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I now speak Model Context Protocol (MCP) — which means you can plug me directly into the AI tools your team already uses. Ask me about cloud risks, findings, and security posture right from your editor or AI assistant, without ever switching tabs.

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What you’ll need

Before connecting an AI client, grab two things:
1

A Plerion API token

Head to Settings → API Keys in the Plerion dashboard and create a new API key.Your token will look like: plerion_tak_...
Treat your API key like a password. Don’t commit it to source control or share it in chat.
2

Your MCP endpoint URL

My MCP server runs at:
https://{region}.api.plerion.com/pleri/mcp
Replace {region} with your account region — typically au, us, or eu. If you’re not sure, check the URL you use to access the Plerion dashboard.

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Connect your AI client

Claude Code supports remote HTTP MCP servers natively. The quickest way is the CLI:
claude mcp add --transport http pleri \
  https://{region}.api.plerion.com/pleri/mcp \
  --header "Authorization: Bearer plerion_tak_your_key_here"
Or add it manually to your project’s .mcp.json file (create it in your repo root if it doesn’t exist):
{
  "mcpServers": {
    "pleri": {
      "type": "http",
      "url": "https://{region}.api.plerion.com/pleri/mcp",
      "headers": {
        "Authorization": "Bearer plerion_tak_your_key_here"
      }
    }
  }
}
To add it globally (available in all projects), use ~/.claude.json with the same structure under mcpServers.
Run claude mcp list to confirm Pleri is connected, and claude mcp get pleri to inspect the config.

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What you can ask me

Once connected, just talk to me naturally in your AI client. Here are some things I can help with:
  • “What are our top cloud security risks right now?”
    I’ll pull live findings from your Plerion environment and explain what needs attention most.
  • “Are there any critical findings in our AWS account?”
    I’ll surface high-severity issues, explain the risk, and suggest next steps.
  • “Show me recent security posture changes.”
    I’ll summarise what’s improved, what’s new, and what the team should look at.
  • “Help me write a fix for this misconfigured S3 bucket.”
    I’ll combine context from your cloud environment with the code in your editor.
  • “What compliance gaps do we have for SOC 2?”
    I’ll map current findings to your compliance framework and flag what’s missing.
For the richest experience — where I can take action, file tickets, and work autonomously — use me via Slack or the Chrome extension. MCP is perfect for bringing my cloud security context right into your AI workflow.