grantr-code/orderli_mcp_server

3.2

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Orderli MCP Server is a Python-based backend designed for managing and analyzing PostgreSQL databases, particularly in the context of restaurant POS integrations and error diagnostics.

Tools

Functions exposed to the LLM to take actions

list_schemas

List all schemas in the database.

list_objects

List objects (tables, views, sequences, extensions) in a schema.

get_object_details

Show detailed information about a database object (columns, constraints, indexes, etc).

explain_query

Explains the execution plan for a SQL query, with optional real execution and hypothetical indexes.

execute_sql

Execute any SQL query (restricted to read-only in restricted mode).

analyze_workload_indexes

Analyze frequently executed queries and recommend optimal indexes (DTA or LLM method).

analyze_query_indexes

Analyze a list of up to 10 SQL queries and recommend optimal indexes.

analyze_db_health

Analyze database health (index, connection, vacuum, sequence, replication, buffer, constraint, all).

get_top_queries

Report the slowest or most resource-intensive queries using pg_stat_statements.

lookup_error_info

Lookup known Orderli database errors and solutions for a specific POS system (with optional keyword search).

get_restaurant_pos

Get the restaurant name and configured POS integration for a given restaurant id.

search_order_errors

Search recent order HTTP requests and order groups for a restaurant, with optional error text and time filters.

find_menu_pos_mismatches

Find menu/POS inconsistencies that may be causing errors (option requirement mismatches, etc).

search_by_error_text

Search for a specific error pattern across all restaurants and a wide date range.

analyze_order_error

Debug and analyze an order error by examining both the order and potential menu-POS mismatches.

search_common_pos_errors

Search recent order errors for a restaurant matching common POS error patterns (supports relative time).