What is Cleverchatty Memory

cleverchatty-memory is an MCP server designed to provide a memory interface for AI chat tools, enabling them to remember and summarize previous conversations.

Use cases

Use cases include maintaining context in customer service chats, providing personalized responses in virtual assistants, and summarizing discussions in collaborative tools.

How to use

To use cleverchatty-memory, clone the repository, install the necessary dependencies, create and activate a virtual environment, and run the server using FastAPI. The server can be accessed via the specified port.

Key features

Key features include the ability to remember chat messages for context extraction and to recall summaries of previous conversations, enhancing the AI chat experience.

Where to use

cleverchatty-memory can be used in various fields such as customer support, virtual assistants, and any application requiring conversational memory.

Memory server for AI Chat with MCP interface

This is an example of the memory server for AI chat. It follows the interface supported by the tool CleverChatty.

The interface for the MCP server is:

{
  "tools": [
    {
      "name": "remember",
      "description": "Remember a chat message to extract a context later for the memory",
      "inputSchema": {
        "properties": {
          "role": {
            "type": "string"
          },
          "message": {
            "type": "string"
          }
        },
        "required": [
          "role",
          "message"
        ]
      }
    },
    {
      "name": "recall",
      "description": "Returns the summary of the previous conversations",
      "inputSchema": {
        "properties": {},
        "required": []
      }
    }
  ]
}

This tool can be used together with the CleverChatty CLI to create an AI chat with memory. The server will remember the messages and return the summary of the previous conversations when requested.

How to run the server

1. Clone the repository

git clone [email protected]:Gelembjuk/cleverchatty-memory.git
cd cleverchatty-memory

2. Install uv if not already installed

curl -Ls https://astral.sh/uv/install.sh | sh

3. Create the virtual environment

uv venv

4. Activate the virtual environment on Linux/macOS (can be different on other platforms)

source .venv/bin/activate

5. Install the dependencies

uv sync

6. Run the server

fastapi run mcp_server.py --port 8001

This will start the MCP server with SSE transport on port 8001. You can change the port by modifying the --port argument. It will be accessible by the URL http://localhost:8001/mcp. You can also use the --host argument to change the host. By default, it will be accessible only from localhost. You can change it to --host 0.0.0.0 to make it accessible from any IP address.

Test ad debug

This tool contains also the CLI to test the server.

python manager.py COMMAND

Examples:

python manager.py clear-memory
python manager.py remember "user" "Some message from user"
python manager.py remember "assistant" "Some response from assistant"
python manager.py patch-memories
python manager.py recall
python manager.py history-dump