Skip to main content
Glama
capsolver-ai

CapSolver MCP Server

Official
by capsolver-ai

get_supported_captchas

List all CAPTCHA types and handler names available for solving through this CapSolver instance.

Instructions

List all captcha types supported by this CapSolver instance.

Returns the registered handler names and all available captcha type values. No parameters required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

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 behavioral disclosure burden. It clearly states the tool returns registered handler names and all available captcha type values, and the read-only nature is evident from 'List'. It does not mention authentication or error behavior, but for a zero-parameter discovery endpoint this is acceptable.

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 three short sentences with no filler. It front-loads the purpose, then states the return content and parameter expectation. Every sentence earns its place.

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 listing tool with an output schema present, the description covers purpose, scope, return content, and call shape. It could be slightly stronger by mentioning when to use this in relation to the sibling tools, but nothing essential for correct invocation is missing.

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 input schema has no properties, and the description explicitly reinforces this with 'No parameters required.' With zero parameters, the baseline is 4, and the explicit statement adds a small usability benefit beyond the empty schema.

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 opens with a specific verb and resource: 'List all captcha types supported by this CapSolver instance.' It is immediately clear what the tool does and is easily distinguished from siblings like solve_captcha and detect_captchas, which perform actions rather than discovery.

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

Usage Guidelines3/5

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

The usage is implied by the purpose: if an agent needs to know which captcha types are supported, this is the tool. However, the description does not explicitly state when to use it over siblings or provide any workflow guidance, such as checking supported types before calling solve_captcha.

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