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linkedin-agent-mcp AGENTS.md

linkedin-agent-mcp AGENTS.md is an instructions file for Codex, OpenCode from iushv/linkedin-agent-mcp. It costs 2,068 tokens per session, scanned A, original, Apache-2.0.

A repository instruction file for linkedin-agent-mcp, an MCP server related to LinkedIn data collection. It documents the project’s setup, architecture, development commands, testing, and release process.

In plain words
What is it for?
Use it when developing or operating the project: install dependencies, run the server or browser, lint and format Python code, type-check it, run tests, build containers, and prepare releases.
Why use it?
It gives contributors the project-specific commands and rules needed to work safely and consistently. It also explains how to run, check, package, and release the server.

Instructions file for CodexOpenCode

not rated 1 1mo ago A scan 2,068 tokens original Apache-2.0
View the source file iushv/linkedin-agent-mcp
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/iushv/linkedin-agent-mcp/agents-md
Clone the repo
git clone --depth 1 https://github.com/iushv/linkedin-agent-mcp

Made for: Codex, OpenCode.

Wrote 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.

agentmods badge for linkedin-agent-mcp AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/iushv/linkedin-agent-mcp/agents-md.svg)](https://agentmods.dev/instructions/iushv/linkedin-agent-mcp/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/iushv/linkedin-agent-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/iushv/linkedin-agent-mcp/agents-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 2,068 This file is loaded in full into every session.
When invoked 2,068 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.02068 $0.02068
Opus 5 $0.01034 $0.01034
Sonnet 5 $0.00414 $0.00414
Haiku 4.5 $0.00207 $0.00207

Measured 4d ago against content hash f8ddf51dbbae, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

linkedin-agent-mcp AGENTS.md scanned grade A with 0 findings 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 4d 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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

AGENTS.md · 178 lines

How it starts

The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Development Commands

Environment Setup:

  • Use uv for dependency management: uv sync (installs all dependencies)
  • Development dependencies: uv sync --group dev
  • Bump version: uv version --bump minor (or major, patch) - this is the only manual step for a release. The GitHub Actions release workflow (.github/workflows/release.yml) automatically handles: manifest.json/docker-compose.yml version updates, git tag, Docker build & push, DXT extension, GitHub release, and PyPI publish. After the workflow completes, manually file a PR in the MCP registry to update the version.
  • Install browser: uv run patchright install chromium
  • Run server locally: uv run -m linkedin_mcp_server --no-headless
  • Run via uvx (PyPI): uvx linkedin-scraper-mcp
  • Run in Docker: docker run -it --rm -v ~/.linkedin-mcp:/home/pwuser/.linkedin-mcp iushv/linkedin-agent-mcp:latest

Code Quality:

  • 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 hooks: uv run pre-commit install then uv run pre-commit run --all-files

Docker Commands:

  • Build: docker build -t linkedin-agent-mcp .
  • Login: Use uvx locally first: uvx linkedin-scraper-mcp --login

Architecture Overview

This is a LinkedIn MCP (Model Context Protocol) Server that enables AI assistants to interact with LinkedIn through web scraping. The codebase follows a two-phase startup pattern:

  1. Authentication Phase (authentication.py) - Validates LinkedIn browser profile exists
  2. Server Runtime Phase (server.py) - Runs FastMCP server with tool registration

Core Components:

  • cli_main.py - Entry point with CLI argument parsing and orchestration
  • server.py - FastMCP server setup and tool registration
  • tools/ - LinkedIn scraping tools (person, company, job profiles)
  • drivers/browser.py - Patchright browser management with persistent profile (singleton)
  • core/ - Inlined browser, auth, and utility code (replaces linkedin_scraper dependency)
  • scraping/ - innerText extraction engine with Flag-based section selection
  • config/ - Configuration management (schema, loaders)
  • authentication.py - LinkedIn profile-based authentication

Read the full file on GitHub · 178 lines

Changes

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.

  1. 4d ago First seen · 178 lines · 2,068 tokens per session scan A f8ddf51dbbae

Subscribe to this mod's changes

linkedin-agent-mcp AGENTS.md is an instructions file published in the GitHub repository iushv/linkedin-agent-mcp (1 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 2,068 tokens to every session, about $0.0103 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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