MCP OpenMetadata
@pfldy2850
About MCP OpenMetadata
mcp-openmetadata
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp-openmetadata": {
"command": "uv",
"args": [
"pip",
"install",
"mcp-openmetadata"
]
}
}
}Tools
No tools detected
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is MCP OpenMetadata?
MCP OpenMetadata is a FastMCP-based server that provides a subset of OpenMetadata APIs for querying and managing metadata. It offers tools for searching entities, retrieving table metadata, columns, ownership information, and sample data—designed for AI assistants to interact with an OpenMetadata instance.
How to use MCP OpenMetadata?
Install the package via uv pip install mcp-openmetadata or pip install mcp-openmetadata. Configure it in your MCP client with the command python -m mcp_openmetadata.server and environment variables for authentication (OPENMETADATA_URI plus either OPENMETADATA_JWT_TOKEN for token auth or OPENMETADATA_USERNAME/OPENMETADATA_PASSWORD for basic auth). Then invoke any of the provided tools from your LLM.
Key features of MCP OpenMetadata
- Search entities using query text with pagination and sorting
- Retrieve paginated list of tables with basic information
- Get detailed table information by fully qualified name
- Fetch table columns and ownership details
- Access sample data from specified tables
- Supports token and basic authentication methods
Use cases of MCP OpenMetadata
- An AI assistant listing all database tables in an OpenMetadata instance
- Finding tables by column name or tag to locate relevant data assets
- Retrieving column schemas and ownership for data governance checks
- Getting sample rows to understand table content before querying
- Integrating metadata discovery into automated data lineage or catalog workflows
FAQ from MCP OpenMetadata
How does it compare to using the OpenMetadata API directly?
The server returns optimized, context-friendly results instead of raw API responses that may contain excessive data. Not all OpenMetadata APIs are exposed; see the Supported APIs document for the list.
What are the runtime dependencies?
Python 3.10 or later, plus the fastmcp, httpx, and mcp-openmetadata packages.
Where does the server connect to?
It connects to an OpenMetadata instance via the configured OPENMETADATA_URI environment variable (default http://localhost:8585). No external cloud service is involved.
What authentication methods are supported?
Two options: token authentication (using OPENMETADATA_JWT_TOKEN) or basic authentication (using OPENMETADATA_USERNAME and OPENMETADATA_PASSWORD).
What transport or protocol does the server use?
It is a FastMCP server, so it uses the MCP protocol over stdio transport by default (as configured in the MCP client).
Frequently asked questions
How does it compare to using the OpenMetadata API directly?
The server returns optimized, context-friendly results instead of raw API responses that may contain excessive data. Not all OpenMetadata APIs are exposed; see the Supported APIs document for the list.
What are the runtime dependencies?
Python 3.10 or later, plus the `fastmcp`, `httpx`, and `mcp-openmetadata` packages.
Where does the server connect to?
It connects to an OpenMetadata instance via the configured `OPENMETADATA_URI` environment variable (default `http://localhost:8585`). No external cloud service is involved.
What authentication methods are supported?
Two options: token authentication (using `OPENMETADATA_JWT_TOKEN`) or basic authentication (using `OPENMETADATA_USERNAME` and `OPENMETADATA_PASSWORD`).
What transport or protocol does the server use?
It is a FastMCP server, so it uses the MCP protocol over stdio transport by default (as configured in the MCP client).
Basic information
More Other MCP servers
Peekaboo MCP – lightning-fast macOS screenshots for AI agents
steipetePeekaboo is a macOS CLI & optional MCP server that enables AI agents to capture screenshots of applications, or the entire system, with optional visual question answering through local or remote AI models.
Production-ready MCP integrations for AI applications
Klavis-AIKlavis AI: MCP integration platforms that let AI agents use tools reliably at any scale
Codelf
unbugA search tool helps dev to solve the naming things problem.
Activepieces
activepiecesAI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents
Unity MCP ✨
justinpbarnettUnity MCP acts as a bridge between AI assistants and your Unity Editor. Give your LLM tools to manage assets, control scenes, edit scripts, and automate tasks within Unity.
Comments