Concept Activation Network (CAN) MCP Server

by psikosen

161 downloads
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Description

# Concept Activation Network (CAN) MCP Server The Concept Activation Network (CAN) MCP Server implements a parallel, associative thinking approach using the Model Context Protocol (MCP). Unlike sequential thinking approaches, CAN operates on a network of interconnected concepts…

About

# Concept Activation Network (CAN) MCP Server The Concept Activation Network (CAN) MCP Server implements a parallel, associative thinking approach using the Model Context Protocol (MCP). Unlike sequential thinking approaches, CAN operates on a network of interconnected concepts with activation spreading in parallel…

Details

Author
psikosen
Downloads
161
Categories
Other

- Network structure of interconnected concept nodes with weighted connections
- Parallel activation spreading through multiple conceptual pathways simultaneously
- Session management: create, list, and delete independent sessions
- Concept management: add/remove concepts and connections between them
- Configurable activation parameters and convergence detection
- Analysis tools: top activated concepts, emergent patterns, summaries, and history

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

  1. Download and install Highlight from highlightai.com/download
  2. Navigate to the plugins tab and select "Add Custom Plugin"
  3. Configure the plugin with the settings below
    Plugin Name Concept Activation Network (CAN) MCP Server
    Command (node, npx, python, etc.)

    Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.

  4. Enable "Start Automatically" if you want the plugin to start when Highlight launches

From the repository

Clone the repository, install dependencies with npm install, and start with npm start. Configure it in Claude Desktop by adding a can entry to your claude_desktop_config.json pointing to can-server.js. Use the MCP tools to create sessions, add concepts and connections, set activation parameters, run activation iterations, and analyze emergent patterns.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "concept activation network (can) mcp server": {
            "can": {
                "command": "node",
                "args": [
                    "yourpath/can-mcp-server/can-server.js"
                ]
            }
        }
    }
}

McpServers

{
    "can": {
        "command": "node",
        "args": [
            "yourpath/can-mcp-server/can-server.js"
        ]
    }
}

Concept Activation Network (CAN) MCP Server

The Concept Activation Network (CAN) MCP Server implements a parallel, associative thinking approach using the Model Context Protocol (MCP). Unlike sequential thinking approaches, CAN operates on a network of interconnected concepts with activation spreading in parallel through the network until a coherent pattern or solution emerges.

Key Concepts

Parallel Concept Activation

Traditional AI reasoning often relies on sequential, step-by-step thinking processes. CAN takes a fundamentally different approach:

1. Network Structure: Knowledge is represented as a network of interconnected concepts
2. Parallel Activation: When prompted, activation energy spreads simultaneously through multiple pathways
3. Emergent Patterns: Solutions emerge as stable patterns of highly activated, related concepts
4. Non-Linear Exploration: Multiple conceptual paths are explored simultaneously

This approach is inspired by theories of human cognition suggesting that we often think by association rather than pure sequential logic.

Core Components

The CAN system consists of:

1. Concept Nodes: Individual units representing concepts, ideas, or elements
2. Weighted Connections: Links between concepts with varying strengths
3. Activation Dynamics: Algorithms controlling how activation spreads through the network
4. Pattern Detection: Methods for identifying emergent structures of activated concepts

Installation

```bash

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