dbecho
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_databasesA | List all configured PostgreSQL databases with their descriptions. |
| healthA | Check connectivity and basic info for all configured databases. |
| schemaA | Get the full schema of a database: tables, columns, types, primary keys, row counts, and sizes. Args: database: Name of the database from config (use list_databases to see available). |
| queryA | Execute a read-only SQL query on a database and return results as a formatted table. Only SELECT, WITH, EXPLAIN, and SHOW queries are allowed. Args: database: Name of the database from config. sql: SQL query to execute (read-only). |
| analyzeB | Profile a table: row count, column types, null percentages, distinct values, min/max/avg for numeric columns, top values for low-cardinality text columns. Args: database: Name of the database from config. table: Name of the table to analyze. |
| compareA | Run the same SQL query across multiple databases and compare results side by side. Args: sql: SQL query to execute on each database (must be SELECT). databases: List of database names to compare. If omitted, runs on all databases. |
| summaryA | Get a quick overview of all databases: table counts, total rows, largest tables, database sizes. |
| trendA | Analyze time series data: group rows by time period and show counts, averages, and totals. Args: database: Name of the database from config. table: Name of the table. date_column: Name of the date/timestamp column to group by. value_column: Optional numeric column to aggregate (avg, sum). If omitted, shows counts only. period: Grouping period: day, week, month, quarter, year. Default: month. |
| anomaliesA | Find data quality issues in a table: high null rates, single-value columns, numeric outliers, future dates, possible duplicates. Args: database: Name of the database from config. table: Name of the table to check. |
| sampleA | Show sample rows from a table to understand the data format. Args: database: Name of the database from config. table: Name of the table. limit: Number of rows to return (default 5, max 50). |
| erdB | Show entity-relationship diagram as text: tables, primary keys, and foreign key relationships. Args: database: Name of the database from config. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| explore_database | Guided exploration of a database: schema, summary, sample data from key tables. |
| compare_databases | Compare all databases: find common tables, compare row counts and structures. |
| data_quality_report | Run a comprehensive data quality check on all tables in a database. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| resource_databases | List of all configured databases. |
TDQS
Scored across 11 tools
Each tool has a clearly distinct purpose: profiling (analyze) vs anomaly detection (anomalies) vs schema exploration (schema) vs time series (trend) etc. No two tools appear to do the same thing, and descriptions make boundaries clear.
All names use lowercase with underscores for multi-word terms, but the part-of-speech varies (verbs like analyze, query vs nouns like anomalies, schema). The pattern is mostly predictable, but lacks the strict verb_noun consistency seen in higher-scoring sets.
11 tools is squarely in the optimal range for a database analysis server. Each tool addresses a specific analytical need without redundancy, and the number feels complete without being overwhelming.
The tool surface covers all major database exploration tasks: listing, schema, profiling, sampling, querying, comparison, anomaly detection, time trends, and health checks. No obvious gaps for the stated purpose of database analysis.