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system_events

Read-only

Stream real-time Docker events with filters, returning when a limit or timeout is reached. Wait for a specific event instead of polling.

Instructions

Stream real-time events from the Docker server, bounded by limit events or timeout_seconds.

Returns when limit events are collected or timeout_seconds elapses, whichever comes first (limit caps memory; timeout_seconds caps how long the call blocks - without it a quiet daemon would block indefinitely, since the stream only yields on an actual event).

Caveat for ssh:// daemons: docker-py can't cancel an SSH stream, so the timeout_seconds watchdog can't interrupt a fully idle stream - bound with until/limit (or a non-SSH endpoint).

"Wait for the next matching event" idiom: pass limit=1 with filters narrowed to what you care about (e.g. {"type": "container", "event": "health_status"}) and a generous timeout_seconds. This blocks until that one event arrives (or the timeout elapses, returning an empty list) instead of re-polling a snapshot on a timer - there's no separate wait tool for this since the filtering this call already does covers it.

Args: since: Show events created since this timestamp until: Show events created until this timestamp filters: Filters to apply to the event stream limit: Max events to return timeout_seconds: Max wall-clock seconds before returning what was collected

Returns: list: A list of decoded event dicts (length <= limit)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
sinceNo
untilNo
filtersNo
timeout_secondsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.0.0

TDQS

A4.9/5.0
Behavior5/5

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

Annotations only declare readOnlyHint and destructiveHint, but the description adds substantial behavioral detail: it blocks until limit or timeout, returns what was collected, can block indefinitely without timeout, and documents the SSH cancellation limitation. This is exactly the kind of operational nuance that helps an agent avoid misuse.

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?

Although longer than most descriptions, every sentence adds unique operational value: bounding behavior, SSH caveat, wait idiom, and parameter descriptions. The structure is front-loaded with core behavior and ends with a compact Args/Returns section, with no filler.

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

Completeness4/5

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

The description covers return shape, edge cases, blocking behavior, and the SSH caveat, which is strong for a stream tool with no output schema. The only minor gap is that timestamp formats for since/until and the exact filter schema are not specified, but the provided example and defaults make invocation practical.

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?

With 0% schema description coverage, the description carries full responsibility for parameter meaning, and it succeeds. Each parameter gets a concise one-line explanation, and filters are illustrated with a concrete example to show how to wait for a specific event.

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: 'Stream real-time events from the Docker server', immediately distinguishing it from snapshot-style siblings like system_info and system_version. It also clarifies the bounded nature of the stream, leaving no doubt about what the tool does.

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

Usage Guidelines5/5

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

The description explicitly explains when to use this tool, including a 'wait for next matching event' idiom with limit and filters, and states that no separate wait tool exists because filtering already covers it. It also gives a concrete caveat for ssh:// daemons and recommends bound parameters, which is strong usage guidance.

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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