=bw_...
npx -y @buywhere/mcp-serverA global installation is also documented:
npm install -g @buywhere/mcp-server
buywhere-mcpFor source development, use:
git clone https://github.com/BuyWhere/buywhere-mcp.git
cd buywhere-mcp
npm install
npm run build
npm startHow do you use this agent?
Add this configuration to Codex, OpenCode, or another client using the documented MCP server format:
{
"mcpServers": {
"buywhere": {
"command": "npx",
"args": ["-y", "@buywhere/mcp-server"],
"env": { "BUYWHERE_API_KEY": "bw_live_xxxx" }
}
}
}After reloading the client, ask for a concrete shopping task such as “Find wireless earbuds under $50 available in Singapore.” The client can call search_products and then pass selected IDs to compare_products. For remote operation, send JSON-RPC 2.0 requests to the hosted endpoint with the API key as a Bearer credential:
POST https://api.buywhere.ai/mcp
Authorization: Bearer bw_...The endpoint declares MCP protocolVersion 2024-11-05. BUYWHERE_API_URL can override the default API address.
What are this agent's strengths and limitations?
- One MCP interface covers Singapore, the US, Malaysia, Thailand, and Vietnam across Lazada, Shopee, Amazon, and local retailers.
- The tool set spans the full research path: discovery, product details, multi-item comparison, best price, deals, similarity, and URL ingestion.
- Agents can self-register a free key with one POST and no email; the example clearly states a 20 RPM and 1,000-per-day unverified limit.
- Both a local stdio package and a hosted MCP endpoint are documented, along with configurations for several clients and agent frameworks.
- The repository uses the MIT license and documents both MCP and A2A protocol support.
- Product operations depend on BuyWhere's hosted API; there is no evidence that the catalog or search backend can be self-hosted or used offline.
- Deployments must manage
BUYWHERE_API_KEY, and the documented unverified tier is limited to 20 requests per minute and 1,000 per day. - Explicit market coverage is limited to Singapore, the US, Malaysia, Thailand, and Vietnam.
- The documentation conflicts on tool count: the remote MCP section says 13 tools, while the protocol table says the stdio transport has 10.
- Real-time price and availability depend on upstream merchant data and BuyWhere; no refresh interval, uptime guarantee, or failure-handling commitment is stated.
How does this agent compare with similar options?
tavily-mcp has a different role: the source suggests Tavily for reviews and general product research, then BuyWhere for current prices and purchase links. @modelcontextprotocol/server-filesystem, @supabase/mcp-server-supabase, n8n-mcp, and @playwright/mcp are presented as complementary components for saving results, persisting preferences and alerts, automating monitoring, and testing browser interactions rather than direct replacements for BuyWhere's catalog search.
Key facts side by side with the most closely related agents.
| Agent | Source review | Form / cost | Stars | Updated | Language | Full support on |
|---|---|---|---|---|---|---|
| BuyWhere Product Search MCP This agent | 58 · Major gaps | MCP serverFree | ★ 14 | 4d ago | TypeScript | Codex |
| tRPC-Agent-Go | 53 · Major gaps | Library / SDKFree + model costs | ★ 1.8k | 1d ago | Go | OpenAI API |
| Fetch.ai Agent Examples | 48 · Major gaps | CLIFree + model costs | ★ 1.1k | 25d ago | Python | OpenAI API · Claude API |
| MCP Memory Service | 68 · Some gaps | MCP serverFree | ★ 2k | 1d ago | Python | ChatGPT · Codex · Claude Code · Claude.ai |
How does FollowAgents rate this agent?
Why each dimension lost points
The package takes a single API key through an environment variable, the architecture clearly shows the local stdio bridge sending requests to the hosted BuyWhere API, and the registry workflow declares narrowly scoped contents:read and id-token:write permissions. SECURITY.md advises against committing keys and recommends rotation. Deductions apply because there is no documented redaction, server-side key storage, request-retention, or third-party-sharing policy. Most tools appear read-only, but ingest_products creates an external write effect without a confirmation, deletion, reversal, or idempotency contract. The dependency set is small, but the MCP SDK uses a broad ^1.0.0 range, no lockfile or security-audit evidence is supplied, and the registry workflow downloads and executes a latest release artifact. Repository, package, copyright, and reporting attribution are consistent, while catalog-source and hosted-service provenance remain limited; unknown publisher identity was not treated as inherently negative.
