The Alation AI Agent SDK enables AI agents to access and leverage metadata from the Alation Data Catalog.
This SDK empowers AI agents to:
- Easily integrate with Alation's Data Catalog
- Address use cases like Asset Curation, Search & Discovery, Role Based Agents, and Data Analyst Agents
- Use natural language to search for relevant metadata
- Integrate seamlessly with AI frameworks like MCP
The project is organized into multiple components:
- Core SDK - Foundation with API client and context tools
- MCP Integration - Server implementation for Model Context Protocol
- LangChain Integration - Adapters for the LangChain framework
The core SDK provides the foundation for interacting with the Alation API. It handles authentication, request formatting, and response parsing.
This component integrates the SDK with the LangChain framework, enabling the creation of sophisticated AI agents that can reason about your data catalog.
Learn more about the LangChain Integration
The MCP integration provides an MCP-compatible server that exposes Alation's context capabilities to any MCP client.
Learn more about the MCP Integration
- Python 3.10 or higher
- Access to an Alation Data Catalog instance
- A valid refresh token or client_id and secret. For more details, refer to the Authentication Guide.
# Install core SDK
pip install alation-ai-agent-sdk
# Install LangChain integration
pip install alation-ai-agent-langchain
# Install MCP integration
pip install alation-ai-agent-mcpThe library needs to be configured with your Alation instance credentials. Depending on your authentication mode, you can use either UserAccountAuthParams or ServiceAccountAuthParams.
from alation_ai_agent_sdk import AlationAPI, ServiceAccountAuthParams
# Initialize the SDK with Service Account Authentication
auth_params = ServiceAccountAuthParams(
client_id="your_client_id",
client_secret="your_client_secret"
)
alation_api = AlationAPI(
base_url="https://your-alation-instance.com",
auth_method="service_account",
auth_params=auth_params
)If you cannot obtain service account credentials (admin only), see the User Account Authentication Guide for instructions.
A retrieval tool that pulls contextual information from the Alation catalog based on natural language queries.
Functionality
- Accepts user questions in natural language
- Performs query rewrites to optimize search results
- Returns relevant catalog data in JSON format
- Can return multiple object types in a single response
Usage
response = alation_ai_sdk.get_context(
"What certified data set is used to make decisions on providing credit for customers?"
)Input Parameters
question(string): The natural language querysignature(optional dict): The configuration controlling which objects and their fields
Returns
- JSON-formatted response of relevant catalog objects
A retrieval tool that pulls data products from the Alation catalog based on product ID or natural language queries.
Functionality
- Accepts product IDs for direct lookup
- Accepts user queries in natural language for discovery
- Returns relevant data products in JSON format
- Can return single or multiple results
Usage
response = alation_ai_sdk.get_data_products(
"12345" # Example product ID
)
response = alation_ai_sdk.get_data_products(
"Show me all data products related to sales"
)Input Parameters
product_id(string, optional): The ID of the product for direct lookupquery(string, optional): A natural language query to discover data products
Returns
- JSON-formatted response of relevant data products
A retrieval tool that pulls a set of objects from the Alation catalog based on a signature.
Functionality
- Retrieve catalog objects without conversational queries.
- Useful for having an LLM decide which items to use from a larger set.
- Accepts a signature defining which objects and the fields required.
- Returns relevant catalog data in JSON format
- Can return multiple object types in a single response
Usage
# Get tables from a specific datasource
bulk_signature = {
"table": {
"fields_required": ["name", "description", "columns"],
"search_filters": {
"fields": {"ds": [123]} # Specific datasource
},
"limit": 100,
"child_objects": {
"columns": {
"fields": ["name", "data_type", "description"]
}
}
}
}
response = sdk.bulk_retrieval(signature=bulk_signature)Input Parameters
signature(dict): The configuration controlling which objects and their fields
Returns
- JSON-formatted response of relevant data products
A tool for checking the status of asynchronous jobs.
Functionality
- Used to monitor progress and completion of async jobs.
