Get Biji Dev By Gemini3pro

🚀 Get Notes MCP Server

A Model Context Protocol (MCP) server for integrating with Get Notes API. This server provides tools to search and recall knowledge from your Get Notes knowledge base, helping users access and utilize knowledge more efficiently.

🚀 Quick Start

This MCP server offers seamless integration with the Get Notes API. You can quickly set up and start using it by following the installation and configuration steps below.

✨ Features

• Knowledge Search: AI-processed search that returns synthesized answers and references.
• Knowledge Recall: Raw recall of relevant notes and files.
• Rate Limiting: Built-in protection with QPS < 2 and Total Requests < 5000 limits.
• Retry Mechanism: Automatic retries for transient network errors (5xx).

📦 Installation

1. Clone the repository.
2. Install dependencies:

   npm install
   

3. Create .env file from example:

   cp .env.example .env
   

4. Configure your API key in .env:

   GET_API_KEY=T0TR1HWqw+tL00gVc5PPoXDnGIUIuPw7QCBeb1dMC6afCojR9WpHyuZicEFJjkMg3oZYS0HB/S3vqOj7+0e5FGoVtYuv938zkR8=
   GET_NOTE_TOPIC_ID=RYk1kmRJ
   

💻 Usage Examples

Basic Usage

Running with npx

You can run the server directly without installing it using npx:

npx get_notebook_mcp_server

MCP Configuration (Claude Desktop)

Option 1: Single Knowledge Base (Simple Setup) For a single knowledge base, add this to your claude_desktop_config.json:

{
  "mcpServers": {
    "get-notes": {
      "command": "npx",
      "args": ["-y", "get_notebook_mcp_server"],
      "env": {
        "GET_API_KEY": "T0TR1HWqw+tL00gVc5PPoXDnGIUIuPw7QCBeb1dMC6afCojR9WpHyuZicEFJjkMg3oZYS0HB/S3vqOj7+0e5FGoVtYuv938zkR8=",
        "GET_NOTE_TOPIC_ID": "RYk1kmRJ"
      }
    }
  }
}

Option 2: Multiple Knowledge Bases (Grouped Configuration - Recommended) For multiple knowledge bases sharing the same API key, use grouped configuration. The system will automatically expand them into individual knowledge bases:

{
  "mcpServers": {
    "get-notes": {
      "command": "npx",
      "args": ["-y", "get_notebook_mcp_server"],
      "env": {
        "GET_KNOWLEDGE_BASES": "[{\"id\":\"medical_group\",\"name\":\"Medical Knowledge Bases\",\"config\":{\"api_key\":\"T0TR1HWqw+tL00gVc5PPoXDnGIUIuPw7QCBeb1dMC6afCojR9WpHyuZicEFJjkMg3oZYS0HB/S3vqOj7+0e5FGoVtYuv938zkR8=\",\"topics\":[{\"id\":\"kb_pancreatic_trials\",\"name\":\"Tumor Clinical Trials KB\",\"topic_id\":\"RYk1kmRJ\"},{\"id\":\"kb_patient_experience\",\"name\":\"Patient Experience KB\",\"topic_id\":\"mnyV9OjY\"}]}}]"
      }
    }
  }
}

This configuration will be automatically expanded into two independent knowledge bases: kb_pancreatic_trials and kb_patient_experience.

Option 3: Using Local Configuration File (Recommended for Development) Create a knowledge_bases.json file in your project root:

[
  {
    "id": "demo_group",
    "name": "Sam's Knowledge Bases",
    "description": "Knowledge bases sharing the same API Key",
    "config": {
      "api_key": "T0TR1HWqw+tL00gVc5PPoXDnGIUIuPw7QCBeb1dMC6afCojR9WpHyuZicEFJjkMg3oZYS0HB/S3vqOj7+0e5FGoVtYuv938zkR8=",
      "api_endpoint": "https://open-api.biji.com/getnote/openapi",
      "topics": [
        {
          "id": "kb_pancreatic_trials",
          "name": "Tumor Clinical Trials Knowledge Base",
          "description": "Knowledge base about tumor clinical trials",
          "topic_id": "RYk1kmRJ"
        },
        {
          "id": "kb_patient_experience",
          "name": "Patient Experience Information",
          "description": "Patient experience info including guidelines and treatment experiences",
          "topic_id": "mnyV9OjY"
        }
      ]
    }
  }
]

