MCP Server LogoMCP Server
MCPsCategoriesDirectorySubmit
Submit
MCPsCategoriesDirectorySubmit
Submit

MCP Servers

A curated list of MCP Servers, featuring Awesome MCP Servers and Claude MCP integration.

Contact Us

[email protected]

About

Privacy PolicyTerms of Service

Resources

Model Context ProtocolMCP Starter GuideClaude MCP Servers

Community

GitHub

© 2026 mcpserver.cc © 2025 MCP Server. All rights reserved.

Privacy PolicyTerms of Service
  1. Home
  2. /Categories
  3. /Automation & Scripting
  4. /Snak
Snak

Snak

Created by kasarlabs•9 months ago
Visit Website

Build powerful and secure AI Agents powered by Starknet.

Automation & Scripting
AI AgentsStarknetAgent Engine

Snak Logo

NPM Version License GitHub Stars Node Version

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"
  1. 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).

  2. 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
  1. 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.


For detailed documentation visit docs.kasar.io

Prerequisites

  • •Familiarity with the server domain
  • •Basic understanding of related technologies
  • •Knowledge of Automation & Scripting

Recommended Server

Mcp Command Server

Mcp Command Server

Google Sheets Mcp

Google Sheets Mcp

Code Explainer Mcp

Code Explainer Mcp

A Cloudflare Worker that serves as an MCP (Model Context Protocol) server for code explanation. It analyzes and explains code with a comprehensive breakdown of structure and functionality.

View more → →

Details

Created

June 12, 2025

Last Updated

June 12, 2025

Category

Automation & Scripting

Author

kasarlabs

Share

More Server

Dingding_mcp_v2

Dingding_mcp_v2

Esxi Mcp Server

Esxi Mcp Server

A VMware ESXi/vCenter management server based on MCP (Model Control Protocol), providing simple REST API interfaces for virtual machine management.

Hana Mcp Server

Hana Mcp Server

Model Context Server Protocol for your HANA DB

Mcp Server Ts Trello

Mcp Server Ts Trello

TypeScript implementation of a Model Context Protocol (MCP) server for Trello integration