Dcp MCP

Name: Dcp MCP
Author: dhnpmp-tech

by dhnpmp-techversion 1.0.0i★ –i–

Registry nameio.github.dhnpmp-tech/dcp-mcp

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: –
Transport:
Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

The maker has not listed install details in the registry. See the maker’s README below.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account dhnpmp-tech, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 5666 servers in this category
Published to the registry more recently than 18% of the other 5666 servers in this category
Basic checks equal to or better than 100% of the other 5666 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Dcp MCP safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.0) reached the registry 5 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated yesterday

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Codebase Memory

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Runs on your computer★ 48,148MITUpdated 21 days ago

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Exa

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Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated 2 months ago

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

@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

Tool	What it does
`register_agent`	Self-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_models`	List currently-serveable models (OpenAI-style).
`chat`	Run a chat completion (OpenAI-compatible, in-Kingdom).
`get_balance`	Renter wallet balance (SAR).
`list_gpus`	List rentable GPU types (e.g. `H100`, `RTX 4090`) with VRAM + live availability.
`create_pod`	Rent a whole GPU as an interactive pod (root + Jupyter + SSH), prepaid per minute.
`get_pod`	Pod status + access URL / SSH command / time remaining.
`extend_pod`	Add time to a running pod, no restart.
`stop_pod`	Stop early; unused prepaid time refunded.
`rent_volume`	Rent an exclusive in-Kingdom persistent volume (10/20/30 GB).
`get_volume`	Active volume status + usage.

Zero-human quickstart (for agents)

The whole loop runs with no human in it:

`register_agent` → returns a real api_key + a 20 SAR trial credit (no email click). Set it as DCP_API_KEY.
`list_gpus` → pick a gpu_type string (e.g. "H100", "RTX 4090") from the live, available types.
`create_pod` with that gpu_type + duration_minutes → poll `get_pod` for the access_url / ssh_command once running.
`chat` → run OpenAI-compatible inference on an available model from list_models.
`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.

Dcp MCP

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

@dcp/mcp — DCP Model Context Protocol server

Install (one line)

MCP client config

Tools

Zero-human quickstart (for agents)

→ { "api_key": "dcp-renter-…", "trial_credit_sar": 20, "balance_sar": 20, ... }

Environment

Why DCP