Agora MCP
Connects AI assistants to SearchAgora, a universal product search engine, allowing users to search for products, compare options, and (coming soon) manage shopping carts and complete purchases directly through the AI assistant.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Agora MCP find a wireless gaming mouse under $50"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Agora MCP
An MCP server for searching, discovering, and purchasing products through AI assistants like Claude or Cursor.
What is Agora MCP?
Agora MCP connects AI assistants to SearchAgora - a universal product search engine that helps you discover and buy products from across the web. With this MCP, you can seamlessly search for products, compare options, manage your shopping cart, and complete purchases directly through your AI assistant.
Related MCP server: @datalanguage/datagraphs-mcp-server
Prerequisites
MCP Client like Cursor or Claude Desktop
UV installed
A payment method through any L402-compatible client like Fewsats
Setting Up the MCP Server
For Cursor
Open Cursor and go to Settings
Navigate to MCP Server Configuration
Add the following configuration:
{
"mcpServers": {
"Agora": {
"command": "uvx",
"args": [
"agora-mcp"
]
},
"Fewsats": {
"command": "env",
"args": [
"FEWSATS_API_KEY=YOUR_FEWSATS_API_KEY",
"uvx",
"fewsats-mcp"
]
}
}
}Make sure to replace YOUR_FEWSATS_API_KEY with your actual API key from Fewsats.
For Claude Desktop
Find the configuration file:
On MacOS:
~/Library/Application\ Support/Claude/claude_desktop_config.jsonOn Windows:
%APPDATA%/Claude/claude_desktop_config.json
Add the following configuration:
"mcpServers": {
"Agora": {
"command": "uvx",
"args": [
"agora-mcp"
]
},
"Fewsats": {
"command": "env",
"args": [
"FEWSATS_API_KEY=YOUR_FEWSATS_API_KEY",
"uvx",
"fewsats-mcp"
]
}
}Running a Local Development Version
For development purposes, you can run a local version of the Agora MCP from your own repository:
"Agora": {
"command": "uv",
"args": [
"--directory",
"/path/to/your/agora-mcp",
"run",
"agora-mcp"
]
}Replace /path/to/your/agora-mcp with the actual path to your local Agora MCP repository.
Using Agora MCP With Your AI
Once configured, you can have natural conversations with your AI to search for and purchase products:
Searching for Products
Simply ask your AI to search for products:
Can you find a cool t-shirt for me?Advanced Search Options
Refine your search with additional parameters:
Show me headphones under $100 sorted by highest ratingThe search supports:
Price ranges (min/max)
Pagination
Custom sorting
Product filtering
Coming Soon: Shopping Cart & Purchasing
Soon you'll be able to:
Add that red t-shirt to my cartShow me what's in my cartCheckout and purchase my itemsSupported Features
Currently, Agora MCP supports:
Product search with customizable parameters:
Search query
Results per page
Page navigation
Price filtering (minimum and maximum)
Custom sorting options
Coming soon:
Add products to cart
View and manage shopping cart
Complete purchases
Save favorite products
Track order status
About SearchAgora
SearchAgora is a universal product search engine that helps you discover products from across the web. It offers a seamless shopping experience with comprehensive product information, price comparisons, and streamlined checkout processes.
Available Tools
6 toolsagora_get_orderC
Get details for a specific order in Agora.
Args:
order_id: The order ID.
Returns:
The order details.
Inputs: order_id (required).
agora_get_payment_offersA
Get the payment offers for a product in Agora. Some products do not have variants, in such cases use the product_id as variant_id too.
Before calling this tool, check if the user has already provided the shipping address and user information.
Otherwise, ask the user for the shipping address and user information.
If the user does not provide an `addressName`, use the `firstname` and `lastname` to populate it.
Args:
slug: The product slug.
product_id: The product ID as str delimited by escaped double quotes
variant_id: The product variant ID as str delimited by escaped double quotes
quantity: The quantity to purchase.
shipping_address: The shipping address.
user: The user information.
Example:
product_id = "\"1234567890\""
variant_id = "\"1234567890\""
shipping_address = {
"addressName": "John Doe",
"addressFirst": "123 Main St",
"city": "New York",
"state": "NY",
"country": "US",
"zipCode": "10001"
}
user = {
"firstname": "John",
"lastname": "Doe",
"email": "john@example.com",
}
Returns:
L402 offer that can be paid by L402-compatible clients.
Inputs: slug (required), product_id (required), variant_id (required), shipping_address (required), +2 more.
agora_get_product_detailB
Get details for a specific product in Agora.
Args:
slug: The product slug, it usually looks something like 'royal-blue-waxed-shoe-laces-6f2049ef-0d08-4a79-8937-025bb596092f-1718242165922'
Returns:
The product details.
Inputs: slug (required).
agora_get_user_infoB
Get the current user's profile and shipping addresses in Agora.
Returns:
Dict containing user profile info (firstname, lastname, email) and list of shipping addresses
Inputs: no named parameters.
agora_get_user_ordersB
Get all orders for the current user.
Returns:
A list of orders.
Inputs: no named parameters.
agora_searchB
Search for products matching the query in Agora.
Args:
q: The search query.
count: The number of products to return per page.
page: The page number.
price_min: The minimum price. Optional
price_max: The maximum price. Optional
sort: The sort field: price:relevance.
order: The sort order: asc or desc.
Returns:
The search results.
Inputs: q (required), price_min, price_max, count, +3 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 6 tools
Each tool has a clearly distinct purpose targeting different resources: get_order, get_payment_offers, get_product_detail, get_user_info, get_user_orders, and search. There is no overlap in functionality, making it easy for an agent to select the right tool for each task.
All tool names follow a consistent 'agora_verb_noun' pattern using snake_case, such as 'agora_get_order' and 'agora_search'. This predictability enhances readability and reduces confusion when navigating the tool set.
With 6 tools, the set is well-scoped for an e-commerce platform like Agora, covering core operations like product search, details, orders, payments, and user management. Each tool serves a distinct and necessary function without being excessive or insufficient.
The tool set provides strong coverage for browsing, ordering, and user management, but lacks update or delete operations (e.g., updating user info or canceling orders). Agents can work around these gaps, but the absence limits full lifecycle management in the domain.
Related MCP Connectors
Hosted MCP server connecting AI assistants to 9,000+ apps and 40,000+ actions via Zapier.
Connect e-commerce and marketing data to AI assistants via MCP.
MCP server that lets your AI assistant build and deploy apps, hosting each one at a live URL.
One MCP server for the services your AI needs: memory, files, Microsoft 365, kanban and more.
Related MCP Servers
- AlicenseNot gradedqualityDmaintenanceMCP server that provides standardized access to Google Maps, Flights, Hotels, and other search services, enabling AI assistants to perform various searches.MIT
- FlicenseNot gradedqualityDmaintenanceMCP server that connects AI assistants to the Data Graphs knowledge graph platform, enabling natural language search, exploration, and querying of graph data.5 npm-

BizNetAI MCP Serverofficial
AlicenseNot gradedqualityCmaintenanceA hosted MCP server that routes natural-language shopping queries to independent merchant storefronts, returning normalized product and merchant results for AI agents and shopping assistants.MIT- AlicenseNot gradedqualityDmaintenanceMCP server that enables AI shopping assistants to understand customer needs, search products using visual and semantic queries, apply metadata filters, and recommend relevant products from an inventory.2Apache 2.0