# MCP Serve

> Use this tool when you need to deploy and manage Deep Learning models with flexibility and ease, solving problems such as model serving, remote access, and framework compatibility. It accepts model inputs and outputs via Shell, Ngrok, and Docker interfaces, supporting multiple AI frameworks like Anthropic, Gemini, and OpenAI. Ideal for use cases requiring scalable and secure model hosting, MCP Serve streamlines the deployment process for various AI applications.

Canonical page: https://skillsregistry.net/skills/mark-oori-mcpserve  
JSON: https://api.skillsregistry.net/v1/skills/mark-oori-mcpserve

## Description

A server tool for running Deep Learning models that offers Shell execution, Ngrok connectivity, and Docker container hosting with support for multiple AI frameworks including Anthropic, Gemini, and OpenAI.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** cloud-infra
- **Updated:** 2026-09-02

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/mn4iwptrqz)
- **Repository:** <https://github.com/mark-oori/mcpserve>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "mark-oori-mcpserve"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/mark-oori-mcpserve` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/mark-oori-mcpserve/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt