NSAF MCP Server

The Neuro-Symbolic Autonomy Framework integrates neural, symbolic, and autonomous learning methods into a single, continuously evolving AI agent-building system. This prototype demonstrates the SCMA component, which enables AI agents to self-design new AI agents using Generative Architecture Models.

Installation

Installing for Claude Desktop

Manual Configuration Required

This MCP server requires manual configuration. Run the command below to open your configuration file:

npx mcpbar@latest edit -c claude

This will open your configuration file where you can add the NSAF MCP Server MCP server manually.

NSAF MCP Server

This is a Model Context Protocol (MCP) server for the Neuro-Symbolic Autonomy Framework (NSAF). It allows AI assistants to interact with the NSAF framework through the MCP protocol.

Note: This repository includes both the NSAF framework code and the MCP server implementation, making it a complete package that can be deployed and used anywhere.

Note: This implementation uses a simplified version of the MCP protocol that doesn't require the official MCP SDK. It implements the core functionality needed to expose NSAF capabilities to AI assistants.

Features

  • Run NSAF evolution with customizable parameters
  • Compare different NSAF agent architectures
  • Integrate NSAF capabilities into AI assistants

Prerequisites

  • Node.js 18+ and npm
  • Python 3.8+ with the NSAF framework installed

Installation

  1. Clone this repository:
git clone https://github.com/ariunbolor/nsaf-mcp-server.git
cd nsaf-mcp-server
  1. Install dependencies:
npm install
  1. Build the server:
npm run build

Configuration

The server includes the NSAF framework code, so no additional configuration is required for basic usage. The MCP server is designed to work out-of-the-box when installed globally.

Usage

Running the server locally

npm start

Deploying to GitHub

  1. Create a new GitHub repository for your MCP server:

    • Go to GitHub and create a new repository named nsaf-mcp-server
    • Initialize it with a README file
  2. Use the provided setup script to push your code to GitHub:

# For a new repository
./setup-github-fixed.sh yourusername

# If the repository already exists and you want to overwrite its content
./setup-github-fixed.sh yourusername --force

The script will:

  • Initialize git if needed
  • Set up the remote repository
  • Commit your changes
  • Try to push to GitHub (with options to handle existing repositories)
  1. Configure GitHub Actions for CI/CD (optional):
    • Create a .github/workflows directory
    • Add a workflow file for testing and building the server

Using with AI Assistants

To use this MCP server with AI assistants like Claude, you need to:

  1. Install the server:

    Option 1: Install from GitHub (after pushing your code):

    npm install -g yourusername/nsaf-mcp-server
    

    Option 2: Install from your local directory:

    # Navigate to the nsaf-mcp-server directory
    cd nsaf_mcp_server
    
    # Install dependencies and build
    npm install
    npm run build
    
    # Install globally from the local directory
    npm install -g .
    
  2. Add the server to your MCP settings configuration:

For Claude Desktop app, edit ~/Library/Application Support/Claude/claude_desktop_config.json (on macOS):

{
  "mcpServers": {
    "nsaf": {
      "command": "nsaf-mcp-server",
      "args": [],
      "env": {},
      "disabled": false,
      "autoApprove": []
    }
  }
}

For Cline, edit /Users/onthego/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json:

{
  "mcpServers": {
    "nsaf": {
      "command": "nsaf-mcp-server",
      "args": [],
      "env": {},
      "disabled": false,
      "autoApprove": []
    }
  }
}

Available Tools

run_nsaf_evolution

Run NSAF evolution with specified parameters.

Parameters:

  • population_size: Size of the agent population (default: 20)
  • generations: Number of generations to evolve (default: 10)
  • mutation_rate: Mutation rate (0.0-1.0) (default: 0.2)
  • crossover_rate: Crossover rate (0.0-1.0) (default: 0.7)
  • architecture_complexity: Complexity of the agent architecture ('simple', 'medium', 'complex') (default: 'medium')

compare_nsaf_agents

Compare different NSAF agent architectures.

Parameters:

  • architectures: List of architectures to compare (default: ['simple', 'medium', 'complex'])

License

MIT

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