What authentication methods are supported?
The recommended method is Service Account authentication using `client_id` and `client_secret`. User account authentication is documented as a fallback.
@Alation
基本信息
Python library for integrating the Alation API into agentic workflows
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"alation-ai-agent-sdk": {
"command": "uv",
"args": [
"pip",
"install",
"alation-ai-agent-sdk==1.0.0rc3"
]
}
}
}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。
The Alation AI Agent SDK enables AI agents to access and leverage metadata from the Alation Data Catalog. It is designed for developers and data teams who want to integrate AI agents with their data catalog for tasks like search, discovery, and curation.
Install the SDK via pip with uv, then configure it with your Alation instance credentials using ServiceAccountAuthParams. You can use the core SDK directly, or integrate with LangChain or MCP (Model Context Protocol) via separate packages.
The recommended method is Service Account authentication using `client_id` and `client_secret`. User account authentication is documented as a fallback.
Python 3.10 or higher, access to an Alation Data Catalog instance, and a valid refresh token or client credentials.
The remote MCP server allows clients to connect without installing the SDK locally. After a one-time authorization setup, you can add a URL like `https://<your_instance>/ai/mcp` to your MCP client.
Supported tools include `alation_context`, `bulk_retrieval`, `data_quality_tool`, `get_custom_fields_definitions`, `get_data_products`, `get_data_sources_tool`, `get_signature_creation_instructions`, and `lineage`.
Agents include `catalog_context_search_agent`, `custom_agent`, `query_flow_agent`, and `sql_query_agent`.

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