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mcp-builder

Generate and deploy MCP (Model Context Protocol) servers with planning, implementation, validation, and deployment.

Skill by baralmanish

IndexedApache-2.0
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

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About

Generate and deploy MCP (Model Context Protocol) servers with planning, implementation, validation, and deployment. Use this skill when the user asks to build, create, or generate an MCP server, extend an existing MCP server, or deploy an MCP server to production. Covers Python and Node.js SDKs, tool implementation, resource management, and best practices.

Use cases: backend, devops, agent-building

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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  • codeload.github.com · found in install command

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  • ~/.claude/skills/mcp-builder

What's inside

Skill name
mcp-builder
Description
Generate and deploy MCP (Model Context Protocol) servers with planning, implementation, validation, and deployment. Use this skill when the user asks to build, create, or generate an MCP server, extend an existing MCP server, or deploy an MCP server to production. Covers Python and Node.js SDKs, tool implementation, resource management, and best practices.
License
Apache-2.0
Instructions
294 lines in SKILL.md · view on GitHub

Files (6)

  • QUICK_REFERENCE.md
  • README.md
  • SKILL.md
  • nodejs_mcp_server.md · reference/
  • python_mcp_server.md · reference/
  • tool_design_patterns.md · reference/

SKILL.md (first lines)

# MCP Builder

Build production-ready Model Context Protocol (MCP) servers with comprehensive planning, implementation, testing, and deployment guidance.

## Process

### 🚀 High-Level Workflow

1. **Phase 1: Deep Research and Planning** — Understand requirements, study MCP architecture, plan server structure
2. **Phase 2: Implementation** — Write core server code, implement tools/resources, add error handling
3. **Phase 3: Validation** — Test locally, verify tool outputs, debug issues
4. **Phase 4: Deployment** — Containerize (if needed), set environment variables, deploy to production

### Phase 1: Deep Research and Planning

#### 1.1 Clarify Requirements

- What tools/resources should the server expose?
- What is the primary use case?
- Are there authentication or permission requirements?
- What are the scale/performance expectations?

#### 1.2 Choose SDK and Framework

- **Python**: Use the official Python SDK for MCP
  - Reference: [Python SDK README](https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md)
  - Best for: Data processing, AI integrations, scientific computing
  - Framework: FastMCP (simplified decorator-based approach) or standard SDK

- **Node.js/TypeScript**: Use the official Node.js SDK
  - Best for: Web APIs, real-time features, JavaScript ecosystem integration
  - Framework: Full SDK with fine-grained control

- **Other languages**: Check [MCP Implementations](https://github.com/modelcontextprotocol#implementations) for community SDKs

#### 1.3 Study Framework Documentation

- **Python SDK**: Understand `Server` class, `@tool` decorator, `@resource` decorator, error handling patterns
- **Node.js SDK**: Understand server initialization, `Tool` and `Resource` classes, request/response handling
- Review reference implementation guides: See `reference/python_mcp_server.md` or `reference/nodejs_mcp_server.md`

#### 1.4 Plan Server Structure

```
my-mcp-server/
├── server.py (or server.ts for Node.js)      # Main server entry point
├── tools/
│   ├── __init__.py
│   ├── tool_1.py                              # Each tool in its own module
│   ├── tool_2.py
│   └── shared_utils.py                        # Shared utility functions
├── resources/
│   ├── __init__.py
│   ├── resource_1.py                          # Each resource in its own module
│   └── templates.py                           # Template definitions
├── requirements.txt (Python) or package.json  # Dependencies
├── .env.example                               # Environment variable template
├── README.md                                  # Usage documentation
└── Dockerfile (optional)                      # For containerization
```

### Phase 2: Implementation

#### 2.1 Create Server Instance

Initialize the MCP server with proper configuration.

**Python (FastMCP - Recommended):**

```python
from mcp.server.fastmcp import FastMCP

server = FastMCP("server-name", instructions="Brief description of what this server does")
```

**Python (Standard SDK):**

```python
from mcp.server import Server
from mcp.types import Tool, Resource

server = Server("server-name")
```

**Node.js:**

```typescript
import { Server } from "@modelcontextprotocol/sdk/server/index.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";

const server = new Server({
  name: "server-name",
  version: "1.0.0",
});
```

#### 2.2 Implement Tools

A tool is a callable function that Claude can invoke. Always include:

- Clear, descriptive name
- Detailed description of what it does
- Input schema with types and documentation
- Error handling
- Return value documentation

**Python:**

```python
@server.tool()
def tool_name(arg1: str, arg2: int) -> str:
    """
    Brief description of what this tool does.

    Args:
        arg1: Description of arg1
        arg2: Description of arg2

    Returns:

From baralmanish/AI-Agent-Skills, Apache-2.0.

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Last commit (this folder)
Jun 30, 2026 (4 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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mcp-builder skill. Agent Mart. https://agentmart.dev/skills/baralmanish-mcp-builder (last updated 2026-10-24)