get_entity_attributes

ChatGPT

Get one entity type's columns/attributes. Call after get_schema, once per entity type your question touches — several can run in parallel. Returns a lean outline of ALL the entity type's columns (column name, type, attribute group, and any lookup-table JOINs needed to resolve UUID foreign keys to display values) — everything you need to write SQL with run_sql. entityType must match a name exactly as shown in get_schema (e.g. "Loan").

get_entity_attributes

ChatGPT

Get one entity type's columns/attributes. Call after get_schema, once per entity type your question touches — several can run in parallel. Returns a lean outline of ALL the entity type's columns (column name, type, attribute group, and any lookup-table JOINs needed to resolve UUID foreign keys to display values) — everything you need to write SQL with run_sql. entityType must match a name exactly as shown in get_schema (e.g. "Loan").

get_schema

ChatGPT

Get the organization's data model as a compact tree: entity types, their tables, and how they relate (1:N / N:M join keys), plus the document-type catalog. Call this FIRST, once. It is the map — it does NOT list columns. For an entity type's columns/attributes, call get_entity_attributes({ entityType }). Use the relationships and join keys shown here to plan JOINs before writing SQL with run_sql.

get_schema

ChatGPT

Get the organization's data model as a compact tree: entity types, their tables, and how they relate (1:N / N:M join keys), plus the document-type catalog. Call this FIRST, once. It is the map — it does NOT list columns. For an entity type's columns/attributes, call get_entity_attributes({ entityType }). Use the relationships and join keys shown here to plan JOINs before writing SQL with run_sql.

run_sql

ChatGPT

Execute a read-only SQL SELECT query against the organization's structured data. MANDATORY: Call get_schema({}) FIRST to learn tables + relationships, then get_entity_attributes({ entityType }) for a table's columns. Never guess table or column names. Rules: - PostgreSQL SELECT only (no INSERT/UPDATE/DELETE). - No schema prefixes — search_path is pre-configured (exception: reference tables use the schema-qualified names shown in get_schema). - Auto-LIMIT 500 is added if you omit it (aggregations don't need a LIMIT). - Use full table names, not aliases. - JOIN parent → child on the keys shown in get_schema: 1:N via the child's FK column; N:M via the junction table. For UUID foreign keys, LEFT JOIN the lookup table to show display values, not raw UUIDs. - Escape single quotes by doubling them (O''Brien). Returns rows as JSON objects for code and a markdown table for the conversation. Full docs: https://app.hypha.co/docs/mcp

run_sql

ChatGPT

Execute a read-only SQL SELECT query against the organization's structured data. MANDATORY: Call get_schema({}) FIRST to learn tables + relationships, then get_entity_attributes({ entityType }) for a table's columns. Never guess table or column names. Rules: - PostgreSQL SELECT only (no INSERT/UPDATE/DELETE). - No schema prefixes — search_path is pre-configured (exception: reference tables use the schema-qualified names shown in get_schema). - Auto-LIMIT 500 is added if you omit it (aggregations don't need a LIMIT). - Use full table names, not aliases. - JOIN parent → child on the keys shown in get_schema: 1:N via the child's FK column; N:M via the junction table. For UUID foreign keys, LEFT JOIN the lookup table to show display values, not raw UUIDs. - Escape single quotes by doubling them (O''Brien). Returns rows as JSON objects for code and a markdown table for the conversation. Full docs: https://app.hypha.co/docs/mcp

Hypha

Overview

Tools

get_entity_attributes

get_entity_attributes

get_schema

get_schema

run_sql

run_sql

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