Skip to main content
Glama

catalog_search

Search cloud instance catalog by provider, vCPU, memory, price, or text query to match instance types with specs, pricing, and architecture for workload sizing and cost optimization.

Instructions

Search the cloud instance catalog by provider, specs, or text query.

Returns matching instance types with instance family, vCPU / memory / storage, hourly on-demand price, region availability, and architecture (x86 / arm). All filters combine with AND semantics.

When to use: Right-sizing workloads, finding the cheapest instance that meets a hardware bar, or discovering equivalents across families.

Behavior: Pure lookup from the bundled SQLite catalog — no LLM, no network. Prices reflect catalog snapshot date (see refresh CLI command to update).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
providerNoCloud provider slug to search within. Default 'aws'.aws
queryNoOptional free-text query matching instance family, generation, or purpose (e.g. 'memory-optimized', 'graviton', 'gpu').
vcpusNoOptional exact vCPU count filter. Returns instances matching this vCPU count.
memory_gbNoOptional exact memory-in-GB filter. Returns instances matching this memory size.
max_price_per_hourNoOptional maximum hourly on-demand price (USD). Returns only instances at or below this price. Useful for budget-constrained sizing.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

The description discloses that it is a pure lookup from a bundled SQLite catalog with no LLM or network calls, and that prices are from a catalog snapshot date. This fully describes the tool's behavior, especially since no annotations are provided.

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 (3 paragraphs) with clear headings for purpose, usage, and behavior. Every sentence provides essential information without redundancy.

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?

The description covers all aspects: search criteria, returned data, usage context, and behavioral notes. Given that an output schema exists (context signal), the description does not need to detail return values. It is complete for an effective tool invocation.

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 baseline is 3. The description adds value by stating that all filters combine with AND semantics, which is not explicit in the schema. This clarifies how multiple filters interact, earning a 4.

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 searches the cloud instance catalog by multiple criteria (provider, specs, text query) and lists the returned fields (instance family, vCPU, memory, storage, price, region, architecture). It distinguishes from siblings like compare_providers and estimate_cost by focusing on search and filtering.

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?

The 'When to use' section explicitly outlines three use cases: right-sizing workloads, finding cheapest instance meeting hardware requirements, and discovering equivalent instance families. This provides clear guidance on when to invoke this tool over alternatives.

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

Install Server

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/xmpuspus/cloudwright'

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