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mcp-server-malcolm

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Python
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Ping Malcolm API

malcolm_ping
Read-only

Check whether the Malcolm API is reachable and credentials authenticate by calling GET /mapi/ping; returns pong or an error.

Instructions

Quick liveness check that the Malcolm API answers (GET /mapi/ping).

    Use this as the cheapest reachability probe. For readiness of the individual
    services behind the API use malcolm_service_status; for the OpenSearch cluster
    status specifically use cluster_health. Returns the raw /mapi/ping response
    ({"ping": "pong"}); an unreachable API is reported as an error, not as an
    answer.

    A pass proves exactly two things: the HTTP endpoint answers, and the
    configured credentials authenticate — a wrong password comes back as an
    upstream 401, not as a pass. It proves nothing
    about OpenSearch, the capture pipeline or any optional subsystem.

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.3.0
  2. Removedv0.2.0
  3. First observedv0.1.0

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint/destructiveHint already cover safety), the description discloses auth behavior — a wrong password surfaces as an upstream 401 rather than a pass — and that an unreachable API is reported as an error, not as a result. It also bounds the blast radius of a pass by naming what it proves nothing about (OpenSearch, capture pipeline, optional subsystems).

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?

Front-loads the core purpose and immediately follows with alternative routing and the meaning of a pass. It is slightly verbose with parenthetical asides, but each sentence carries distinct information.

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 annotations covering the safety profile, the description supplies the remaining decision-relevant context: exact endpoint, auth semantics, error behavior, and sibling routing. Nothing an agent needs to call it correctly is missing.

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 takes zero parameters, so there is nothing to document and the baseline is 4. The description adds no param detail because none is needed.

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 and resource (liveness check of the Malcolm API) and pins it to the exact endpoint GET /mapi/ping. It explicitly distinguishes itself from the two closest siblings (malcolm_service_status for per-service readiness, cluster_health for OpenSearch), so an agent can route without opening a schema.

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?

Gives explicit when-to-use ('cheapest reachability probe') plus when-not-to-use, naming both alternatives and the condition that selects each. The scope of what a pass proves and does not prove is stated directly, leaving nothing to inference.

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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