database-analytics-mcp
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": true
} |
| logging | {} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| extensions | {
"io.modelcontextprotocol/ui": {}
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| connect_dbB | Connect to an SQLite database file. |
| execute_queryC | Execute a SQL query on the connected database. |
| list_tablesA | List all tables in the connected database. |
| export_to_csvB | Execute a SQL query and export results to CSV file |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
Each tool has a clearly distinct role: connecting, executing queries, listing tables, and exporting results. Even though export_to_csv involves executing a query, its output destination (file) differentiates it from execute_query.
All tool names follow a consistent verb_noun pattern (connect_db, execute_query, list_tables, export_to_csv), making the set predictable and easy to understand.
Four tools is well-scoped for a focused SQLite analytics server, covering the essential operations without unnecessary bloat.
The set covers connection, querying, table listing, and export, which are core for analytics. A minor gap is lack of explicit schema inspection, but agents can work around this via SQL queries (e.g., PRAGMA table_info).