Then configure Claude Desktop to use the local file:

{
  "mcpServers": {
    "get-notes": {
      "command": "npx",
      "args": ["-y", "get_notebook_mcp_server"]
    }
  }
}

How Claude Uses Multiple Knowledge Bases

Claude automatically selects the appropriate knowledge base - no manual selection needed!

Workflow:

1. User asks a question: "How long after pancreatic cancer surgery should chemotherapy start?"
2. Claude automatically calls list_knowledge_bases: Views all available knowledge bases
3. Claude intelligently selects: Based on the question content, automatically chooses the most relevant KB (e.g., kb_pancreatic_trials)
4. Claude calls search_knowledge: Passes the selected kb_id and the question
5. Returns results: Claude synthesizes the search results into an answer

Users can also specify explicitly:

• "Search in the Tumor Clinical Trials KB: pancreatic cancer chemotherapy timing"
• "Find in Patient Experience: chemotherapy side effect management"

This way Claude knows exactly which knowledge base to use.

Running Locally

node index.js

Testing with MCP Inspector

You can test the MCP server interactively using the MCP Inspector:

npx @modelcontextprotocol/inspector node index.js

📚 Documentation

Tools

list_knowledge_bases

List all available knowledge bases with their IDs, names, and descriptions.

Parameters: None

Returns: Array of knowledge base information (without sensitive API keys)

search_knowledge

Search the knowledge base with AI processing.

Parameters:

• kb_id (string, optional): Knowledge base ID. If not provided, uses the first configured KB.
• question (string, required): The question to ask.
• deep_seek (boolean): Enable deep thinking mode (default: false).
• history (array): Chat history for context.

recall_knowledge

Raw recall from knowledge base without AI synthesis.

Parameters:

• kb_id (string, optional): Knowledge base ID. If not provided, uses the first configured KB.
• question (string, required): The question or query.
• top_k (number): Number of results to return (default: 10).
• intent_rewrite (boolean): Enable intent rewrite (default: false).

🔧 Technical Details

Development

Running Tests

npm test

Project Structure

• src/api: API client implementation
• src/utils: Utility classes (RateLimiter, etc.)
• tests: Unit and integration tests
• index.js: Main MCP server entry point

📄 License

ISC

❤️ Acknowledgments

This project is contributed by the Xiao-X-Bao Community - an AI open-source public welfare community focused on improving medical information access for cancer/rare disease patients and their families throughout their life cycle.

About Xiao-X-Bao Community

We are an AI open-source public welfare community dedicated to using AI technology to build a high-quality, high-density patient knowledge ecosystem to improve medical information barriers. Our community brings together a diverse group of open-source contributors, AI technology experts, cancer patients, family members, medical professionals, and public welfare volunteers, working together to improve the information access challenges faced by patients.

Community Website: https://info.xiao-x-bao.com.cn

Our Mission: To use AI technology to break down medical information barriers and build a comprehensive knowledge ecosystem for patients.

Origin of Community Name: All our AI assistants are named "Xiao-X-Bao" (Little X Treasure), such as "Xiao Yi Bao" (Little Pancreas Treasure), "Xiao Fen Bao" (Little Pink Treasure), etc., hence our community is named "Xiao-X-Bao Community".

Community Development: In 2024, the project was donated to the "Tiangong Kaiwu Foundation", which provides funding and guidance to promote public welfare initiatives.

Progress Updates: Published via the WeChat Official Account "Xiao Yi Bao Assistant".

Community Contact

Detailed Community Introduction: View Introduction

Contact Us:

• WeChat: qinxiaoqiang2002
• WeChat: hhxdeweixinxin
• WeChat: zhuangbiaowei

We welcome all contributors, developers, medical professionals, and volunteers to join our community and use technology to improve medical information accessibility! 🌟