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aksdrx

mcp-human-search

by aksdrx

human_search_sign_in

Open a headed browser window to solve a CAPTCHA or sign in to a search engine account, so cookies persist for future automated searches.

Instructions

Open a headed browser window on the machine running this MCP server, on the engine's own persistent profile, so the user can solve a CAPTCHA and/or sign in to their account (Google, Microsoft, Baidu, ...). The user types credentials into the engine page itself; this server never sees them. Cookies persist for all future searches. While the window is open, searches on that engine fail over to the others instantly. Requires a display on the server machine (SSH X forwarding counts); on a headless host, warm the profiles with the mcp-human-search warm CLI on a desktop instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
engineYesEngine whose profile opens in the headed window

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and delivers: credentials never reach the server, cookies persist across future searches, concurrent searches on that engine fail over to the others, and a display (or SSH X forwarding) is required. These side effects and prerequisites are exactly what an agent needs before invoking a headed-browser action.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the action and keeps every sentence load-bearing (purpose, credential safety, cookie persistence, failover, display requirement, headless fallback). It is somewhat long and reads as one dense block, but no sentence is filler.

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?

There is no output schema and no annotations, yet the description covers prerequisites, security posture, persistence, and concurrency behavior. An agent has everything needed to decide whether invoking it is safe and appropriate.

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 coverage is 100% and the single `engine` parameter is enumerated and documented, so the schema does the heavy lifting. The description adds only that the window opens on that engine's persistent profile, which is marginal beyond what the schema already states.

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?

States a specific verb and resource: opening a headed browser window on the MCP server's own persistent profile so the user can solve a CAPTCHA or sign in. The CAPTCHA/credential purpose implicitly separates it from human_search and human_search_status, which cannot fill that role.

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?

Gives a clear trigger (user must solve a CAPTCHA or sign in) and an explicit when-not with an alternative (on a headless host, use the `mcp-human-search warm` CLI on a desktop instead). It never names the sibling tools human_search or human_search_status, so routing between them is still left partly to inference.

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