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jperelli

Graylog MCP Server

by jperelli

list_fields

List actual message fields in the index to avoid guessing field names that may not exist. Use the contains filter to narrow down fields before running searches.

Instructions

List the message fields that actually exist in the index. Use this BEFORE searching on a field you have not seen in a result, so you never guess a field name — a query on a nonexistent field returns 0 matches, which is indistinguishable from 'no logs'. Clusters index thousands of fields, so pass contains to narrow (e.g. "namespace").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax field names to return. Default: 100.
containsNoCase-insensitive substring filter on the field name, e.g. "namespace", "pod", "level".
instanceNoGraylog instance to query. Active: "instance_1". Default: "instance_1".
Behavior4/5

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

With no annotations, the description discloses key behavioral traits: it lists only fields that actually exist in the index, and warns about the misleading '0 matches' outcome. It also hints at the scale (thousands of fields). This is strong contextual disclosure, though it does not mention whether it is read-only or describe pagination, which would be nice.

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?

Four sentences, each serving a distinct purpose: stating the action, advising when to use, explaining the risk, and giving a usage suggestion. No fluff or redundancy. Well-structured with the primary action first.

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?

Given no output schema and no annotations, the description provides sufficient context for an agent to decide when and how to invoke the tool. It covers the core use case, a critical pitfall, and parameter guidance. A small gap is the lack of detail about the return format or default behavior, but overall it is complete enough.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds meaningful context for 'contains' by explaining its purpose and giving an example. It also reinforces the rationale for using limit. This goes beyond just restating schema definitions.

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 the tool lists actual indexed fields, which is distinct from sibling tools like search or analyze. It immediately identifies the resource (message fields) and the action (list), making it unambiguous.

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?

Explicitly instructs to use before searching on unseen fields, explains the failure mode (0 matches indistinguishable from no logs), and advises using the contains parameter to narrow results. This provides clear when-to-use guidance versus search tools.

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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