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mcp-opensearch

by bunnyiesart

opensearch_ppl

Execute PPL queries on OpenSearch to perform multi-step filtering, aggregation, and sorting in a single pipeline command.

Instructions

Execute a PPL (Piped Processing Language) query against OpenSearch.

Prefer over opensearch_search when you need multi-step pipeline operations (filter → stats → sort) in a single query. Not interchangeable with Lucene — different syntax. Returns 404 if the PPL plugin is not installed.

PPL syntax: source= | [| ...] Common commands: where — filter rows stats count() by — aggregate fields , — select columns sort - — order results (- = descending) head — limit rows

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesFull PPL query string.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description carries full burden. It discloses a critical failure mode (404 if PPL plugin not installed) and explains that it executes a query (implying read operation). However, it does not explicitly state whether the tool is read-only or if it can mutate data, which is a minor gap.

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 concise and well-structured: a one-line purpose, a usage guideline, syntax format, and a list of common commands. Every sentence adds value with no fluff.

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?

Given the single parameter with complete schema coverage and presence of an output schema, the description thoroughly covers syntax, common commands, alternative tool guidance, and a failure case. It is fully sufficient for correct agent invocation.

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

Parameters5/5

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

Only one parameter 'query' with 100% schema coverage. The description adds significant value by providing PPL syntax, common commands (where, stats, fields, sort, head) and their usage, far exceeding the schema's bare description.

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 executes a PPL query against OpenSearch, using a specific verb and resource. It distinguishes from sibling tool opensearch_search by noting PPL vs Lucene syntax, making the purpose 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 says to prefer over opensearch_search for multi-step pipeline operations, warns about non-interchangeability with Lucene, and mentions a specific failure condition (404 if plugin missing). Provides clear when-to-use and not-to-use guidance.

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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