MCP Server

MCP MCP server exists for a simple reason — assistants are far more useful when they can act on MCP directly instead of describing what you should do. A Model Context Protocol (MCP) server for DataHub.

What you get

DataHub is an open-source context platform that gives organizations a single pane of glass across their entire data supply chain. DataHub unifies data discovery, governance, and observability under one roof for every table, column, dashboard pipeline, document, and ML Model.

Setting it up

Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client.

What the assistant can call

Once MCP is connected, these are the calls the assistant has available:

• search — Find relevant datasets for the question
• list_schema_fields — Understand dataset structure
• get_lineage — Assess data authority and provenance
• get_dataset_queries — Learn how the dataset is typically queried
• get_entities — Retrieve related entities for context
• get_lineage_paths_between — Understand deeper relationships between datasets

Before you rely on it

• It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
• MCP clients confirm each tool call by default. Leave that on until you have watched what the mcp mcp server does with a few real requests.

Choosing this one

This sits in the developer tooling group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. MCP's toolset — search, list_schema_fields, get_lineage and 3 more — is a fair guide to whether it matches your workflow.

This entry was verified against MCP's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.