Data Agents Platform MCP Server

@HotTechStack

代码仓库主页

基本信息

分类

数据与分析

许可证

MIT

传输方式

stdio

作者

HotTechStack

关于 Data Agents Platform MCP Server

Data Agents are intelligent assistants built by data engineers to help non-data professionals navigate the organization’s data infrastructu

#data-science #database#dataengineering#genai #agentic-ai #mcp-server

Data Agents Platform MCP Server 配置

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该服务器的 README 中没有可解析的 MCP 配置块，请前往代码仓库查看安装说明。

代码仓库

Data Agents Platform MCP Server 工具

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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 🤖 Data Agents Platform?

The platform is an agentic AI that uses generative AI to automate and streamline data engineering workflows. It enables multi-agent collaboration with specialized data engineering agents and supports multiple AI backends.

How to use 🤖 Data Agents Platform?

Deploy with Docker Compose or run locally with pnpm. After starting containers, upload the n8n workflow, configure API keys in Docker Compose and n8n, then visit http://localhost:3000 to interact with agents.

Key features of 🤖 Data Agents Platform

Multi-agent collaboration with specialized data engineering agents
Multiple backend support (OpenAI, Claude, Gemini, Ollama)
n8n integration for agent orchestration
Strategy-based approach for various data engineering tasks
Modern dark UI inspired by LobeChat
Docker ready with Docker Compose

Use cases of 🤖 Data Agents Platform

Automate data pipeline building with Pipeline Engineer agent
Design data infrastructure using Data Architect agent
Analyze and interpret complex data with Data Analyst agent
Apply statistical models with Data Scientist agent
Ensure data quality and compliance with Governance Specialist agent

常见问题

What AI backends does it support?

It supports OpenAI, Claude, Gemini, and Ollama for private deployments.

Can I run the platform without Docker?

Yes, you can run locally using `pnpm install` and `pnpm run dev`, optionally with your own hosted n8n instance.

How do I configure API keys?

Update API keys in the Docker Compose file or directly in the n8n workflow blocks for each model provider.

What is the current development status?

The project is in Alpha stage.

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