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MCPg - Production-grade PostgreSQL MCP Server

List timescale jobs

list_timescale_jobs
Read-only

List TimescaleDB background jobs (retention / compression / refresh / reorder policies and user jobs) with schedule, next start, last run status and run/failure counts. Job ids below 1000 are TimescaleDB system jobs.

Instructions

List TimescaleDB background jobs (retention / compression / refresh / reorder policies and user jobs) with schedule, next start, last run status and run/failure counts. Job ids below 1000 are TimescaleDB system jobs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
databaseNoOptional: target a configured secondary (read-only) database by name; omit for the primary. Call list_databases to see the configured ids.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobsYes
availableYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.8.3

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds real behavioral context beyond that: which attributes are surfaced (schedule, next start, last run status, run/failure counts) and the id<1000 convention that lets an agent distinguish system jobs from user jobs in the output.

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?

Two sentences, both dense and front-loaded: the primary purpose and field list come first, and the id-threshold convention follows as a compact interpretive note. No filler or restatement of the title.

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

Completeness5/5

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

With an output schema present and 100% parameter description coverage, the description does not need to explain return shapes or argument syntax. It supplies exactly the extra semantics an agent needs (job categories and the system-job id convention) and nothing is missing for correct invocation.

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

Parameters3/5

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

The single optional 'database' parameter is fully documented in the schema (100% coverage), including the cross-reference to list_databases, so the schema does the work. The description adds nothing about the parameter, which is the expected baseline when coverage is this high.

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

Purpose5/5

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

States a specific verb (List) and a precisely-scoped resource (TimescaleDB background jobs), then enumerates the sub-kinds covered (retention/compression/refresh/reorder policies plus user jobs). This cleanly separates it from nearby siblings such as list_cron_jobs, list_autowarm_jobs, and list_hypertables without needing to open any schema.

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

Usage Guidelines3/5

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

The description implies usage by naming the job categories and telling the agent that ids below 1000 are system jobs, which helps interpret results. However, it never says when to choose this tool over the many other j observability/list tools, nor any prerequisite or exclusion. Usage is implied rather than stated.

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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