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CaptchaAI MCP Server

CaptchaAI MCP Server

Official
by CaptchaAI
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Get Threads

get_threads
Read-only

Retrieves CaptchaAI thread usage, including total, active working, and free thread counts, so you can inspect current account capacity before submitting CAPTCHA tasks.

Instructions

Get CaptchaAI thread usage: total threads, active working_threads, and free_threads.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_threads"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds only the names of the returned metrics, which are also available in the output schema; it says nothing about latency, caching, live vs. quota-window semantics, or whether thread counts change dynamically.

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?

A single front-loaded sentence with the resource first and the returned fields appended. Every word earns its place; nothing is padded.

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?

For a zero-parameter read tool with an output schema, the description covers purpose and returned fields adequately; safety is carried by annotations. The only real gap is the absence of any hint about when an agent should consult it or how quickly thread counts change.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline of 4 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb and resource ('Get CaptchaAI thread usage') and enumerates the three metrics returned (total threads, active working_threads, free_threads), which clearly separates it from get_balance and get_supported_captchas. It stops short of explicitly contrasting itself with those siblings, so a 4 rather than a 5.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no stated prerequisites, and no mention of alternatives. The use case (checking capacity/availability before solving captchas) must be inferred entirely from the metric names.

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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