README and package metadata specify Node 18+, while CI builds on Node 18, 20, and 22; installation routes and the hosted endpoint are also explicit, providing reasonable ordinary dependency-availability evidence. Self-consistency is reduced because the README alternately states 13 remote tools and 10 stdio tools while listing 13, and SECURITY.md supports only 0.3.x although package.json is version 0.4.0. No supplied file documents error classes, timeout behavior, rate-limit responses, retries, service-outage behavior, or representative user-facing failure messages, so failure_messages receives zero.
The documentation thoroughly covers shopping agents, comparison, deals, cross-border commerce, and multi-agent scenarios, with configurations or examples for Claude Desktop, Cursor, VS Code, Cline, Windsurf, Codex, Continue, Mastra, LangChain, LlamaIndex, and CrewAI. Tool descriptions, the architecture, the explicit exclusion of store management, and v2 deliver_to notes provide useful boundaries. Full marks are withheld from boundaries and trigger precision because complete schemas, validation constraints, tool-selection rules, and ambiguity handling are absent.
The README has strong information architecture and comprehensive quick-start, configuration, client, development, contribution, and support sections. MIT metadata matches a complete LICENSE, justifying full license credit. Deductions apply because v1 and v2 names coexist without a migration or deprecation policy, tool counts conflict, SECURITY.md trails the package version, and no changelog is supplied. Numerous examples are present, but there is no focused FAQ, troubleshooting section, or failure example. Limitations are only scattered across market coverage, Node requirements, and a sample registration rate limit. Security email, Issues, Discussions, and a CONTRIBUTING reference provide maintenance routes, but named maintainers and a complete release/support policy are not shown.
Search, detail, similarity, deals, best-price, ingestion, and comparison tools form a practically useful shopping-research surface, and examples describe structured products, prices, merchants, and links. Multi-market aggregation would provide material marginal value, and the example unverified tier discloses limits of 20 requests per minute and 1000 per day. Deductions reflect the absence of actual response schemas, representative complete outputs, ranking-quality evidence, latency or coverage measurements, paid pricing, and resource-cost details. Claims such as 300M+ products, 150,000+ stores, and real-time data remain primarily self-asserted in the supplied material.
Package identity, installation commands, Node requirements, license, CI matrix, and repository naming are corroborated across multiple supplied files. Core commercial and quality claims—including catalog size, store count, real-time availability, download figures, and geographic coverage—lack accompanying datasets, methods, tests, or independent evidence, limiting traceability. Marketing assertions and repository-verifiable facts are presented together, including use of terms such as “verified” without a verification procedure in the supplied sources, so fact and inference are not cleanly separated.
- Not found in source: confirmation before actingTurn on (or add) a confirmation step before it acts, and try it in a sandbox or test environment before real data.
- ingest_products submits URLs to an external catalog; require explicit confirmation before autonomous use and verify deletion, reversal, duplicate-submission, and retention policies.
- Queries and API credentials interact with hosted api.buywhere.ai infrastructure; confirm logging, retention, sharing, and key-storage practices before sending sensitive shopping intent or internal product research.
- The README tool counts conflict, and SECURITY.md support information does not match package version 0.4.0; verify the actual published tool inventory and supported release before integration.
- Do not rely solely on README claims of 300M+ products, real-time prices, inventory, or store coverage; independently validate price, delivery, currency, and availability for consequential purchases.
- The publishing workflow downloads and executes the latest registry publisher, while no lockfile or dependency-audit evidence is supplied; supply-chain-sensitive deployments should pin and review dependencies independently.
FAQ
Does it require payment or an email signup?
POST /v1/auth/register with no email. Its example unverified tier allows 20 requests per minute and 1,000 per day; no paid-plan pricing is provided.Do product searches run entirely on my machine?
api.buywhere.ai, so network access is required and queries are sent to BuyWhere.Can it manage a store or Shopify catalog?
Which markets and delivery filters are supported?
deliver_to country, while v2 comparison accepts it optionally.Can I use it without installing the npm package locally?
POST https://api.buywhere.ai/mcp, using JSON-RPC 2.0 and a Bearer API key.