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Snippy MCP Server

@Azure-Samples

基本信息

分类

AI 与智能体

许可证

MIT

传输方式

stdio

作者

Azure-Samples

关于 Snippy MCP Server

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

Snippy MCP Server 配置

暂无标准配置

该服务器的 README 中没有可解析的 MCP 配置块,请前往代码仓库查看安装说明。

代码仓库

Snippy MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

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.

常见问题

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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