Borrowing it
Nothing to install: this file belongs to gacabartosz/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/gacabartosz/linkedin-mcp-server/main/CLAUDE.mdgit clone --depth 1 https://github.com/gacabartosz/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/gacabartosz/linkedin-mcp-server/claude-md)<a href="https://agentmods.dev/instructions/gacabartosz/linkedin-mcp-server/claude-md"><img src="https://agentmods.dev/badge/instructions/gacabartosz/linkedin-mcp-server/claude-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/gacabartosz/linkedin-mcp-server/claude-md"><img src="https://agentmods.dev/badge/instructions/gacabartosz/linkedin-mcp-server/claude-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 | $0.01776 | $0.01776 |
| Opus 5 | $0.00888 | $0.00888 |
| Sonnet 5 | $0.00355 | $0.00355 |
| Haiku 4.5 | $0.00178 | $0.00178 |
Grade A, and why
linkedin-mcp-server CLAUDE.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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md — LinkedIn MCP Server
Build & Run
npm run build # TypeScript compile + shebang injection
npm run dev # Dev mode with tsx
npm start # Run compiled dist/index.js
Verify tools after changes:
echo '{"jsonrpc":"2.0","id":1,"method":"tools/list","params":{}}' | node dist/index.js
Architecture
src/index.ts— MCP server entry point, all 31 tool handlers (single switch statement)src/api/— LinkedIn REST API modules (client, auth, posts, comments, media, profile, reactions)src/scheduler/— SQLite-based post scheduler (store, daemon, publisher)src/content/— Content templates (12 built-in + custom), brand voice config, and guidelines loadersrc/gemini/— Google Gemini Imagen 4 image generationsrc/banner/— Banner generator (6 templates, 8 gradients, carousel PDF, screenshot capture)src/casestudy/— Case study PDF generator (branded PDFs with screenshots, metrics, Gemini covers)src/utils/— Config, logger, errors (toolResult/toolError helpers)guidelines/— LinkedIn algorithm strategy data (linkedin-strategy.json)scripts/generate-banner.mjs— Standalone banner generator CLIauto-engage.mjs— Intelligent auto-reply daemon (Gemini via MCP, socjotechnika, persona from second-mind)auto-publish.mjs— Auto-publish daemon (60s interval, comment queue, banner generation)
Code Conventions
- ESM only —
"type": "module"in package.json, use.jsextensions in imports - Strict TypeScript —
strict: true, target ES2022, NodeNext module resolution - Zod for input validation — schemas defined at top of index.ts, parsed with
.parse(args)in handlers - Tool responses — always return
toolResult(data)for success,toolError(message)for errors - Logging — use
log("info"|"warn"|"error", message, data?)fromsrc/utils/logger.ts - NEVER write to stdout — all logging goes to stderr (stdout is reserved for MCP stdio transport)
- Native
fetch()— no axios, no node-fetch; use Node 18+ built-in fetch - Minimal dependencies —
@modelcontextprotocol/sdk,better-sqlite3,zod,@anthropic-ai/sdk,pdf-lib
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.
- 9d ago First seen · 142 lines · 1,776 tokens per session scan A 874c4ab8bb6b
linkedin-mcp-server CLAUDE.md is an instructions file published in the GitHub repository gacabartosz/linkedin-mcp-server (5 stars, last pushed 20d ago), licensed MIT. It adds 1,776 tokens to every session, about $0.0089 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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