mcp-builder-ms
Helps your agent integrate external services when building MCP servers. It works with Python or Node/TypeScript to connect APIs.
What it does
This tool helps build servers so that artificial intelligences (AI) can connect to and use other services or APIs. Think of it as a translator that allows AI to understand and interact with external systems.
When to use it
- ✓When you want an AI to control a cloud service (like Azure).
- ✓When you need an AI to use an API that wasn't originally designed for it.
- ✓To create bridges between different AI systems and external services.
Example of what to ask your AI
“Create an MCP server so the AI can access and manage my files in Azure Blob Storage.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
You define how the AI should interact with an external service. The tool creates the server structure and the necessary connections for the AI to send and receive information from that service.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add sickn33/agentic-awesome-skills --skill mcp-builder-msOr download just the file:
curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/mcp-builder-ms/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
MCP Server Development Guide
When to Use
Use this skill when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Overview
Create MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. The quality of an MCP server is measured by how well it enables LLMs to accomplish real-world tasks.
Microsoft MCP Ecosystem
Microsoft provides extensive MCP infrastructure for Azure and Foundry services. Understanding this ecosystem helps you decide whether to build custom servers or leverage existing ones.
Server Types
| Type | Transport | Use Case | Example |
|---|---|---|---|
| Local | stdio | Desktop apps, single-user, local dev | Azure MCP Server via NPM/Docker |
| Remote | Streamable HTTP | Cloud services, multi-tenant, Agent Service | https://mcp.ai.azure.com (Foundry) |
Microsoft MCP Servers
Before building a custom server, check if Microsoft already provides one:
| Server | Type | Description |
|---|---|---|
| Azure MCP | Local | 48+ Azure services (Storage, KeyVault, Cosmos, SQL, etc.) |
| Foundry MCP | Remote | https://mcp.ai.azure.com - Models, deployments, evals, agents |
| Fabric MCP | Local | Microsoft Fabric APIs, OneLake, item definitions |
| Playwright MCP | Local | Browser automation and testing |
| GitHub MCP | Remote | https://api.githubcopilot.com/mcp |
Full ecosystem: See 🔷 Microsoft MCP Patterns for complete server catalog and patterns.
When to Use Microsoft vs Custom
| Scenario | Recommendation |
|---|---|
| Azure service integration | Use Azure MCP Server (48 services covered) |
| AI Foundry agents/evals | Use Foundry MCP remote server |
| Custom internal APIs | Build custom server (this guide) |
| Third-party SaaS integration | Build custom server (this guide) |
| Extending Azure MCP | Follow Microsoft MCP Patterns |
Process
🚀 High-Level Workflow
Creating a high-quality MCP server involves four main phases:
Phase 1: Deep Research and Planning
1.1 Understand Modern MCP Design
API Coverage vs. Workflow Tools: Balance comprehensive API endpoint coverage with specialized workflow tools. Workflow tools can be more convenient for specific tasks, while comprehensive coverage gives agents flexibility to compose operations. Performance varies by client—some clients benefit from code execution that combines basic tools, while others work better with higher-level workflows. When uncertain, prioritize comprehensive API coverage.
Tool Naming and Discoverability:
Clear, descriptive tool names help agents find the right tools quickly. Use consistent prefixes (e.g., github_create_issue, github_list_repos) and action-oriented naming.
Context Management: Agents benefit from concise tool descriptions and the ability to filter/paginate results. Design tools that return focused, relevant data. Some clients support code execution which can help agents filter and process data efficiently.
Actionable Error Messages: Error messages should guide agents toward solutions with specific suggestions and next steps.
1.2 Study MCP Protocol Documentation
Navigate the MCP specification:
Start with the sitemap to find relevant pages: https://modelcontextprotocol.io/sitemap.xml
Then fetch specific pages with .md suffix for markdown format (e.g., https://modelcontextprotocol.io/specification/draft.md).
Key pages to review:
- Specification overview and architecture
- Transport mechanisms (streamable HTTP, stdio)
- Tool, resource, and prompt definitions
1.3 Study Framework Documentation
Language Selection:
| Language | Best For | SDK |
|---|---|---|
| TypeScript (recommended) | General MCP servers, broad compatibility | @modelcontextprotocol/sdk |
| Python | Data/ML pipelines, FastAPI integration | mcp (FastMCP) |
| C#/.NET | Azure/Microsoft ecosystem, enterprise | Microsoft.Mcp.Core |
Transport Selection:
| Transport | Use Case | Characteristics |
|---|---|---|
| Streamable HTTP | Remote servers, multi-tenant, Agent Service | Stateless, scalable, requires auth |
| stdio | Local servers, desktop apps | Simple, single-user, no network |
Load framework documentation:
…
FAQ
What is an MCP server?
An MCP (Model Context Protocol) server is a special type of server that allows language models (like Claude or ChatGPT) to interact with external tools and services in a structured way.
What's the difference between Azure MCP and Foundry MCP?
Azure MCP helps AI use Microsoft Azure services. Foundry MCP is for managing AI agents and their evaluations on Microsoft's Foundry platform.
Do I need to know how to code to use this?
Yes, this guide is for developers who already know how to code in languages like TypeScript or Python and want to build servers for AI.
Details
Original description by the author
Use this skill when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Popularity
- GitHub stars
- 48k
- Ranking position
- #3570
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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