Skip to main content
Glama
joaovaleri

linkedin-mcp

by joaovaleri

linkedin_search_companies

Find LinkedIn companies by specifying keywords; returns matching business profiles.

Instructions

Search LinkedIn for companies by keywords

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordsYesSearch keywords (e.g. 'fintech startups Brazil')
Behavior2/5

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

No annotations are provided, so the description must carry the disclosure burden. It only states the basic action without revealing behavioral traits like whether results are paginated, rate limits, or authentication requirements. It does not even explicitly state that it is a read-only operation.

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?

The description is a single sentence with no wasted words, but it is too minimal to fully inform the agent. It is efficient but sacrifices completeness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and no annotations, the description should provide more context about what the search returns (e.g., list of company names/IDs) or any constraints. It falls short for a search tool that an agent may need to invoke correctly.

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?

The schema covers the single parameter 'keywords' with a helpful example, and the description adds no additional semantics beyond what the schema already provides. With 100% schema description coverage, baseline 3 is appropriate.

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 clearly states the tool searches LinkedIn for companies by keywords, using a specific verb ('search') and resource ('companies'), and it distinguishes from sibling tools like linkedin_search_people and linkedin_search_jobs.

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 description implies usage when needing to find companies, but does not provide explicit when-to-use vs. when-not-to-use or mention 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.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/joaovaleri/linkedin-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server