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Surfmeter MCP Server

Official

surfmeter_search_anomalies

Read-onlyIdempotent

Find and aggregate anomaly episodes by submitting an Elasticsearch Query DSL body. Use .keyword fields for exact text matching.

Instructions

Search and aggregate anomaly episode documents with Elasticsearch Query DSL. Use .keyword for exact text fields.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesElasticsearch Query DSL object (preferred) or JSON string. Use .keyword for exact text matching.
fromNo
sizeNo
source_onlyNo
search_afterNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so safety is covered. The description adds that the operation can aggregate results via Elasticsearch Query DSL, which is useful, but it does not disclose pagination behavior, result shape, or other operational caveats.

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 short and front-loaded with the core purpose in the first sentence. The second sentence is a useful practical tip, though it partially duplicates the body parameter description in the schema. Overall, there is no wasteful filler.

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

Completeness2/5

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

With no output schema and five parameters, the description is too sparse. It does not explain how from, size, search_after, or source_only shape behavior, nor does it describe the return structure. An agent would need external Elasticsearch knowledge to use the tool confidently.

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

Parameters2/5

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

Only one of five parameters (body) has any description, and the tool description mostly repeats the schema's body description by mentioning .keyword. The from, size, source_only, and search_after parameters are left undocumented in both the schema and the description, and the low 20% coverage is not compensated.

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 names a specific verb ('Search and aggregate') and a distinct resource ('anomaly episode documents'), which clearly sets it apart from siblings like surfmeter_search_measurements and surfmeter_search_actions. An agent can identify when this tool is relevant without needing to inspect schemas.

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

Usage Guidelines3/5

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

The description implies this tool is for anomaly episode documents, and offers a concrete tip about using .keyword for exact text fields. However, it does not explicitly state when to prefer this tool over sibling search tools, nor does it mention any alternative or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.