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LinkedIn MCP Server (Salesbot)

search_web

Read-only

General-purpose Google search — returns organic results for any query. Unlike search_google_xray (LinkedIn-only), this searches the entire web. Useful for finding job postings on portals (jobs.cz, prace.cz, profesia.sk, indeed.com), company info, news, or any other web content. Results are NOT saved to contacts — use this for research and discovery. Capped at 4 calls per minute to protect the Serper/Google budget.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results (1-30, default 10)
queryYesGoogle search query. Use operators like site:jobs.cz, intitle:, OR, quotes for exact match, etc.
countryNoCountry code for localized results (e.g. 'cz', 'sk', 'de', 'us'). Default: 'cz'.
languageNoLanguage code (e.g. 'cs', 'sk', 'en', 'de'). Default: 'cs'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.8/5.0
Behavior5/5

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

Annotations cover the safety profile (readOnly=true, destructive=false, openWorld=true), and the description adds the crucial non-obvious trait: a rate cap of 4 calls per minute to protect the Serper/Google budget. It also discloses the side-effect boundary ('results are NOT saved to contacts'), which is not derivable from annotations.

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?

Four sentences with no filler, scoping and sibling differentiation front-loaded. Slightly long but each sentence carries distinct information (scope, use cases, side-effect boundary, rate limit).

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 read-only search tool with no output schema, the description covers scope, alternatives, side effects, and a hard rate limit. An agent has everything needed to call it correctly and to know when to call something else instead.

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?

Schema coverage is 100%, so baseline is 3; the description lifts above baseline by describing the query surface ('any query', operators like site:, intitle:, OR) and use cases like localized job portals. It doesn't restate the limit/country/language ranges, but the schema handles those.

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+resource (general-purpose Google web search returning organic results) and explicitly distinguishes itself from sibling search_google_xray (LinkedIn-only) versus 'entire web'. An agent can route between this and other search_* tools without opening schemas.

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?

Gives explicit use cases (job portals, company info, news), names the alternative (search_google_xray) and its narrow scope, and clarifies this is for research/discovery with results NOT saved to contacts. This is when-to-use plus when-not-to-use guidance.

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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