Knowledgebaseserver
K

Knowledgebaseserver

A server based on the MCP protocol that allows LLMs to store and retrieve memories during conversations, using an SQLite database to implement full-text search functionality.
2.5 points
7.6K

What is the MCP KnowledgeBase Server?

This is a server based on the Model Context Protocol (MCP), specifically designed to help AI models store memories (information fragments) during conversations and retrieve these memories in subsequent conversations. It uses an SQLite database to store information and leverages its full-text search functionality for efficient retrieval.

How to use the MCP KnowledgeBase Server?

You can deploy this server through a Docker container or a local .NET runtime environment. After deployment, AI models can interact with it via the MCP protocol to store and retrieve conversation memories.

Use cases

Suitable for AI conversation systems that require long-term memory functions, such as personal assistants, customer service robots, or any AI application scenarios that need context memory.

Main features

Memory storage
Allows AI models to store important information fragments as memories during conversations
Memory retrieval
Provides an efficient full-text search function to help AI models find relevant memories
SQLite backend
Uses a lightweight SQLite database to store data without the need for complex database settings
Docker support
Provides pre-built Docker images to simplify the deployment process
Advantages
Lightweight and easy to deploy
No complex database configuration required
Supports Docker containerized deployment
Provides an efficient full-text search function
Limitations
Designed for single-machine use, not suitable for large-scale distributed deployment
The performance of the SQLite database may be limited with large amounts of data
Requires basic server deployment knowledge

How to use

Choose a deployment method
Decide whether to run the server using a Docker container or a local .NET environment
Docker deployment
Create a persistent storage volume and run the Docker container
Local deployment
Clone the repository and run it after installing the .NET 9 SDK
Configure the AI client
Add the MCP server configuration to the AI client configuration file

Usage examples

Remember user preferences
AI can remember user preference settings, such as favorite colors and language preferences
Context memory
AI can remember previous conversation content to provide a more coherent communication experience

Frequently Asked Questions

Where is the database stored?
How to back up memory data?
Does it support simultaneous access by multiple AI instances?
Do memory data expire?

Related resources

Model Context Protocol official website
Official documentation and specifications for the MCP protocol
Docker image repository
Official Docker images
GitHub repository
Project source code and issue tracking
SQLite documentation
Official documentation for the SQLite database

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "knowledgebase": {
      "command": "docker",
      "args": [
        "run",
        "--interactive",
        "--rm",
        "--volume", "knowledgebase:/db",
        "mbcrawfo/knowledge-base-server"
      ]
    }
  }
}

{
  "mcpServers": {
    "knowledgebase": {
      "command": "dotnet",
      "args": [
        "run",
        "--project", "/full/path/to/repo/src/KnowledgeBaseServer/KnowledgeBaseServer.csproj",
        "--no-restore",
        "--no-build"
      ]
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

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