Skip to main content
Glama

search_docs

Search Apache Iggy's guides and Rust API docs for any term to find current, accurate answers. Choose website, Rust API, or both sources, and control result count for targeted lookup.

Instructions

Search the Apache Iggy documentation for a term or phrase.

Searches both halves of the corpus: the hand-written guides on iggy.apache.org and the inline Rust doc comments from apache/iggy, whose results link to docs.rs. Each result says which half it came from, because the guides say how Iggy is meant to be used and the Rust API says what is actually callable, and those can disagree. Set source to 'website' or 'rust-api' to search one half alone.

Prefer this over answering Iggy questions from memory: the SDKs and server move quickly and the docs are the current truth.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
sourceNoall
max_resultsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It openly explains that results are labeled by source, notes that guides and Rust API docs may disagree, and describes the effect of the 'source' parameter. This goes beyond a simple 'search' statement and gives useful behavioral expectations, though it stops short of describing output format or error behavior.

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 well-structured and front-loaded with the core action. Each subsequent sentence adds valuable context: the two-corpus behavior, source filtering, and the strong recommendation to use this tool over memory. Nothing is redundant or wasted.

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 the tool's moderate complexity and the existence of an output schema, the description is quite complete. It explains what the tool does, how to narrow the search, and why it matters. The only minor gap is the lack of mention of 'max_results' or result ordering, but the output schema likely covers result structure, so this is a minor shortfall.

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 0%, so the description must compensate. It explicitly explains the 'source' parameter and implicitly covers 'query' via 'search for a term or phrase', but it gives no explanation for 'max_results'. Since only two of the three parameters are addressed, the compensation is partial, warranting a middle score.

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 a specific verb and resource ('Search the Apache Iggy documentation') and clearly distinguishes its scope (searches both hand-written guides and Rust doc comments) from sibling tools like list_docs and get_doc. An agent can immediately understand what this tool does and what makes it unique.

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?

The description provides clear usage context: it explicitly tells the agent to prefer searching docs over answering from memory, and explains when to use the 'source' parameter to narrow the search. However, it does not explicitly compare against sibling tools or state when not to use them, though this is implicitly clear from their names.

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

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/justinmclean/IggyDocMCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server