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.
git clone --depth 1 https://github.com/Kubis010/linkedin-mcp-server-salesbotWrote 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/plugins/kubis010/linkedin-mcp-server-salesbot/linkedin-mcp-server-salesbot)<a href="https://agentmods.dev/plugins/kubis010/linkedin-mcp-server-salesbot/linkedin-mcp-server-salesbot"><img src="https://agentmods.dev/badge/plugins/kubis010/linkedin-mcp-server-salesbot/linkedin-mcp-server-salesbot/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/plugins/kubis010/linkedin-mcp-server-salesbot/linkedin-mcp-server-salesbot"><img src="https://agentmods.dev/badge/plugins/kubis010/linkedin-mcp-server-salesbot/linkedin-mcp-server-salesbot.svg" alt="Reviewed on agentmods" width="80" height="20"></a>Grade A, and why
salesbot 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 7d 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.
What it actually says
{
"name": "salesbot",
"displayName": "Salesbot – LinkedIn Outreach & CRM",
"version": "2.1.0",
"description": "LinkedIn outreach, campaigns and a sales CRM for Claude, with human or AI approval and server-side safety limits.",
"author": {
"name": "Salesbot",
"url": "https://salesbot.cz"
},
"homepage": "https://salesbot.cz/en/mcp-server",
"repository": "https://github.com/Kubis010/linkedin-mcp-server-salesbot",
"license": "MIT",
"keywords": [
"linkedin",
"sales",
"outreach",
"crm",
"mcp",
"email"
],
"icon": "./logo.png",
"documentationUrl": "https://salesbot.cz/en/mcp-server",
"supportUrl": "https://github.com/Kubis010/linkedin-mcp-server-salesbot/issues",
"privacyPolicyUrl": "https://salesbot.cz/en/privacy",
"termsOfServiceUrl": "https://salesbot.cz/en/terms"
}
What it installs
The manifest is a name and a version. 3 skills, 2 MCP servers travel with it, and installing the plugin installs all of them — 155 tokens a session between them. Each is measured on its own page, and each can be installed alone.
What ships with it
1 file beside plugin.json in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 7d ago Changed 5549ff08ba66
- 12d ago First seen · 27 lines scan A 6ffd2336d076
salesbot is a plugin published in the GitHub repository Kubis010/linkedin-mcp-server-salesbot (1 stars, last pushed 8d ago), licensed MIT. Its token cost is not measured: this kind of file is read by the harness, not the model. 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 2026-10-04.
Other plugins, from other repositories
linkedin-mcp-server
Research LinkedIn through a local, browser-backed MCP server.
x-use
Browser-native X workflows via x-use MCP: research, inbox reads, reviewed outreach, campaigns, posts, and threads. Requires x-use-mcp (pip install x-use-mcp) and an authorized X account.
project-mem
Persistent project memory with automatic consolidation.
linkedctl
LinkedIn API toolkit — MCP server and workflow guidance for Claude Code.
striderlabs-opentable
Make restaurant reservations on OpenTable. Let AI agents search restaurants, check availability, and book tables.
humanizer
Rewrite AI-sounding text so it reads like the writer without changing what it says.