Db Metadata Extractor Mcp
Extract schemas and metadata from Postgres, Snowflake, SQL Server, BigQuery, and Oracle so your agent can plan migrations and APIs accurately.
Overview
DB Metadata Extractor MCP is a MCP server for the Build phase that extracts database metadata from PostgreSQL, Snowflake, SQL Server, BigQuery, and Oracle.
What is this MCP server?
- Metadata extraction for PostgreSQL, Snowflake, SQL Server, BigQuery, and Oracle
- PyPI package db-metadata-extractor-mcp plus optional OCI Docker image
- Python runtime hint with stdio MCP transport
- Version 0.1.6 with dual install paths (pypi and oci)
- Focused on catalog introspection, not arbitrary query execution
- 5 supported database engines: PostgreSQL, Snowflake, SQL Server, BigQuery, Oracle
- Server version 0.1.6
- Two package channels: PyPI db-metadata-extractor-mcp and OCI Docker image
What problem does it solve?
Agents drafting SQL or backend code without live schema context routinely assume wrong column names and miss warehouse-specific objects.
Who is it for?
Solo developers wiring data-heavy backends who need trustworthy schema snapshots inside Claude Code or Cursor.
Skip if: Teams that only need a GUI schema browser and never want database credentials in an agent environment.
What do I get? / Deliverables
After you run the PyPI or Docker MCP server with valid DB credentials, your agent can introspect supported databases via dedicated metadata tools.
- Structured metadata from PostgreSQL, Snowflake, SQL Server, BigQuery, or Oracle
- Agent-grounded schema context for migrations and API design
- Deployable via PyPI 0.1.6 or matching OCI container
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Journey fit
Backend build work depends on knowing real table shapes, keys, and dialect quirks before agents generate SQL or ORM models. Backend is where database contracts are defined; metadata extraction prevents hallucinated columns during implementation.
How it compares
Database catalog introspection MCP, not a hosted Postgres admin UI or ETL orchestration skill.
Common Questions / FAQ
Who is DB Metadata Extractor MCP for?
It is for builders and data-minded indie devs who want MCP-driven schema and metadata extraction across five enterprise database engines.
When should I use DB Metadata Extractor MCP?
Use it during build when designing APIs, migrations, or agent-generated SQL and you need accurate metadata from an existing database.
How do I add DB Metadata Extractor MCP to my agent?
Install db-metadata-extractor-mcp from PyPI or run the published OCI image, configure stdio in your MCP host, and supply connection settings your server documentation requires.