Snak

npx mcpbar@latest install KasarLabs/snak -c claude

npx mcpbar@latest edit -c claude

{
  "mcpServers": {
    "Snak": {
      "command": "npx",
      "args": [
        "-y",
        "@npm_package_example/npx_server_example"
      ],
      "env": {
        "API_KEY": "YOUR_API_KEY"
      }
    }
  }
}

A Agent Engine for creating powerful and secure AI Agents powered by Starknet. Available as both an NPM package and a ready-to-use backend.

Quick Start

Prerequisites

• Starknet wallet (recommended: Argent X)
• AI provider API key (Anthropic/OpenAI/Google Gemini/Ollama)
• Node.js and pnpm installed

Installation

git clone https://github.com/kasarlabs/snak.git
cd snak
pnpm install

Configuration

1. Create a .env file by copying .env.example:

cp .env.example .env

Then, fill in the necessary values in your .env file:

# --- Starknet configuration (mandatory) ---
STARKNET_PUBLIC_ADDRESS="YOUR_STARKNET_PUBLIC_ADDRESS"
STARKNET_PRIVATE_KEY="YOUR_STARKNET_PRIVATE_KEY"
STARKNET_RPC_URL="YOUR_STARKNET_RPC_URL"

# --- AI Model API Keys (mandatory) ---
# Add the API keys for the specific AI providers you use in config/models/default.models.json
# The agent will automatically load the correct key based on the provider name.

# Example for OpenAI:
OPENAI_API_KEY="YOUR_OPENAI_API_KEY" # (e.g., sk-...)

# Example for Anthropic:
ANTHROPIC_API_KEY="YOUR_ANTHROPIC_API_KEY" # (e.g., sk-ant-...)

# Example for Google Gemini:
GEMINI_API_KEY="YOUR_GEMINI_API_KEY"

# Example for DeepSeek:
DEEPSEEK_API_KEY="YOUR_DEEPSEEK_API_KEY"

# Note: You do not need an API key if using a local Ollama model.

# --- General Agent Configuration (mandatory) ---
SERVER_API_KEY="YOUR_SERVER_API_KEY" # A secret key for your agent server API
SERVER_PORT="3001"

# --- PostgreSQL Database Configuration (mandatory) ---
POSTGRES_USER="admin"
POSTGRES_PASSWORD="admin"
POSTGRES_ROOT_DB="postgres" # Database used to create/manage the application database
POSTGRES_HOST="localhost"
POSTGRES_PORT="5454"

# --- LangSmith Tracing (Optional) ---
# Set LANGSMITH_TRACING=true to enable tracing
LANGSMITH_TRACING=false
LANGSMITH_ENDPOINT="https://api.smith.langchain.com"
LANGSMITH_API_KEY="YOUR_LANGSMITH_API_KEY" # (Only needed if LANGSMITH_TRACING=true)
LANGSMITH_PROJECT="Snak" # (Optional project name for LangSmith)

# --- Node Environment ---
NODE_ENV="development" # "development" or "production"

2. Configure AI Models (Optional): The config/models/default.models.json file defines the default AI models used for different tasks (fast, smart, cheap). You can customize this file or create new model configurations (e.g., my_models.json) and specify them when running the agent. See config/models/example.models.json for the structure.

   The agent uses the provider field in the model configuration to determine which API key to load from the .env file (e.g., if provider is openai, it loads OPENAI_API_KEY).

3. Create your agent configuration file (e.g., default.agent.json or my_agent.json) in the config/agents/ directory:

{
  "name": "Your Agent name",
  "group": "Your Agent group",
  "description": "Your AI Agent Description",
  "lore": ["Some lore of your AI Agent 1", "Some lore of your AI Agent 1"],
  "objectives": [
    "first objective that your AI Agent need to follow",
    "second objective that your AI Agent need to follow"
  ],
  "knowledge": [
    "first knowledge of your AI Agent",
    "second knowledge of your AI Agent"
  ],
  "interval": "Your agent interval beetween each transaction of the Agent in ms,",
  "chatId": "Your Agent Chat-id for isolating memory",
  "maxIterations": "The number of iterations your agent will execute before stopping",
  "mode": "The mode of your agent, can be interactive, autonomous or hybrid",
  "memory": {
    "enabled": "true or false to enable or disable memory",
    "shortTermMemorySize": "The number of messages your agent will remember"
  },
  "plugins": ["Your first plugin", "Your second plugin"],
  "mcpServers": {
    "nxp_server_example": {
      "command": "npx",
      "args": ["-y", "@npm_package_example/npx_server_example"],
      "env": {
        "API_KEY": "YOUR_API_KEY"
      }
    },
    "local_server_example": {
      "command": "node",
      "args": ["node /path/to/local_server/dist/index.js"]
    }
  }
}

You can simply create your own agent configuration using our tool on snakagent

Usage

Prompt Mode

Run the promt:

# start with the default.agent.json
pnpm run start

# start with your custom configuration
pnpm run start --agent="name_of_your_config.json" --models="name_of_your_config.json"

Server Mode

Run the server :

# start with the default.agent.json
pnpm run start:server

# start with your custom configuration
pnpm run start:server --agent="name_of_your_config.json" --models="name_of_your_config.json"

Available Modes

	Interactive Mode	Autonomous Mode
Prompt Mode	✅	✅
Server Mode	✅	✅

Implement Snak in your project

1. Install snak package

#using npm
npm install @snakagent

# using pnpm
pnpm add @snakagent

2. Create your agent instance

import { SnakAgent } from 'starknet-agent-kit';

const agent = new SnakAgent({
  provider: new RpcProvider({ nodeUrl: process.env.STARKNET_RPC_URL }),
  accountPrivateKey: process.env.STARKNET_PRIVATE_KEY,
  accountPublicKey: process.env.STARKNET_PUBLIC_ADDRESS,
  aiModel: process.env.AI_MODEL,
  aiProvider: process.env.AI_PROVIDER,
  aiProviderApiKey: process.env.AI_PROVIDER_API_KEY,
  signature: 'key',
  agentMode: 'interactive',
  agentconfig: y,
});

const response = await agent.execute("What's my ETH balance?");

Actions

To learn more about actions you can read this doc section. A comprehensive interface in the Kit will provide an easy-to-navigate catalog of all available plugins and their actions, making discovery and usage simpler.

To add actions to your agent you can easily follow the step-by-steps guide here

Contributing

Contributions are welcome! Feel free to submit a Pull Request.

License

MIT License - see the LICENSE file for details.

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For detailed documentation visit docs.kasar.io