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HenkDz

Self-Hosted Supabase MCP Server

get_database_stats

Retrieve database statistics including activity metrics and background writer data from pg_stat_database and pg_stat_bgwriter for monitoring self-hosted Supabase instances.

Instructions

Retrieves statistics about database activity and the background writer from pg_stat_database and pg_stat_bgwriter.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The execute handler function that runs SQL queries against pg_stat_database and pg_stat_bgwriter to fetch database activity statistics and background writer stats, processes the results, and returns them structured according to the output schema.
    execute: async (input: GetDbStatsInput, context: ToolContext) => {
        const client = context.selfhostedClient;
    
        // Combine queries for efficiency if possible, but RPC might handle separate calls better.
        // Using two separate calls for clarity.
    
        const getDbStatsSql = `
            SELECT
                datname,
                numbackends,
                xact_commit::text,
                xact_rollback::text,
                blks_read::text,
                blks_hit::text,
                tup_returned::text,
                tup_fetched::text,
                tup_inserted::text,
                tup_updated::text,
                tup_deleted::text,
                conflicts::text,
                temp_files::text,
                temp_bytes::text,
                deadlocks::text,
                checksum_failures::text,
                checksum_last_failure::text,
                blk_read_time,
                blk_write_time,
                stats_reset::text
            FROM pg_stat_database
        `;
    
        const getBgWriterStatsSql = `
            SELECT
                checkpoints_timed::text,
                checkpoints_req::text,
                checkpoint_write_time,
                checkpoint_sync_time,
                buffers_checkpoint::text,
                buffers_clean::text,
                maxwritten_clean::text,
                buffers_backend::text,
                buffers_backend_fsync::text,
                buffers_alloc::text,
                stats_reset::text
            FROM pg_stat_bgwriter
        `;
    
        // Execute both queries
        const [dbStatsResult, bgWriterStatsResult] = await Promise.all([
            executeSqlWithFallback(client, getDbStatsSql, true),
            executeSqlWithFallback(client, getBgWriterStatsSql, true),
        ]);
    
        // Use handleSqlResponse for each part; it throws on error.
        const dbStats = handleSqlResponse(dbStatsResult, GetDbStatsOutputSchema.shape.database_stats);
        const bgWriterStats = handleSqlResponse(bgWriterStatsResult, GetDbStatsOutputSchema.shape.bgwriter_stats);
    
        // Combine results into the final schema
        return {
            database_stats: dbStats,
            bgwriter_stats: bgWriterStats,
        };
    },
  • Zod output schema defining the structure for database_stats (array from pg_stat_database) and bgwriter_stats (array from pg_stat_bgwriter), handling string representations of bigints and timestamps.
    // Note: Types are often bigint from pg_stat, returned as string by JSON/RPC.
    // Casting to numeric/float in SQL or parsing carefully later might be needed for calculations.
    const GetDbStatsOutputSchema = z.object({
        database_stats: z.array(z.object({
            datname: z.string().nullable(),
            numbackends: z.number().nullable(),
            xact_commit: z.string().nullable(), // bigint as string
            xact_rollback: z.string().nullable(), // bigint as string
            blks_read: z.string().nullable(), // bigint as string
            blks_hit: z.string().nullable(), // bigint as string
            tup_returned: z.string().nullable(), // bigint as string
            tup_fetched: z.string().nullable(), // bigint as string
            tup_inserted: z.string().nullable(), // bigint as string
            tup_updated: z.string().nullable(), // bigint as string
            tup_deleted: z.string().nullable(), // bigint as string
            conflicts: z.string().nullable(), // bigint as string
            temp_files: z.string().nullable(), // bigint as string
            temp_bytes: z.string().nullable(), // bigint as string
            deadlocks: z.string().nullable(), // bigint as string
            checksum_failures: z.string().nullable(), // bigint as string
            checksum_last_failure: z.string().nullable(), // timestamp as string
            blk_read_time: z.number().nullable(), // double precision
            blk_write_time: z.number().nullable(), // double precision
            stats_reset: z.string().nullable(), // timestamp as string
        })).describe("Statistics per database from pg_stat_database"),
        bgwriter_stats: z.array(z.object({ // Usually a single row
            checkpoints_timed: z.string().nullable(),
            checkpoints_req: z.string().nullable(),
            checkpoint_write_time: z.number().nullable(),
            checkpoint_sync_time: z.number().nullable(),
            buffers_checkpoint: z.string().nullable(),
            buffers_clean: z.string().nullable(),
            maxwritten_clean: z.string().nullable(),
            buffers_backend: z.string().nullable(),
            buffers_backend_fsync: z.string().nullable(),
            buffers_alloc: z.string().nullable(),
            stats_reset: z.string().nullable(),
        })).describe("Statistics from the background writer process from pg_stat_bgwriter"),
    });
  • Zod input schema for get_database_stats tool, which takes no parameters.
    const GetDbStatsInputSchema = z.object({});
    type GetDbStatsInput = z.infer<typeof GetDbStatsInputSchema>;
  • src/index.ts:106-106 (registration)
    Registration of the getDatabaseStatsTool in the availableTools object, which is used to populate the MCP server's tool capabilities.
    [getDatabaseStatsTool.name]: getDatabaseStatsTool as AppTool,
  • src/index.ts:17-17 (registration)
    Import statement for getDatabaseStatsTool from its implementation file.
    import { getDatabaseStatsTool } from './tools/get_database_stats.js';
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves statistics, implying a read-only operation, but doesn't specify if it requires authentication, has rate limits, returns real-time or cached data, or any error conditions. For a tool with zero annotation coverage, this leaves key behavioral traits unclear, scoring a 2.

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 that directly states the tool's purpose and data sources. It's front-loaded with the core action ('Retrieves statistics') and avoids any unnecessary words, making it highly concise and well-structured, earning a 5.

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

Completeness3/5

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

Given the tool's complexity (simple read operation with no parameters), no annotations, and no output schema, the description is minimally complete. It explains what the tool does but lacks details on return values, behavioral traits, or usage context. For a tool with no structured support, it's adequate but has clear gaps, scoring a 3.

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, and schema description coverage is 100% (though empty). The description doesn't need to add parameter details, so it meets the baseline of 4 for tools with no parameters. It appropriately focuses on the tool's purpose without redundant parameter explanations.

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 tool's purpose: 'Retrieves statistics about database activity and the background writer' with specific sources (pg_stat_database and pg_stat_bgwriter). It distinguishes itself from siblings like get_database_connections (which focuses on connections) and list_tables (which lists tables), but doesn't explicitly contrast with all siblings. The verb 'retrieves' and resources 'statistics' are specific, earning a 4.

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. It doesn't mention prerequisites, context for usage, or compare with siblings like get_database_connections for connection stats or execute_sql for custom queries. Without any usage context, this is a significant gap, scoring a 2.

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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