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Insights Knowledge Base MCP Server

by v587d
GitHub
Python
1
  • Apple
  • Linux
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Insights Knowledge Base(IKB) MCP Server

>>>中文版

🍭A free, plug-and-play knowledge base. Built-in with 10,000+ high-quality insight reports, packaged as MCP Server, and secure local data storage.

⚠️⚠️ All collected reports in this project come from free resources on official research report websites. ⚠️⚠️

Features

  1. 🍾 No configuration needed, truly plug-and-play. For private document parsing, configure VLM models and parameters in .env (e.g., VLM_MODEL_NAME=qwen2.5-vl-72b-instruct).
  2. 🦉 Permanently free - no need to waste effort collecting report resources. Welcome to share reliable, copyright-free report sources via issues.
  3. 📢 Committed to weekly report updates, but bug fixes depend on my mood (I'm not a programmer 🤭).

[introduction video][https://youtu.be/Mb8KbPo7EVM]

Installation (Beginner-Friendly)

💡Pro tip: Stuck? Drag this page to an LLM client (like DeepSeek) for step-by-step guidance. Actually, these instructions were written by DeepSeek too...

Prerequisites: Python 3.12+ (Download from official website and ADD ENVIRONMENT PATH)

Install UV:

pip install uv
1. Clone the project
git clone https://github.com/v587d/InsightsLibrary.git cd InsightsLibrary
2. Create virtual environment
uv venv .venv # Create dedicated virtual environment # Activate environment # Windows: .\.venv\Scripts\activate # Mac/Linux: source .venv/bin/activate
3. Install core dependencies
uv pip install -e . # Note the trailing dot indicating current directory
4. Create environment variables (for future needs)
notepad .env # Windows # Or nano .env # Mac/Linux
5. Configure MCP Server
  • VSCODE

    Note: Replace <Your Project Root Directory!!!> with actual root directory.

{ "mcpServers": { "ikb-mcp-server": { "command": "uv", "args": [ "--directory", "<Your Project Root Directory!!!>", "run", "ikb_mcp_server.py" ] } } }
  • Cherry Studio
    • Command: uv
    • Arguments:
--directory <Your Project Root Directory!!!> run ikb_mcp_server.py

Parse Private Documents

Version 0.1.0 has basic functionality - we'll improve this later. 😎

  1. Upload PDF documents to the library_files folder
  2. Manually run Python scripts:
# cd to project root # Activate virtual environment uv run decoder.py # Wait for completion uv run large_models.py # Wait for completion # Data is now updated in the database

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A
security – no known vulnerabilities
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license - not found
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quality - confirmed to work

Tools

A free, plug-and-play knowledge base server that provides access to 10,000+ insight reports with secure local data storage.

  1. Features
    1. Installation (Beginner-Friendly)
      1. Prerequisites: Python 3.12+ (Download from official website and ADD ENVIRONMENT PATH)
      2. Clone the project
      3. Create virtual environment
      4. Install core dependencies
      5. Create environment variables (for future needs)
      6. Configure MCP Server
    2. Parse Private Documents

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