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Snak MCP Server

@kasarlabs

代码仓库主页

基本信息

分类

其他

许可证

MIT

传输方式

stdio

作者

kasarlabs

提交者

antiyro

关于 Snak MCP Server

Build powerful and secure AI Agents powered by Starknet.

#starknet#ai-agents#blockchain

Snak MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "snak": {
      "command": "node",
      "args": [
        "/absolute/path/to/snak/mcp_server/snak/dist/index.js",
        "plugin_name_1",
        "plugin_name_2",
        "plugin_name_3"
      ]
    }
  }
}

Snak MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Snak?

An Agent Engine for creating powerful and secure AI Agents powered by Starknet, available as both an NPM package and a ready-to-use backend. It integrates with Starknet wallet (Argent X) and AI providers (Anthropic, OpenAI, Google Gemini, Ollama, DeepSeek). Designed for developers building autonomous or interactive agents on Starknet.

How to use Snak?

Clone the repository, install dependencies with pnpm, copy .env.example to .env and fill in Starknet credentials and AI API keys. Optionally configure AI models and agent settings in JSON files under config/. Run in prompt mode with pnpm run start or server mode with pnpm run start:server, optionally specifying custom agent and model configurations. Alternatively, install the @snakagent package and instantiate SnakAgent programmatically.

Key features of Snak

  • Supports multiple AI providers (OpenAI, Anthropic, Google Gemini, Ollama).
  • Customizable agent configuration with lore, objectives, knowledge, and plugins.
  • Two operating modes: interactive and autonomous.
  • Built-in short‑term memory and optional LangSmith tracing.
  • Integrates with MCP servers for extended functionality.
  • Available as both CLI/server and programmable NPM package.

Use cases of Snak

  • Build autonomous DeFi agents that execute transactions on Starknet.
  • Create interactive AI assistants for wallet queries (e.g., “What’s my ETH balance?”).
  • Develop automated trading bots with custom strategies and memory.
  • Deploy scalable agent backends with PostgreSQL persistence and server API.

常见问题

1

What prerequisites do I need?

A Starknet wallet (e.g., Argent X), an AI provider API key (or Ollama for local models), Docker and Docker compose, Node.js, and pnpm installed.

2

How can I switch between interactive and autonomous mode?

Set the `mode` field in your agent configuration file to `"interactive"` or `"autonomous"`. Both modes are supported in prompt and server runs.

3

Can I use my own AI model?

Yes. Edit `config/models/default.models.json` or create a new model config file, specifying `provider` and model name. The agent loads the corresponding API key from the `.env` file.

4

Where is agent data stored?

Agent memory and chat history are persisted in a PostgreSQL database (configured via `POSTGRES_*` env vars). Optional LangSmith tracing sends logs to LangSmith.

5

How do I add new actions/plugins to an agent?

Follow the step‑by‑step guide at [docs.kasar.io/add-agent-actions](https://docs.kasar.io/add-agent-actions). Plugins are listed in the agent config under `"plugins"`.

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