Alation MCP. Discover data assets and audit lineage via conversation.
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Alation MCP Server. Connect your AI agent to your data catalog to search assets, audit metadata, and query data using natural conversation.
This server lets you discover schemas, trace data lineage, and list saved SQL queries directly from your AI client, making data governance and analysis accessible without writing code.
What your AI agents can do
Get lineage
Traces the data flow path to show how an asset is populated and what assets depend on it.
Get object metadata
Retrieves detailed information about a specific data asset, including its descriptions and ownership.
Get query results
Fetches the cached output from a previously run SQL query.
Your agent searches the catalog using keywords and advanced filters to locate specific schemas, tables, or data sources.
Your agent retrieves detailed metadata for any object, including descriptions, data stewards, and classification tags.
Your agent traces the data lineage, showing the source and all downstream assets that rely on a specific table.
Your agent retrieves a list of saved SQL queries and fetches the cached results from previous executions.
Your agent lists and audits custom governance fields tied to specific catalog objects.
Your agent lists the specific columns and their definitions for any given table.
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Alation MCP Server: 10 Tools for Data Asset Management
Use these tools to search the catalog, audit metadata, trace data lineage, and manage data assets through natural conversation with your AI client.
019d754bget lineage
Traces the data flow path to show how an asset is populated and what assets depend on it.
019d754bget object metadata
Retrieves detailed information about a specific data asset, including its descriptions and ownership.
019d754bget query results
Fetches the cached output from a previously run SQL query.
019d754blist columns
Lists all column names and their data types for a specified table.
019d754blist custom fields
Shows a list of custom governance fields defined on the catalog object.
019d754blist data sources
Lists all the primary data sources registered in the catalog.
019d754blist saved queries
Lists the names of SQL queries that have been saved in the catalog.
019d754blist schemas
Lists all schemas contained within a given data source.
019d754blist tables
Lists all tables that exist within a specific schema.
019d754bsearch catalog
Searches the entire catalog using keywords to find relevant data assets.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Alation, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
You connect your AI agent to your data catalog. This server lets your agent search assets, audit metadata, and query data using natural conversation. Your agent finds schemas, traces data lineage, and lists saved SQL queries right from your AI client, making data governance and analysis totally accessible without writing code.
Finding Data Assets and Schemas
Your agent searches the entire catalog using keywords and advanced filters to locate specific schemas, tables, or data sources. It lists all data sources registered in the catalog, and it lets your agent list all schemas within a given data source, and it lists all tables that exist within a specific schema.
Inspecting Data Details and Owners
Your agent retrieves detailed metadata for any object, getting its descriptions and ownership information. It shows a list of custom governance fields defined on the catalog object, and it lets your agent list all column names and their data types for any given table.
Mapping Data Flow and Dependencies
Your agent traces the data lineage to show the data flow path, detailing how an asset is populated and what other assets depend on it. It lets your agent search the entire catalog using keywords to find relevant data assets.
Listing and Auditing Saved Queries
Your agent retrieves a list of saved SQL queries and fetches the cached output from previous executions. It lets your agent list all names of SQL queries that have been saved in the catalog.
Core Capabilities
Your agent can use search_catalog to search the entire catalog using keywords to find relevant data assets. It uses get_object_metadata to retrieve detailed information about a specific data asset, including its descriptions and ownership. It uses get_lineage to trace the data flow path to show how an asset is populated and what assets depend on it.
It uses list_columns to list all column names and their data types for a specified table. It uses list_custom_fields to show a list of custom governance fields defined on the catalog object. It uses list_data_sources to list all the primary data sources registered in the catalog. It uses list_saved_queries to list the names of SQL queries that have been saved in the catalog.
It uses list_schemas to list all schemas contained within a given data source. It uses list_tables to list all tables that exist within a specific schema. Finally, it uses get_query_results to fetch the cached output from a previously run SQL query.
How Alation MCP Works
- 1 Subscribe to the server and provide your Alation Instance URL and API Access Token.
- 2 Your AI client sends a natural language request (e.g., 'Show me the lineage for X').
- 3 The server executes the appropriate tool (e.g.,
get_lineage) and returns the structured data to your agent for a clear answer.
The bottom line is, you talk to your agent, and the server handles the complex data lookup and governance checks.
Who Is Alation MCP For?
The data analyst who needs to find a specific table for a report but can't remember the exact name. The data governor who must audit metadata completeness across hundreds of assets. The BI lead who needs to know if a metric they are using is reliable. This is for anyone who needs to understand data relationships without deep SQL or API calls.
Uses the server to quickly find relevant tables and schemas for reporting or analysis by searching the catalog.
Audits metadata completion and manages custom field values across the catalog to maintain compliance.
Traces data lineage and inspects column definitions using simple commands, verifying data flow before writing code.
Retrieves saved queries and monitors data asset endorsements to ensure reports use approved data sources.
What Changes When You Connect
- Find assets instantly. Instead of manually navigating through dozens of folders, use
search_catalogto find tables and schemas just by mentioning keywords like 'Customer ROI'. - Audit data trust. Use
get_object_metadatato instantly check who owns a dataset, what its official description is, and if it has required governance tags. - Map data flow. When you suspect data is wrong, run
get_lineageto trace it back to the source. You immediately see every upstream table and every dashboard that consumes it. - Review past work. Use
list_saved_queriesandget_query_resultsto instantly see the results of a report run last week, saving you from re-running expensive queries. - Keep governance clean.
list_custom_fieldslets you audit governance fields, ensuring every critical data asset has the required ownership and compliance information attached. - Verify structure. If you're unsure about a table's structure,
list_columnsgives you a quick list of all columns and their data types without needing to write aDESCRIBEstatement.
