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parajiholkar

Multi-Container Log Correlator MCP Server

by parajiholkar

List Active Containers

list_active_containers
Read-onlyIdempotent

List currently monitored Docker containers, optionally filtered by Compose project, and view service name, container ID, image, status, and project. Use this to map service topology before running log queries.

Instructions

List all currently running Docker containers being monitored.

Returns the container name, short ID, Docker image, status, and the Compose project it belongs to (if any).

Args: - project_name (string, optional): Filter by Docker Compose project name. Omit to list all.

Returns: A formatted list of containers with: serviceName, containerId (12-char), image, status, project.

Use this first to understand the service topology before issuing other queries.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_nameNoDocker Compose project name to filter by. return to list all containers.

Schema Changelog

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

  1. First observedv1.0.0

TDQS

A4.2/5.0
Behavior4/5

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

The readOnlyHint, idempotentHint, and destructiveHint annotations already cover safety, and the description adds useful behavioral scope: only monitored Docker containers, optional Compose-project filtering, and the exact return format. It also clarifies the 12-char container ID detail, which is 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.

Conciseness4/5

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

The description is compact and front-loaded, with the purpose stated first and usage guidance at the end. The Returns section partly duplicates the earlier prose listing fields, which costs a small amount of conciseness, but the added field-name mapping and 12-char detail justify most of the repetition.

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?

For a simple list tool with one optional parameter and no output schema, the description is complete: it specifies the return shape, the optional filter, the monitored-container scope, and the intended position in the workflow. An agent has enough information to call it correctly without further inference.

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 schema already provides 100% coverage for the single optional parameter, and the description only repeats the same filter behavior ('Filter by Docker Compose project name. Omit to list all.'). It adds no new semantic information beyond the schema, so the baseline 3 applies.

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 clearly states a specific action ('List all currently running Docker containers being monitored') and identifies the returned fields. This distinguishes it from the sibling tracing/logging tools, making its purpose unmistakable.

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 explicitly instructs to use this tool first to understand service topology before issuing other queries, which provides clear context. It does not name specific alternatives or exclusions, but the guidance is sufficient for the simple listing use case.

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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