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HenkDz

Self-Hosted Supabase MCP Server

get_database_connections

Monitor active database connections in self-hosted Supabase to track usage and identify idle sessions for optimization.

Instructions

Retrieves information about active database connections from pg_stat_activity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The execute handler function that fetches active database connections by querying pg_stat_activity, using shared utilities for SQL execution and response handling.
    execute: async (input: GetDbConnectionsInput, context: ToolContext) => {
        const client = context.selfhostedClient;
    
        // Query pg_stat_activity
        // Note: Access to pg_stat_activity might require superuser or specific grants.
        const getConnectionsSql = `
            SELECT
                pid,
                datname,
                usename,
                application_name,
                client_addr::text, -- Cast inet to text
                backend_start::text, -- Cast timestamp to text
                state,
                query
            FROM
                pg_stat_activity
            WHERE
                backend_type = 'client backend' -- Exclude background workers, etc.
                -- Optionally filter out self?
                -- AND pid != pg_backend_pid()
            ORDER BY
                backend_start
        `;
    
        const result = await executeSqlWithFallback(client, getConnectionsSql, true);
    
        return handleSqlResponse(result, GetDbConnectionsOutputSchema);
    },
  • Zod schema defining the structure of the output: an array of database connection objects with fields like datname, usename, state, etc.
    const GetDbConnectionsOutputSchema = z.array(z.object({
        datname: z.string().nullable().describe('Database name'),
        usename: z.string().nullable().describe('User name'),
        application_name: z.string().nullable().describe('Application name (e.g., PostgREST, psql)'),
        client_addr: z.string().nullable().describe('Client IP address'),
        backend_start: z.string().nullable().describe('Time when the backend process started'),
        state: z.string().nullable().describe('Current connection state (e.g., active, idle)'),
        query: z.string().nullable().describe('Last or current query being executed'),
        pid: z.number().describe('Process ID of the backend'),
    }));
  • Zod input schema (empty object, no parameters required).
    const GetDbConnectionsInputSchema = z.object({});
    type GetDbConnectionsInput = z.infer<typeof GetDbConnectionsInputSchema>;
  • src/index.ts:16-16 (registration)
    Import of the getDatabaseConnectionsTool.
    import { getDatabaseConnectionsTool } from './tools/get_database_connections.js';
  • src/index.ts:105-105 (registration)
    Registration of the tool in the availableTools object used by the MCP server.
    [getDatabaseConnectionsTool.name]: getDatabaseConnectionsTool as AppTool,
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it retrieves information (implying read-only), but doesn't specify permissions needed, rate limits, or what 'active' means (e.g., time thresholds). This leaves significant gaps for a tool that accesses system-level data.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core purpose and includes the specific source ('pg_stat_activity'), making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of accessing database connections (a system-level operation) with no annotations and no output schema, the description is insufficient. It doesn't explain what information is returned (e.g., connection details, query states), security implications, or how to interpret results, leaving the agent under-informed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the input structure. The description doesn't need to add parameter details, and it correctly implies no inputs are required, earning a baseline high score for this context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('retrieves') and resource ('information about active database connections from pg_stat_activity'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_database_stats' or 'list_tables', which prevents a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'get_database_stats' or 'execute_sql'. It lacks context about use cases, prerequisites, or exclusions, leaving the agent to infer usage from the purpose alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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