Real-World Use Cases
Finding a specific metric's source
A data analyst needs the source for a 'Global Sales' metric. Instead of knowing the exact schema path, they ask their agent to 'Show me the lineage for Global Sales'. The agent uses get_lineage and returns the full path, allowing the analyst to find the correct source table immediately.
Checking data reliability before a presentation
A BI lead is prepping a deck and wants to confirm a data source's reliability. They ask the agent to 'Check the metadata for the Sales table'. The agent runs get_object_metadata, verifying the steward and checking if the asset has the 'Endorsed' tag, ensuring the data is trustworthy for the meeting.
Investigating data discrepancies
An engineer notices a discrepancy in a report. They tell the agent to 'Trace the data from the raw staging area to the final report'. The agent uses get_lineage, pinpointing exactly which transformation step or table is introducing the bad data, saving hours of debugging.
Quickly reviewing old reports
A data scientist wants to see the results of a query run last month. They ask the agent to 'Show me the results for the monthly churn report'. The agent uses list_saved_queries and then get_query_results, providing the cached data immediately without needing to re-run the job.
The Tradeoffs
Manual manual data lookup
Logging into the catalog UI, clicking through schemas, and manually filtering until you find the right table. This takes 10-15 minutes of clicking and searching.
→
Ask your agent to search_catalog with keywords. The agent pulls up the list of relevant assets instantly, bypassing the entire UI navigation process.
Assuming data integrity
Using a metric in a report because it 'looks right' but never checking its lineage. You risk basing major decisions on flawed or deprecated data sources.
→
Run get_lineage first. This verifies the data's entire path and tells you exactly what source tables feed the metric, confirming its integrity.
Fragmented metadata checks
To understand a table, you have to check the schemas, then manually check the columns, and then check the custom fields in three different tabs.
→
Use get_object_metadata and list_custom_fields in one conversation. The agent gathers all necessary governance details in a single, consolidated response.
When It Fits, When It Doesn't
Use this if your primary goal is understanding the 'why' and 'where' of your data. Specifically, if you need to trace dependencies (get_lineage), check the origin (list_data_sources), or audit ownership/compliance (get_object_metadata), this server is essential. Don't use it if you just need to know the basic connection string or if you are building a complex ETL pipeline from scratch. For simple connection details, use a dedicated credential vault. For simple data retrieval without context, a basic SQL query tool will suffice. This server provides the necessary context layer that makes raw data usable.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Alation. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
VINKIUS INFRASTRUCTURE
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Finding the source of truth shouldn't feel like a deep dive into documentation.
Today, finding a single data source requires a multi-step process. You check the main catalog search, then you jump into the schema view, and if that doesn't work, you download the metadata documentation, which is usually outdated. You spend time clicking tabs and copy-pasting asset names just to figure out if the data is approved.
With the Alation MCP Server, you just talk to your agent. You ask, 'Where does the quarterly revenue data come from?' and the agent executes `get_lineage`, giving you the full, verified path in seconds. You get immediate, actionable intelligence, not links to documents.
Alation MCP Server: Get a full data profile instantly
Before, you had to manually list the schemas, then list the tables within those schemas, and then separately look up the column definitions for each table. It was a tedious, multi-page chore.
Now, your agent handles all that. You ask for the object details, and the server runs `get_object_metadata` and `list_columns` simultaneously, providing a single, comprehensive view of the data asset's structure and governance details.
Common Questions About Alation MCP
How do I use the `search_catalog` tool with Alation MCP Server? +
You ask your agent to search the catalog using natural language, specifying keywords like 'Customer ROI'. The agent executes search_catalog and returns a list of matching schemas and tables.
Can `get_lineage` track data from multiple sources? +
Yes. The get_lineage tool maps the flow, showing all upstream sources and all downstream reports, even if they cross different schemas or data sources.
What is the difference between `list_tables` and `search_catalog`? +
list_tables shows you every table in a specific, defined schema. search_catalog searches the entire catalog using keywords across all available data sources.
Does `get_query_results` require me to know the query? +
No. You just tell the agent which saved query you want, and it uses get_query_results to fetch the cached output, saving you the effort of re-running the SQL.
How do I find out who is responsible for a data asset using `get_object_metadata`? +
You ask the agent for the metadata. The tool runs get_object_metadata and returns details including the designated data steward or owner for that asset.
How does `list_data_sources` help me inventory my entire data environment? +
It lists all data sources connected to your Alation instance. This allows you to get a high-level view of every domain your data assets live in, which is crucial for initial inventory checks.
What if I need to check governance fields that aren't related to a specific object? Can `list_custom_fields` do that? +
Yes, list_custom_fields retrieves all custom governance fields across your catalog. This lets you audit or manage field definitions globally, regardless of which specific table or schema they apply to.
When should I use `list_saved_queries` instead of `get_query_results`? +
list_saved_queries shows you the names and definitions of queries you saved. You use this to see what reports exist. Then, you use get_query_results to fetch the actual cached data for one of those saved queries.
How do I find my Alation API Access Token? +
Log in to Alation, click on your user avatar, and go to Account Settings > Authentication. You can generate a Refresh Token there, which can then be used to obtain short-lived Access Tokens for the API.
Can I search for specific table types? +
Yes! The search_catalog tool allows you to apply filters by object type (otype), such as table, schema, or attribute. This ensures your search results are highly relevant.
Does this support viewing data lineage? +
Yes, the get_lineage tool retrieves technical metadata describing the relationships and data flow between different assets in your catalog.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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