Channel3 MCP Server
OfficialClick on "Install 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., "@Channel3 MCP Serverfind me a good wireless 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.
Channel3 MCP Server
Quick Start (Free Tier)
No API key required. Connect directly and start searching:
https://mcp.trychannel3.com/The free tier is rate-limited to 10 requests per minute per IP address. If you hit the limit, you'll receive an error response.
Related MCP server: Ecomm MCP Server
Unlimited Access
For unlimited usage and affiliate tracking, create an account and add your API key:
Create an account at trychannel3.com and create an API key to authenticate requests and affiliate purchases to your account.
Add the Channel3 MCP to your agent with
?apiKey=<your-api-key>in the URL as such:
https://mcp.trychannel3.com/?apiKey=placeholderCursor
Add to ~/.cursor/mcp.json:
{
"mcpServers": {
"Channel3": {
"url": "https://mcp.trychannel3.com/?apiKey=<your-api-key>"
}
}
}To use the free tier (no API key, rate-limited), omit the apiKey parameter:
{
"mcpServers": {
"Channel3": {
"url": "https://mcp.trychannel3.com/"
}
}
}VS Code
Add to .vscode/mcp.json:
{
"servers": {
"Channel3": {
"type": "http",
"url": "https://mcp.trychannel3.com/?apiKey=<your-api-key>"
}
}
}Claude Code
claude mcp add --transport http Channel3 "https://mcp.trychannel3.com/?apiKey=<your-api-key>"Claude Desktop
Add to your Claude Desktop config file:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"Channel3": {
"command": "npx",
"args": [
"-y",
"mcp-remote",
"https://mcp.trychannel3.com/sse?apiKey=<your-api-key>"
]
}
}
}OpenAI Agents SDK (Python)
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
async with MCPServerStreamableHttp(
name="Channel3",
params={
"url": "https://mcp.trychannel3.com/?apiKey=<your-api-key>",
},
cache_tools_list=True,
) as server:
agent = Agent(
name="Shopping Agent",
instructions="You are a personal shopping assistant.",
mcp_servers=[server],
)
result = await Runner.run(agent, "I'm looking for a new laptop")
print(result.final_output)
asyncio.run(main())OpenAI Agents SDK (TypeScript)
import { Agent, run, MCPServerStreamableHttp } from "@openai/agents";
const server = new MCPServerStreamableHttp({
url: "https://mcp.trychannel3.com/?apiKey=<your-api-key>",
name: "Channel3",
});
await server.connect();
const agent = new Agent({
name: "Shopping Agent",
instructions: "You are a personal shopping assistant.",
mcpServers: [server],
});
const result = await run(agent, "I'm looking for a new laptop");
console.log(result.finalOutput);
await server.close();Local Testing
Start the dev server:
pnpm run devStart MCP Inspector:
npx @modelcontextprotocol/inspectorIn the MCP Inspector UI:
Transport Type: Streamable HTTP
URL:
http://localhost:8787/?apiKey=<YOUR_API_KEY>Click Connect
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