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elastic-mcp

by csimi

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Run Elasticsearch queries using Query DSL to retrieve matching hits and aggregations from specified indices.

Instructions

Run an Elasticsearch search using Query DSL and return the matching hits and aggregations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
aggsNoAggregations object
fromNoOffset of the first hit to return
sizeNoNumber of hits to return (default 10)
sortNoSort specification (string, object, or array)
indexYesIndex name, comma-separated list, or pattern to search
queryNoQuery DSL query object, e.g. { "match": { "field": "value" } }
sourceNo_source filtering: boolean, field, or array of fields
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the read-only nature is known. The description adds that it returns 'matching hits and aggregations' and uses Query DSL, which provides useful behavioral context beyond annotations. It does not describe potential performance impacts or pagination.

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?

The description is a single, front-loaded sentence with no wasted words. It efficiently conveys the tool's core function and output.

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

Completeness3/5

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

Given the complexity (7 parameters, nested objects, no output schema), the description is minimal. It mentions 'matching hits and aggregations' but does not detail return format or complexity of queries, leaving gaps for an agent.

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?

Schema description coverage is 100%, so parameters are already well-documented. The description does not add further meaning to any parameters beyond the high-level purpose. Baseline 3 is appropriate.

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 states 'Run an Elasticsearch search using Query DSL and return the matching hits and aggregations.' This is a specific verb+resource (search on Elasticsearch) and clearly distinguishes from sibling tools like 'count' or 'get_document'.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives such as 'count' for simple counts or 'get_document' for single documents. No exclusions or context for appropriate usage are mentioned.

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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