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ginkida

portainer-mcp

by ginkida

portainer_service_tasks

List tasks for a Docker service to reveal state, node, and error details, helping diagnose why replicas are not starting.

Instructions

List a service's tasks with state, node and error (docker service ps).

The first place to look when replicas are not coming up: a task's error carries the scheduler / container start failure ("no suitable node", "task: non-zero exit (1)", image pull errors, ...).

Args: service_id: Service ID or name limit: Max tasks to return, newest per slot first (default 50, max 500) endpoint_id: Target endpoint ID (uses default if omitted)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
service_idYes
endpoint_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv0.8.0

TDQS

A4.6/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses the read-only nature through 'List', explains what the task error contains with concrete examples, and describes limit behavior ('newest per slot first'). This adds meaningful behavioral context beyond the schema.

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 compact and front-loaded with the core purpose, followed by a high-value diagnostic note and concise parameter explanations. There is no filler; every sentence adds either selection guidance or invocation detail.

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?

The description is complete for a list operation with three parameters and an output schema. It covers what the tool returns, when to use it, how parameters behave, and diagnostic interpretation of the error field. The output schema handles return format details, so nothing essential is missing.

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

Parameters5/5

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

The schema has 0% description coverage, but the description's Args section fully compensates: service_id is 'Service ID or name', limit is 'Max tasks to return, newest per slot first (default 50, max 500)', and endpoint_id is 'Target endpoint ID (uses default if omitted)'. Every parameter receives semantic meaning beyond its schema type and title.

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?

The description opens with a specific verb and resource: 'List a service's tasks with state, node and error', which clearly identifies what the tool does. It also names the Docker equivalent (`docker service ps`) and is distinct from sibling tools like service logs, service inspect, or services list.

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

Usage Guidelines4/5

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

It provides explicit guidance on when to use the tool: 'The first place to look when replicas are not coming up', and explains that the task error carries scheduler/container start failures. It does not list exclusions or explicitly name alternatives, but the usage context is clear enough for an agent to route correctly.

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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