PostgreSQL Analysis & ER Diagrams

What it is

A PostgreSQL server built around two jobs: working out what an unfamiliar database actually contains, and then operating on it. Schema extraction is deterministic; the explanation layer is optional and runs through a local Ollama model. It carries 27 tools spanning analysis, CRUD, schema modification, query optimisation, import and export, transactions and monitoring.

What you get

• Schema understanding first — analyze_database returns the full structure plus detected junction tables, implicit relationships, join suggestions, PlantUML ER, class and component diagrams and Markdown documentation; get_table_details does the same for one table; render_database_diagrams writes them out as SVG, PNG or PDF
• explain_database adds a business explanation and quality recommendations through a local LLM, and get_database_info folds table listing, service status and quick statistics into one call
• Reads that consolidate rather than multiply — crud_query for raw parameterised SQL, crud_get with a mode of records, count, distinct or paginate
• Writes with the same shape — crud_insert detects single versus batch from the payload, crud_update covers single, batch and column updates, crud_delete handles records, truncate and drop, crud_rename covers tables and columns
• Schema work — crud_create_table, crud_create_view, crud_create_index, plus mod_column, mod_index, mod_constraint, mod_add_constraint and mod_view for listing and dropping
• Performance tools — query_explain for estimated or actual plans, query_analyze_indexes to suggest missing indexes and find unused ones in the same call
• Data movement and search — data_export to CSV, JSON or SQL inserts, data_import with a conflict action, data_search with case-insensitive, case-sensitive or fuzzy matching
• transaction_execute runs several statements atomically with rollback, transaction_backup_table snapshots a table and returns the restore SQL, and monitoring_database_stats covers size, connections, cache hit ratio, slow queries and locks

Requirements

Python 3.11 or higher, uv, and a PostgreSQL database. Connection settings go in a .env as DB_HOST, DB_PORT, DB_NAME, DB_USER and DB_PASSWORD. The AI explanation path is optional and needs an Ollama server, configured through OLLAMA_BASE_URL and OLLAMA_MODEL. Start it with uv run postgresql_server.py. Every operation uses parameterised queries with table and column name validation.

Setup effort

Build from source — git clone https://github.com/prasanna00019/MCP-ToolHub

Tools you get

27 tools named in the project's documentation.

Requires

• uv
• Python 3.11+
• A PostgreSQL database
• DB_PASSWORD in your environment