Happy slice of mcp pizzaMCP.pizza

OpenMetadata

MCP.Pizza Chef: open-metadata

This tool gives your AI assistant a map of your company's data: what each dataset means, who owns it, whether it can be trusted, and how different reports and dashboards connect to one another. Instead of guessing at confusing column names or redoing research someone already did, your assistant can look up definitions, check data quality, trace where a number came from, and pull up past notes and decisions about a dataset before it answers your question.

Data
Web/Research

Use This MCP server To

Ask what a business term or metric actually means Find out who owns a dataset before I use it Check whether a report's data is fresh and trustworthy Trace where a number in a dashboard came from See what other reports would break if data changes Look up past notes and decisions about a dataset Find which reports rely on a specific data source

README

OpenMetadata

Commit Activity Release

The Open Context Layer for AI

The largest and fastest-growing open-source project for AI context, data cataloging, and metadata management.

OpenMetadata is the open platform for trusted data context, organizational memory, and business semantics for every data user, AI assistant, and agent.

OpenMetadata connects technical metadata, data quality signals, lineage, column-level lineage, ownership, usage, policies, conversations, memories, glossaries, classifications, metrics, domains, data contracts, and data products into a unified metadata knowledge graph. With 130+ connectors, open metadata standards, semantic search, APIs, SDKs, and an MCP server, OpenMetadata gives every user and AI system the governed context it needs to discover, understand, trust, remember, and use data.

AI does not need another raw database connector. AI needs context + memory.

OpenMetadata: The Open Context Layer for AI

OpenMetadata provides the context AI needs to know:

  • what data exists
  • what it means
  • who owns it
  • how it is used
  • where it came from
  • where it flows
  • whether it is fresh, tested, certified, and trusted
  • which business concepts, classifications, glossary terms, policies, contracts, and data products apply
  • what downstream dashboards, pipelines, metrics, ML models, and applications depend on it
  • what conversations, decisions, assumptions, and memory nuggets have already been captured about it

Why OpenMetadata for AI?

AI systems need more than data access. They need governed context, business meaning, trust signals, lineage, usage, ownership, standards, and organizational memory.

A direct connection to a warehouse, lake, dashboard, or pipeline exposes raw structures. It does not tell an AI assistant what the data means, whether it is certified, who owns it, which policies apply, what contract governs it, what breaks if it changes, or what the organization has already learned about it.

OpenMetadata is the open context layer that gives every data user and AI agent the full picture of enterprise data.

OpenMetadata brings together five capabilities:

  1. Context — technical, operational, trust, usage, and lineage metadata from across the data ecosystem.
  2. Semantics — business meaning through glossaries, metrics, classifications, domains, policies, ontologies, and data products.
  3. Knowledge Graph — relationships connecting assets, columns, people, teams, quality, lineage, policies, memories, contracts, and business concepts.
  4. Memory — conversations, AI threads, decisions, assumptions, runbooks, remediation notes, and reusable memory nuggets that preserve tribal knowledge.
  5. Activation — MCP, Semantic Search, APIs, SDKs, events, and workflows that make context usable by AI assistants, agents, applications, and humans.

With OpenMetadata, users and AI agents can answer:

OpenMetadata FAQ

Can I use this to find out who owns a piece of data before I use it?
Yes — you can ask your assistant to look up the owner, team, and contact information for a dataset instead of hunting down the right person yourself.
Can I use this to check whether a report is trustworthy before I present it?
Yes — you can ask whether a dataset has passed its freshness and quality checks, and whether it has been certified, before you rely on it.
Do I need a developer to set this up?
No — it connects through a hosted web address, so you can add it to your assistant's settings without installing anything or writing code.
Do I need an account to use this?
You will need access to an existing setup of this platform at your organization, since it is the system that stores your company's data information rather than something that comes pre-loaded with data on its own.
Which AI assistants can I use this with?
It is built to work with any assistant that supports the Model Context Protocol, which currently includes tools like Claude, ChatGPT, and Gemini-based assistants that offer this kind of connection.
Will my assistant be able to see raw data, like actual customer records?
No — it shares information about your data, such as descriptions, ownership, and quality results, not the actual rows and values stored inside your databases.
Can it tell me what might break if a certain report or column changes?
Yes — it can trace the dashboards, pipelines, and other datasets that depend on the one you are asking about, so you can see the downstream impact.