Unstuck

Web search

web_search

Read-onlyIdempotent

Search the web and get the top results (title, URL, snippet) as clean JSON. Live Google results, any country or city. Use when you need current information, sources, or links. Price: $0.01 per successful call; failed calls are free.

Input Schema

TableJSON Schema

Name	Required	Description
`num`	No	How many results, default 10, max 20.
`query`	Yes	What to search for.
`api_key`	No	Your Unstuck API key, if this connection has none. Leave empty to try free tools or to get a key and payment link.
`location`	No	Country or place to search from, e.g. "Houston, TX". Default "United States" (or the connection's default location).

Output Schema

TableJSON Schema

Name	Required	Description
`query`	Yes
`results`	Yes
`location`	Yes	Location searched from.
`balance_usd`	Yes	Remaining prepaid balance, USD.
`charged_usd`	Yes	Amount charged for this call, USD.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 4, 2026

addedInput schema / properties / api_key

Added value: +{
+  "description": "Your Unstuck API key, if this connection has none. Leave empty to try free tools or to get a key and payment link.",
+  "maxLength": 200,
+  "type": "string"
+}

AddedOct 4, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already declare read-only, open-world, idempotent, and non-destructive behavior. The description adds meaningful context beyond those: the output fields returned, that results are live Google results, and the pricing model ($0.01 per successful call, failed calls free). It does not cover auth requirements or rate limits, but the cost disclosure is valuable.

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?

Four short sentences, front-loaded with the core action and output, then scope, usage context, and cost. Every sentence carries distinct information and there is no waste.

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 straightforward web search tool with a full schema, rich annotations, and an output schema, the description covers purpose, output shape, scope, usage context, and cost. 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.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all four parameters. The description adds only marginal semantic detail ('any country or city' loosely maps to location), so the baseline of 3 is appropriate.

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 states a specific verb (Search), resource (the web), and output shape (title, URL, snippet as clean JSON), plus scope (live Google results, any country or city). It clearly distinguishes the tool from siblings like paper_search or read_page in practice, but does not explicitly name or contrast any sibling.

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?

It gives a clear when-to-use condition: 'Use when you need current information, sources, or links.' This is direct context for selecting the tool, but it offers no when-not-to-use guidance or explicit alternatives among the many sibling tools.

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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