Skip to main content
Glama

Log in to LinkedIn

linkedin_login

Opens a real Chromium window to manually log in to LinkedIn, including 2FA, and saves the authenticated session locally for reuse without reading or storing your password.

Instructions

Open a real Chromium window and wait for you to log in manually (including 2FA / security checkpoints). The session is saved locally and reused; your password is never read or stored. Run once, or again if the session expires.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

The description adds substantial behavioral context beyond the readOnlyHint annotation: it opens a real browser, requires manual interaction, supports 2FA, saves the session locally, and never reads/stores passwords. These details help the agent set expectations and invoke safely.

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 concise (3 sentences) and front-loaded with the key behavior. Every sentence adds value: browser opening, manual login, session persistence, password handling, and rerun guidance. No filler.

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, no-output-schema tool, the description covers the essential semantics: what it does, how the session is stored, and when to rerun. It doesn't explicitly describe the return value or timeout behavior, but the interactive nature is well explained.

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 tool has zero parameters, so schema coverage is trivially 100% and the description correctly omits parameter details. Baseline for 0 params is 4, and the description doesn't need to add anything beyond what's already clear.

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 states a specific verb ('Open a real Chromium window and wait') and clear resource ('log in to LinkedIn'), and distinguishes from sibling content tools by describing the login process. It clearly explains what the tool accomplishes.

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?

The description provides context on when to use: 'Run once, or again if the session expires.' It implies usage before other tools that require authentication, but does not explicitly reference alternatives or exclusions. Still, the timing guidance is clear.

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/HDHNezherParking-cum-Y638-Intl-Ltd/linkedin-mcp'

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