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quanticdata-mcp

by io.github.quantumproxies

whitelist_ip

Destructive

Manage IP-auth whitelisting on a proxy service (Residential Basic, Datacenter, ISP, IPv6, Mobile): add or remove an IP, or list the current entries. A whitelisted machine uses the proxies without username/password — required for the Mobile V2 IP-auth proxy list. Residential Premium/Private use user:pass auth and don't need this.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ipNoThe IP to add/remove (required for add and remove)
ispNoMobile add: ISP code, e.g. 'tmobile'
ttlNoMobile add: sticky session TTL in seconds
cityNoMobile add: city slug
actionYesWhat to do with the order's whitelist
regionNoMobile add: region slug
stickyNoMobile add: keep the same IP per port
countryNoMobile add: geo targeting for the ports, e.g. 'us'
orderIdYesThe proxy service's orderId (from list_proxies)
protocolNoMobile add: protocol for the allocated ports
ports_countNoMobile add: number of ports to allocate

Schema Changelog

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

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true. The description adds context that whitelisted machines use proxies without credentials and that it's required for Mobile V2 IP-auth list, which clarifies the impact. No contradiction with annotations.

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, front-loaded with the purpose, then the auth context. No unnecessary words.

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?

The description gives enough high-level context: what the tool does, when to use it, and which auth methods it applies to. The schema covers parameter details. It lacks explicit prerequisites like needing an existing order, but this is implied by orderId from list_proxies.

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 covers 100% of parameters with descriptions, so the description adds little beyond the schema. It provides context about the auth method that relates to orderId, but no new parameter-specific details.

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 clear verb (manage) and resource (IP-auth whitelisting) and specifies the actions (add, remove, list). It distinguishes from sibling proxy tools by focusing on whitelisting specifically.

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?

Provides explicit guidance on when to use (for IP-auth proxy types, required for Mobile V2) and when not (Residential Premium/Private with user:pass auth). This gives agents a clear decision rule.

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

All quanticdata-mcp toolsInspect
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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.

Resources