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Snippy MCP Server

@Azure-Samples

基本情報

カテゴリ

AI とエージェント

ライセンス

MIT

トランスポート

stdio

作者

Azure-Samples

Snippy MCP Server について

🧩 Build AI-powered MCP Tools with Azure Functions, Durable Agents & Cosmos vector search. Features orchestrated multi-agent workflows using OpenAI.

Snippy MCP Server の設定

標準の設定はありません

このサーバーの README には解析可能な MCP 設定ブロックが含まれていません。インストール手順はリポジトリをご確認ください。

リポジトリ

Snippy MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Snippy?

Snippy is an Azure Functions-based reference application that demonstrates how to build MCP (Model Context Protocol) tools that integrate with AI assistants like GitHub Copilot. It showcases a serverless AI architecture using Azure Functions, Durable Functions, Azure OpenAI, and the Agent Framework for code snippet management and multi-agent orchestration.

How to use Snippy?

Deploy the entire stack to Azure with a single azd up command after satisfying prerequisites (Azure subscription, azd CLI, and a development environment such as GitHub Codespaces or VS Code Dev Containers). For local development, use Docker-based emulators and Azure Functions Core Tools v4. Once deployed, the Function App URL and MCP endpoint are displayed, ready for integration with AI assistants.

Key features of Snippy

  • Expose Azure Functions as discoverable MCP tools.
  • Stateful AI agents with automatic conversation history.
  • Multi-agent orchestration via Durable Task Scheduler.
  • Semantic code retrieval with Cosmos DB vector search.
  • Real-time monitoring with DTS dashboard.
  • One-click infrastructure deployment using azd up.

Use cases of Snippy

  • Save code snippets with vector embeddings for semantic search.
  • Retrieve snippets by name for quick reference.
  • Generate language-specific code style guides from saved snippets.
  • Create comprehensive wiki documentation via multi-agent workflow.
  • Use as a reference architecture for building production‑ready MCP tools.

よくある質問

1

What is the purpose of Snippy?

Snippy is intended for **learning and demonstration**—it shows how to build MCP tools with Azure Functions. It should **not** be deployed to production without a thorough security review.

2

What are the prerequisites to deploy Snippy?

You need an Azure subscription with permission to create resources, the `azd` CLI installed, and a development environment (GitHub Codespaces, VS Code Dev Containers with Docker Desktop, or a local setup with Python 3.11, Node 18+, and Azure Functions Core Tools v4).

3

Which Azure regions are recommended?

The README recommends **eastus** or **swedencentral** because Azure OpenAI model availability varies by region. Verify model support in those regions before deploying.

4

How does Snippy handle security?

Snippy uses **User-Assigned Managed Identity** for service-to-service authentication, with RBAC roles for Cosmos DB, Storage, Application Insights, and Azure AI Project. For production, the README advises restricting network access via Private Endpoints and VNet integration.

5

Which MCP tools are included?

The tool matrix lists five tools: `save_snippet`, `get_snippet`, `code_style`, `deep_wiki`, and `generate_comprehensive_documentation` (an orchestrated multi-agent workflow).

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