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OpenMetadata

Connects AI assistants to governed metadata, lineage, semantics, quality signals, policies, and organizational memory.

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Install OpenMetadata

Pick your client, then add it in one click or paste the config.

STDIOPython
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "openmetadata": {
      "command": "uvx",
      "args": [
        "data-ai-sdk"
      ]
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Install not yet sandbox-tested— we haven't run this command through our automated sandbox yet. Not a red flag; we're working through the catalog.

Overview

OpenMetadata MCP server connects AI assistants and agents to OpenMetadata’s governed metadata knowledge graph. It brings together technical metadata, business semantics, lineage, data quality, ownership, policies, contracts, data products, and captured organizational memory. The OpenMetadata platform collects this context through connectors, ingestion APIs, events, and SDKs, then makes it available through MCP, semantic search, APIs, and other activation paths. Reach for it when an agent needs business and governance context around enterprise data rather than direct access to a raw database.

Use cases

  • Answer questions about dataset ownership, meaning, freshness, and certification
  • Trace upstream and downstream impact across tables, columns, dashboards, and pipelines
  • Find glossary terms, metrics, classifications, policies, and data contracts for an asset
  • Retrieve decisions, incident notes, runbooks, and other organizational memory
  • Give agents governed context for enterprise data discovery and reasoning

Key features

  • Governed metadata access over MCP
  • Metadata knowledge graph with linked relationships
  • Technical metadata, lineage, quality, and trust context
  • Business semantics, policies, contracts, and data products
  • Asset-linked organizational memory
  • Open standards, APIs, SDKs, events, and semantic search

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked Today

Recent health check succeeded.

12/12 checks healthy over the last 39d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 6d ago via OSV.dev · data-ai-sdk (PyPI)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars15kStargazers on the source repository.
Last commitTodayMost recent push to the default branch.
Directory activity1 viewsConfig copies, upvotes, and views on AllMCPs.

How OpenMetadata works

What OpenMetadata does

OpenMetadata MCP gives AI assistants and agents access to the context stored in OpenMetadata’s metadata graph. That context spans databases, schemas, tables, columns, dashboards, charts, pipelines, APIs, search indexes, ML models, storage assets, topics, and other data-related resources. It also includes descriptions, joins, sample queries, owners, teams, domains, usage, and data products.

The graph adds the information needed to interpret and govern those assets. Agents can work with business terms, glossaries, metrics, KPIs, classifications, tags, policies, contracts, lifecycle states, certifications, and review workflows. Quality and trust signals include tests, suites, profiling results, freshness and volume checks, incidents, alerts, and observability history. Lineage connects upstream and downstream assets, including tables, columns, dashboards, pipelines, metrics, ML models, APIs, topics, and OpenLineage events.

OpenMetadata also preserves organizational knowledge. Conversations, AI threads, decisions, assumptions, runbooks, remediation notes, incident learnings, and reusable memory nuggets can be associated with assets, teams, users, data products, and agent workflows.

How it works

OpenMetadata uses a schema-first metadata graph. Its platform collects metadata from across a data ecosystem through more than 130 connectors, ingestion APIs, events, and SDKs. The collected information is normalized through open schemas and standards, then connected into relationships between assets, people, policies, quality checks, lineage, semantics, contracts, and memories.

MCP is one of the ways OpenMetadata activates this graph for AI systems. Other access and activation paths include semantic search, APIs, SDKs, events, webhooks, metadata applications, and AI workflows. The graph structure lets an agent follow relationships such as a dashboard depending on a table, a column carrying a classification, a pipeline producing a table, or a data contract applying to an asset.

Memory is represented as part of the same governed context rather than as a separate conversational store. A decision or conversation can be retained as a reusable memory and linked to the asset, metric, data product, or workflow it concerns.

Tools and capabilities

  • Exposes governed metadata context to AI assistants and agents through MCP.
  • Provides technical metadata for data assets and their structures.
  • Connects upstream and downstream lineage, including column-level relationships.
  • Surfaces quality, freshness, certification, testing, incidents, and trust signals.
  • Relates technical assets to glossaries, metrics, classifications, policies, domains, and data products.
  • Preserves conversations, decisions, assumptions, runbooks, and remediation knowledge as reusable memory.
  • Represents ownership, stewardship, teams, contracts, roles, and governance context.
  • Supports interoperability through standards including OpenLineage, DCAT, DPROD, PROV-O, RDF/OWL, JSON-LD, SHACL, JSON Schema, and ODCS.

The result is context for questions such as what a metric means, which datasets feed a dashboard, who owns a data product, whether a dataset is trusted, what downstream systems may be affected by a change, and which policies or business concepts apply.

Read the full README View source on GitHub

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Frequently Asked Questions about OpenMetadata

OpenMetadata is an MCP server that connects AI assistants and agents to OpenMetadata’s governed metadata knowledge graph. Its main access paths include MCP, semantic search, APIs, and SDKs, covering technical metadata, lineage, quality, ownership, policies, business semantics, data contracts, data products, and organizational memory.

OpenMetadata MCP provides technical metadata, business semantics, ownership, usage, quality and trust signals, lineage, policies, classifications, contracts, data products, and asset-linked organizational memory. This context helps agents understand what data exists, what it means, how it flows, and whether it is trusted.

OpenMetadata connects them in a shared metadata graph. Relationships link assets and columns to upstream and downstream lineage, owners, teams, glossary terms, metrics, classifications, policies, quality tests, contracts, domains, and data products, giving agents both structural and business context.

Yes. OpenMetadata can preserve conversations, AI threads, decisions, assumptions, runbooks, remediation notes, incident learnings, and reusable memory nuggets. These memories can be attached to assets, users, teams, data products, and agent workflows for later reuse.

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