Skip to main content
Glama

Particular Service Platform Documentation MCP Server

search_docs

Read-onlyIdempotent

Keyword search over Particular Platform documentation: every content word must appear on the matched pages. When a word matches nothing (an unfamiliar term or a typo more than one letter off), the search drops the least common words and retries until a subset matches, then reports the words it dropped. Start with 2-3 core topic words; add words only to narrow. Returns up to 10 ranked pages with their type, Markdown URL, and a short description. Pass a returned URL to read_doc to read the page as Markdown.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesContent words likely to appear on the target page, for example 'saga timeout' or 'SQS transport'. Full questions work too (stopwords and punctuation are ignored). A search with no matches retries with fewer words automatically; if that still finds nothing, try different core topic words.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, and the description adds substantial behavioral context beyond that: the all-words-must-match constraint, the word-dropping retry mechanism, the 10-result cap, and the exact return shape (type, Markdown URL, short description). The retry behavior is especially valuable because it changes how an agent should interpret sparse results.

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 five sentences and every one earns its place: purpose, retry behavior, query strategy, return format, and sibling routing. It is front-loaded with the core purpose. It is slightly dense in the middle (retry explanation could be tightened), but nothing is wasted.

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?

There is no output schema, so the description carries the burden of explaining return values — it does ('up to 10 ranked pages with their type, Markdown URL, and a short description'). Combined with annotations covering safety and the single fully-documented parameter, an agent has everything needed to invoke this tool correctly.

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, and the description adds value on top: it teaches query formulation strategy ('2-3 core topic words; add words only to narrow') and explains the success/failure semantics of the query in a way the schema's static description cannot. This pushes it above baseline.

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 — 'Keyword search over Particular Platform documentation' — and distinguishes itself from the only sibling, read_doc, by defining the division of labor: search returns URLs, read_doc consumes them. An agent can tell these two tools apart without opening either schema.

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

Usage Guidelines4/5

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

Provides concrete search strategy — 'Start with 2-3 core topic words; add words only to narrow' — and explains the automatic retry-with-fewer-words fallback so an agent knows what to do when results are empty. It names the alternative (read_doc) as the follow-up for returned URLs, though it doesn't state an explicit when-not-to-use exclusion for the search tool itself.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources