linkedin-mcp-server is a local MCP server that gives compatible AI assistants access to LinkedIn through a logged-in browser session. Agents can use it to inspect profiles and companies, search jobs, retrieve job details, and manage certain LinkedIn interactions. The catalogue add-ons operate this server and expose its LinkedIn workflows to agents.
Borrowing it
Nothing to install: this file belongs to stickerdaniel/linkedin-mcp-server. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/stickerdaniel/linkedin-mcp-server/main/AGENTS.mdgit clone --depth 1 https://github.com/stickerdaniel/linkedin-mcp-serverWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/stickerdaniel/linkedin-mcp-server/agents-md)<a href="https://agentmods.dev/instructions/stickerdaniel/linkedin-mcp-server/agents-md"><img src="https://agentmods.dev/badge/instructions/stickerdaniel/linkedin-mcp-server/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/stickerdaniel/linkedin-mcp-server/agents-md"><img src="https://agentmods.dev/badge/instructions/stickerdaniel/linkedin-mcp-server/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.05881 | $0.05881 |
| Opus 5.5 | $0.02352 | $0.02352 |
| Sonnet 5.5 | $0.01176 | $0.01176 |
| Haiku 4.5 | $0.00588 | $0.00588 |
Grade A, and why
linkedin-mcp-server AGENTS.md scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -D /tmp/mcp-headers -X POST http://127.0.0.1:8000/mcp \ Copies of this mod
1 near-identical copy found in the catalogue:
- lubot-hunter-mcp-2026 AGENTS.md — 100% identical, 148 lines differ
How it starts
The opening of the file, as written. The whole thing — 362 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
- Before changing repository knowledge, invariant comments, or temporary migration artifacts, read the knowledge policy.
Development Commands
- Use
uvfor dependency management:uv sync(dev:uv sync --group dev) - Lint:
uv run ruff check .(auto-fix with--fix) - Format:
uv run ruff format . - Type check:
uv run ty check(using ty, not mypy) - Tests:
uv run pytest(with coverage:uv run pytest --cov) - Pre-commit:
uv run pre-commit installthenuv run pre-commit run --all-files - Run server locally:
uv run -m linkedin_mcp_server --no-headless - Run via uvx (PyPI/package verification only):
uvx mcp-server-linkedin - Docker build:
docker build -t linkedin-mcp-server . - Install browser:
uv run patchright install chromium
LinkedIn Page Rules
- Voyager / private API. Out of scope. Read the rendered page.
- One section = one navigation. Each entry in
PERSON_SECTIONS/COMPANY_SECTIONS(linkedin/fields.py) maps to exactly one page navigation. Never combine multiple URLs behind a single section. - Minimize DOM dependence. Prefer innerText and URL navigation over DOM selectors. When DOM access is unavoidable, use minimal generic selectors (
a[href*="/jobs/view/"]) — never class names tied to LinkedIn's layout. - Detection must be locale-independent. Classification logic — connection state, action availability, button identity — must rely on URL patterns (
/preload/custom-invite/?vanityName=USER,/in/USER/edit/intro/,/messaging/compose/), attribute presence (aria-labelexists,aria-expandedexists,aria-disabledexists), or structural counts — never on text values like "Connect", "Follow", "Message", "1st", "Pending". The verb in anaria-labelis locale-dependent; whether the attribute exists is not. Where text is genuinely the only signal, guard it behind an explicit per-locale table and document the limitation in code.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago Changed · +1 lines · +66 tokens per session 72702c4212e5
- 12d ago Changed · +5 lines · +47 tokens per session 506ada33edd4
- 13d ago Changed · +4 lines · +78 tokens per session 4a87a27b22ab
- 15d ago Changed · +5 tokens per session 343bbd52d7dd
- 16d ago Changed · +1 lines · +15 tokens per session 8beda7e3be18
- 19d ago Changed · +1 lines · -36 tokens per session 90a32e918aad
- 21d ago Changed · +1 lines · +68 tokens per session 89b6123a00be
- 24d ago Changed · +3 tokens per session beabd4e8c247
- 25d ago Changed · +2 lines · +54 tokens per session 3c315583dd19
- 27d ago First seen · 347 lines · 5,581 tokens per session scan A eb99ab15d1d7
linkedin-mcp-server AGENTS.md is an instructions file published in the GitHub repository stickerdaniel/linkedin-mcp-server (4,014 stars, last pushed yesterday), licensed Apache-2.0. It adds 5,881 tokens to every session, about $0.0235 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
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