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Dcp MCP Server

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Saudi sovereign AI compute: OpenAI-compatible inference, rent GPU pods, manage storage.

About

Saudi sovereign AI compute: OpenAI-compatible inference, rent GPU pods, manage storage.

Security Report

6.2
Moderate6.2Moderate Risk

This is a well-designed MCP server for DCP's sovereign AI compute platform. Authentication is properly handled with environment variables, all tools appropriately require API keys except the bootstrap registration endpoint, and the codebase is clean with proper error handling. Minor concerns around input validation and logging practices are present but do not constitute security vulnerabilities. Supply chain analysis found 2 known vulnerabilities in dependencies (0 critical, 2 high severity).

3 files analyzed · 6 issues found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

env_vars

Check that this permission is expected for this type of plugin.

HTTP Network Access

Connects to external APIs or services over the internet.

What You'll Need

Set these up before or after installing:

renter API key (required for every tool except register_agent).Required

Environment variable: DCP_API_KEY

API host, default https://api.dcp.sa.Required

Environment variable: DCP_API_BASE

How to Install

Add this to your MCP configuration file:

{
  "mcpServers": {
    "io-github-dhnpmp-tech-dcp-mcp": {
      "env": {
        "DCP_API_KEY": "your-dcp-api-key-here",
        "DCP_API_BASE": "your-dcp-api-base-here"
      },
      "args": [
        "-y",
        "@dcp/mcp"
      ],
      "command": "npx"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

@dcp/mcp — DCP Model Context Protocol server

DCP is Saudi Arabia's sovereign AI compute platform — in-Kingdom inference, GPU rental, and persistent storage, billed in SAR, on Saudi-owned hardware. This MCP server lets any MCP-capable agent (Claude Desktop, Claude Code, Cursor, or your own) use DCP through native tool calls.

It is a thin client: it reads DCP_API_KEY from the environment and calls https://api.dcp.sa. No secrets are bundled.

Install (one line)

The connector runs straight from GitHub — no npm install, no clone:

DCP_API_KEY=dc1-sk-xxxxxxxx npx -y github:dhnpmp-tech/dcp-mcp

MCP client config

Add this to your MCP client (Claude Desktop claude_desktop_config.json, Claude Code / Cursor .mcp.json):

{
  "mcpServers": {
    "dcp": {
      "command": "npx",
      "args": ["-y", "github:dhnpmp-tech/dcp-mcp"],
      "env": { "DCP_API_KEY": "dc1-sk-xxxxxxxx" }
    }
  }
}

Then ask your agent to "list DCP models" or "rent a GPU on DCP for 30 minutes." Agents with no key can call register_agent first — see the quickstart below.

Tools

ToolWhat it does
register_agentSelf-register in one call — get a real API key + small SAR trial, no human, no email click. Use first when you have no key.
list_modelsList currently-serveable models (OpenAI-style).
chatRun a chat completion (OpenAI-compatible, in-Kingdom).
get_balanceRenter wallet balance (SAR).
list_gpusList rentable GPU types (e.g. H100, RTX 4090) with VRAM + live availability.
create_podRent a whole GPU as an interactive pod (root + Jupyter + SSH), prepaid per minute.
get_podPod status + access URL / SSH command / time remaining.
extend_podAdd time to a running pod, no restart.
stop_podStop early; unused prepaid time refunded.
rent_volumeRent an exclusive in-Kingdom persistent volume (10/20/30 GB).
get_volumeActive volume status + usage.

Zero-human quickstart (for agents)

The whole loop runs with no human in it:

  1. register_agent → returns a real api_key + a 20 SAR trial credit (no email click). Set it as DCP_API_KEY.
  2. list_gpus → pick a gpu_type string (e.g. "H100", "RTX 4090") from the live, available types.
  3. create_pod with that gpu_type + duration_minutes → poll get_pod for the access_url / ssh_command once running.
  4. chat → run OpenAI-compatible inference on an available model from list_models.
  5. stop_pod → stop early; unused prepaid minutes are refunded to the wallet.

Minting a key by hand (equivalent to register_agent):

curl -s -X POST https://api.dcp.sa/api/renters/agent-register \
  -H 'Content-Type: application/json' -d '{}'
# → { "api_key": "dcp-renter-…", "trial_credit_sar": 20, "balance_sar": 20, ... }

The trial (20 SAR) is enough to list GPUs, run a short pod, and do real inference; the larger grant stays behind email-verified signup. Calls are per-IP rate-limited.

Environment

  • DCP_API_KEY — renter API key (required for every tool except register_agent).
  • DCP_API_BASE — API host, default https://api.dcp.sa.

Why DCP

Inference, GPU rental, fine-tune hosting, and storage on Saudi-owned hardware inside the Kingdom — full PDPL / data-residency compliance, billed in SAR. The inference API is a drop-in OpenAI replacement: point any OpenAI SDK at https://api.dcp.sa/v1.

Learn more: https://dcp.sa/v2/agents · https://dcp.sa/llms.txt

MIT licensed.

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