postgres-schema-mcp
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- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to safely interact with PostgreSQL databases through read-only operations, providing schema discovery, table inspection, and query execution capabilities with structured context awareness.MIT
- FlicenseNot gradedqualityDmaintenanceEnables AI clients to explore a PostgreSQL database schema and run read-only queries, including listing tables, describing columns, executing SELECT queries, and retrieving foreign key relationships.-
- AlicenseNot gradedqualityCmaintenanceEnables secure read-only access to PostgreSQL databases, allowing users to list tables, query schemas, execute SELECT statements, and inspect table structures through natural language interactions.551 npm4MIT
- FlicenseAqualityDmaintenanceEnables AI agents to inspect and query PostgreSQL databases safely, with features like listing tables, retrieving schemas, and running read-only SQL queries.3-
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to query a PostgreSQL database through a small set of controlled, read-only tools for schema inspection, row lookup, and aggregate statistics.1MIT
- AlicenseNot gradedqualityDmaintenanceProvides read-only access to PostgreSQL databases, enabling LLMs to inspect database schemas and execute read-only SQL queries.113,568 npmMIT
TDQS
Scored across 9 tools
Each tool has a clearly distinct purpose: schema discovery, table listing, detailed table description, column search, relationship traversal, data preview, query execution, query planning, and documentation export. There is no practical overlap; even sample_rows and run_select differ in that one is a convenience for previewing a table and the other is for arbitrary read-only queries.
Eight of nine tools follow a clear verb_noun snake_case pattern (list_schemas, describe_table, run_select, etc.), making the set predictable. The single exception is table_relationships, which uses a noun_noun form, creating a minor inconsistency without causing confusion.
Nine tools is well-scoped for a PostgreSQL schema and querying server. Each tool fills a distinct role in the workflow from schema discovery to query tuning, and none feel redundant or bolted on.
The tool surface covers the full read-only lifecycle: schema/table discovery, column search, relationship mapping, data sampling, safe SELECT execution, query planning, and exporting a data dictionary. There are no obvious dead ends for an agent exploring or querying a database, and the explicit lack of write mode is a deliberate boundary rather than a gap.