Allows agents to send notifications and alerts to Discord channels, particularly for autonomous monitoring mode.
Support for Google Gemini AI models to power agents that interact with and monitor the Starknet blockchain.
Provides a ready-to-use NestJS server with web interface for agent interaction and monitoring.
Built on Node.js and available as an NPM package for integration into Node.js applications.
Integration with Ollama's open-source AI models to create blockchain agents for Starknet operations.
Integration with OpenAI models to create AI agents capable of performing Starknet blockchain operations.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Snakcreate an agent for automated DeFi trading on Starknet"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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)
Docker and Docker compose installed
Node.js and pnpm installed
Installation
git clone https://github.com/kasarlabs/snak.git
cd snak
pnpm installConfiguration
Create a
.envfile by copying.env.example:
cp .env.example .envThen, 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_HOST=localhost
POSTGRES_DB=postgres
POSTGRES_PASSWORD=admin
POSTGRES_PORT=5432
# --- 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"Configure AI Models (Optional): The
config/models/default.models.jsonfile 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. Seeconfig/models/example.models.jsonfor the structure.The agent uses the
providerfield in the model configuration to determine which API key to load from the.envfile (e.g., ifproviderisopenai, it loadsOPENAI_API_KEY).Create your agent configuration file (e.g.,
default.agent.jsonormy_agent.json) in theconfig/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",
"max_iterations": "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"],
"mcp_servers": {
"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
Related MCP server: AgentCraft MCP Server
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
Install snak package
#using npm
npm install @snakagent
# using pnpm
pnpm add @snakagentCreate 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.
For detailed documentation visit docs.kasar.io