- Accepts a job id
- Returns the job detail object including status
Input Parameters
job_id(int): The identifier of the asychronous job.
Returns
- JSON-formatted response of the job details
A tool to updates metadata for Alation catalog assets by modifying existing objects.
Supported object types
glossary_term: Individual glossary terms (corresponds to document objects)glossary_v3: Glossary collections (corresponds to doc-folder objects, i.e., Document Hubs)
Functionality
- Creates an async job that updates one or more object field values.
Input Parameters
- A list of objects to be updated which include the
id,otype,field_id, and the newvalue.
Returns
- validation error (dict) A dictionary containing a "error" value.
- on success (dict) A dictionary containing a "job_id" value.
A lineage retrieval tool to identify upstream or downstream objects relative to the starting object. Supports Column level lineage.
NOTE: This BETA feature must be enabled on the Alation instance. Please contact Alation support to do this. Additionally, the lineage tool within the SDK must be explicitly enabled.
Functionality
- Access the object's upstream or downstream lineage.
- Graph is filterable by object type.
- Helpful for root cause and impact analysis
- Enables custom field value propagation
Input Parameters
root_node(dict) The starting object. Must containidandotype.direction(upsteam|downstream) The direction to resolve the lineage graph from.limit(optional int) Defaults to 1,000.batch_size(optional int) Defaults to 1,000.max_depth(optional int) The maximumn depth to transerve of the graph. Defaults to 10.allowed_otypes(optional string[]) Controls which types of nodes are allowed in the graph.pagination(optional dict) Contains information about the request including cursor identifier.show_temporal_objects(optional bool) Defaults to false.design_time(optional 1,2,3) 1 for design time objects. 2 for run time objects. 3 for both design and run time objects.excluded_schema_ids(optional int[]) Remove nodes if they belong to these schemas.time_from(optional timestamp w/o timezone) Controls the start point of a time period.time_to(optional timestamp w/o timezone) Controls the ending point of a time period.
Returns
- (dict) An object containing the lineage graph, the direction, and any pagination values.
The SDK's alation-context and bulk_retrieval tools support customizing response content using signatures. This powerful feature allows you to specify which fields to include and how to filter the catalog results. For instance:
# Define a signature for searching only tables that optionally
# include joins and filters if relevant to the user question
signature = {
"table": {
"fields_required": ["name", "title", "description"],
"fields_optional": ["common_joins", "common_filters"]
}
}
# Use the signature with your query
response = sdk.get_context(
"What are our sales tables?",
signature
)For more information about signatures, refer to Using Signatures
- Planning an Integration - Practical considerations for getting the most out of your agents and the Alation Data Catalog.
- Using Signatures - How to customize your agent with concrete examples.
- Supported Object Types and Fields - See what's available.
Direct usage examples for the Alation AI Agent SDK:
- Basic Usage Example - Simple example showing SDK initialization and context queries.
- QA Chatbot Example - Interactive chatbot demonstrating conversation context and signature usage.
Enable agentic experiences with the Alation Data Catalog.
- MCP Integration - Getting the Alation MCP server up and running.
- Integration with Code Editors - Use the tools directly in your code editor.
- Testing with MCP Inspector - Steps for debugging and verification.
- Claude Desktop Integration - Leverage the Alation MCP server within Claude Desktop.
- LibreChat Integration - Create assistants and agents alike.
Harness the SDK to build complex agents and workflows.
- LangChain Integration - How to integrate the SDK into your LangChain agents.
- Basic Usage Example - A simple example.
- Multi Agent Example - A multi agent workflow with several SDK integration points.
The number of published agent frameworks and toolkits appears to be increasing every day. If you don't happen to see the framework or toolkit you're using here, it's still possible to adapt alation-ai-agent-sdk to your needs. It may be as simple as writing a wrapping function where a decorator is applied.
While we want to reach as many developers as possible and make it as convenient as possible, we anticipate a long tail distribution of toolkits and won't be able to write adapters for every case. If you'd like support for a specific toolkit, please create an issue to discuss.
