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list_proxies

Read-onlyIdempotent

List the account's proxy services of every type — Residential Basic/Premium/Private, Mobile, Mobile V2, Datacenter (static or traffic-based), ISP, IPv6 — with plan type, bandwidth left, expiry, whitelisted IPs and the orderId to pass to generate_proxies. Call this first to see which proxy plans are available.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax services returned (default 50)
activeNotrue: only non-expired services (recommended). false: only expired. Omit for all.
offsetNoPagination offset (default 0)
planTypeNoOnly services of this plan type

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is covered. The description adds useful behavioral context by specifying the breadth of the list and the key output fields, including the orderId needed downstream. It does not cover pagination behavior, but the schema documents the relevant parameters.

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?

Two sentences with no filler. The core action and scope are front-loaded, followed by the useful downstream pointer. Every clause earns its place.

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?

For a read-only listing tool with no output schema, the description compensates well by naming the returned fields, enumerating proxy types, and explaining why an agent should call it first. Combined with the fully documented optional parameters and safe annotations, nothing essential is missing.

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%, with all four parameters already clearly explained and the planType enum fully listed. The description adds no additional parameter-level meaning beyond contextualizing the orderId in the output, so the baseline score of 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 uses a specific verb ('List') with a precise resource ('the account's proxy services'), enumerates all covered types, and lists the returned fields. It clearly differentiates itself from siblings like generate_proxies by explicitly naming that tool as the follow-up consumer of the returned orderId.

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 gives clear context with 'Call this first to see which proxy plans are available' and ties directly to generate_proxies. It does not mention exclusions or alternative tools for proxy locations, but the intended sequencing is explicit enough for an agent.

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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TDQS

A4.1/5.0
Disambiguation5/5

Each tool targets a distinct resource or action: single scrape, batch scrape, crawl, search, dataset creation, parser lifecycle, proxy management, and SEO audit. Even the five status pollers are clearly differentiated by job type and their descriptions explicitly state which job they poll, so an agent can reliably select the right tool.

Naming Consistency4/5

Most names follow a verb-first pattern (create_dataset, generate_parser, run_collector, save_parser_preset, whitelist_ip) and listing tools consistently use the 'list_' prefix. However, a few are noun-first (parser_preset_stats, proxy_locations, collector_run_status) and the status polling tool for collectors breaks the otherwise consistent '<job>_status' convention ('collector_run_status' instead of 'run_collector_status').

Tool Count3/5

At 25 tools, the set is at the upper edge of the 'heavy' range. The tools all serve distinct functions, reflecting a broad platform covering scraping, crawling, search, datasets, parsers, proxies, and SEO, but the count borders on overwhelming for an agent, and some consolidation (e.g., a generic async job status endpoint) could reduce the surface.

Completeness4/5

The tool surface covers the core data-extraction lifecycle well: discovery (map, search), acquisition (scrape, batch, crawl), structured extraction (generate_parser, save_parser_preset, parser stats/heal), proxy management, and result aggregation (datasets, collectors). Notable gaps are the absence of any cancellation/abort mechanism for long-running async jobs and no way to delete a parser preset, but these are minor for most workflows.