bash
npm install -g mcp-server-weread

json
{
  "mcpServers": {
    "mcp-server-weread": {
      "command": "mcp-server-weread",
      "env": {
        "WEREAD_COOKIE": "your-wechat-reading-cookie"
      }
    }
  }
}

bash
npx mcp-server-weread

json
{
  "mcpServers": {
    "mcp-server-weread": {
      "command": "npx",
      "args": ["-y", "mcp-server-weread"],
      "env": {
        "WEREAD_COOKIE": "your-wechat-reading-cookie"
      }
    }
  }
}

bash
export WEREAD_COOKIE="your-wechat-reading-cookie"

json
{
  "mcpServers": {
    "mcp-server-weread": {
      "command": "npx",
      "args": ["-y", "mcp-server-weread"],
      "env": {
        "WEREAD_COOKIE": "your-wechat-reading-cookie"
      }
    }
  }
}

   Available tools from this MCP server:
   - get_bookshelf: Fetch bookshelf information
   - search_books: Search for books
   - get_book_notes_and_highlights: Retrieve notes and highlights
   - get_book_best_reviews: Obtain popular book reviews
   

javascript
// JavaScript example (Node.js)
const { MCPClient } = require('@modelcontextprotocol/client');

const client = new MCPClient();
await client.connect();

// Execute tool
const result = await client.callTool('get_bookshelf', {});

console.log(result);

bash
#!/bin/bash
Batch processing example

for file in *.txt; do
  mcp-tool process "$file"
done

python
Python example
import requests
import json

def call_mcp_tool(tool_name, params):
    response = requests.post(
        'http://localhost:3000/mcp/call',
        json={
            'tool': tool_name,
            'parameters': params
        }
    )
    return response.json()

Usage example
result = call_mcp_tool('get_book_best_reviews', {
    'book_id': 'example-book-id'
})