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https://github.com/azure-samples/snippy

🧩 Demo: Build AI-powered MCP Tools for GitHub Copilot using Azure Functions, OpenAI, AI Agents & Cosmos DB. Manages code snippets w/ vector search.
https://github.com/azure-samples/snippy

ai-agents azure-functions copilot cosmosdb mcp mcp-server

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🧩 Demo: Build AI-powered MCP Tools for GitHub Copilot using Azure Functions, OpenAI, AI Agents & Cosmos DB. Manages code snippets w/ vector search.

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README 

          





  Snippy logo


  Snippy · Intelligent Code-Snippet Service with MCP Tools




[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://github.com/codespaces/new?hide_repo_select=true&ref=main&repo=Azure-Samples/snippy&machine=basicLinux32gb&devcontainer_path=.devcontainer%2Fdevcontainer.json)

[![Open in Dev Containers](https://img.shields.io/static/v1?style=for-the-badge&label=Dev%20Containers&message=Open&color=blue&logo=visualstudiocode)](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/Azure-Samples/snippy)



Snippy is an **Azure Functions**–based reference application that turns any function into an **MCP (Model Context Protocol) tool** consumable by GitHub Copilot Chat and other MCP‑aware clients. The sample implements a production‑style *code‑snippet service* with AI‑powered analysis:



* **Save snippets** – persists code, metadata and OpenAI embeddings in **Cosmos DB DiskANN**

* **Semantic retrieve** – vector search over embeddings

* **AI Agents** – generate a **deep wiki** or language‑specific **code style guide** from stored snippets

* **Durable fan‑out/fan‑in with Blueprints** – [in experimental branch](https://github.com/Azure-Samples/snippy/tree/gk/durable-functions) for large‑scale processing

* **Microsoft Fabric integration** – [in gk/fabric branch](https://github.com/Azure-Samples/snippy/tree/gk/fabric) demonstrating how to build Agents with Fabric Data Agents



The project ships with reproducible **azd** infrastructure, so `azd up` will stand up the entire stack – Functions, Cosmos DB, Azure OpenAI and Azure AI Agents – in a single command.



> **Important Security Notice**

> This repository is intended for learning and demonstration purposes. **Do not** deploy it to production without a thorough security review. At a minimum you should:

>

> * Swap connection strings for **Managed Identity** + **Azure Key Vault**

> * Restrict network access to Azure services via Private Endpoints or service‑tags

> * Enable GitHub secret‑scanning and CI security tools



[Features](#features) • [Architecture](#architecture-diagram) • [Getting Started](#getting-started) • [Guidance](#guidance)



---



## Features



* **Remote MCP trigger** – expose Functions as real‑time SSE tools

* **AI‑assisted documentation** – "deep‑wiki" and "code‑style" agents create rich Markdown (Mermaid, diagrams, etc.)

* **Vector search on Cosmos DB DiskANN** – low‑latency semantic retrieval

* **One‑click deploy** – `azd up` provisions and deploys code & infra

* **Codespaces & Dev Containers** – fully configured dev environment in your browser or local VS Code



### Tool Matrix



| Tool Name      | Purpose                                                             |

| -------------- | ------------------------------------------------------------------- |

| `save_snippet` | Save code snippets with vector embeddings for semantic search       |

| `get_snippet`  | Retrieve previously saved code snippets by their unique name        |

| `code_style`   | Generate language-specific code style guides from saved snippets    |

| `deep_wiki`    | Create comprehensive wiki documentation by analyzing code snippets  |



---



### Architecture Diagram



![Snippy Architecture](https://raw.githubusercontent.com/Azure-Samples/snippy/main/.github/assets/snippy-architecture.png)



```mermaid

flowchart LR

    %% ─── MCP Hosts & Clients (local) ──────────────────────────────

    subgraph mcphosts["MCP Hosts & Clients (Your Computer)"]

        Host["Host
(VS Code / IDE)"]

        Client["Client
(GitHub Copilot)"]

    end



    %% ─── Application on Azure (remote) ────────────────────────────

    subgraph app["Application (Azure)"]

        Snippy["MCP Server
Snippy Triggers
(Function App)"]:::dashed

        Foundry["Foundry Agent
Deep Wiki · Code Style"]

        Cosmos["Cosmos DB
Operational + Vector DB"]:::datasource

        AOAI["Azure OpenAI
text‑embedding‑3‑small"]

        FabricDA["Fabric – Data Agent"]

        VectorTool["Tools – Vector Search"]

    end



    %% ─── Local interactions ───────────────────────────────────────

    Host <--> Client



    %% ─── MCP protocol to Azure ────────────────────────────────────

    Client <-- "MCP Protocol (SSE)" --> Snippy



    %% ─── Bindings & data flow inside Azure ────────────────────────

    Snippy -- Bindings --> AOAI

    Snippy --> Cosmos

    Snippy --> Foundry

    Foundry --> FabricDA

    Foundry --> VectorTool



    %% ─── Styling ──────────────────────────────────────────────────

    classDef datasource stroke-width:2,stroke-dasharray:5 5

    classDef dashed stroke-width:2,stroke-dasharray:5 5,fill:transparent

    class Cosmos datasource

    class Snippy dashed

    style mcphosts fill:transparent

    style app fill:transparent

```



---



## Getting Started



You can run Snippy in **GitHub Codespaces**, **VS Code Dev Containers**, or your **local environment**. The fastest path is Codespaces.



> Snippy requires an Azure region that supports *text‑embedding‑3‑small* (or a compatible embeddings model) **and** Azure AI Agents. The `azd` workflow prompts you for a region; we recommend **eastus** for best availability.



### GitHub Codespaces



1. Click **Open in Codespaces** above (first badge) – the container build may take a few minutes.

2. When the terminal appears, sign in:



   ```bash

   azd auth login --use-device-code

   ```

3. Launch the stack:



   ```bash

   azd up

   ```

4. Once deployment completes, copy the printed MCP URL and open GitHub Copilot Chat → *Agent* mode to try commands like “Save this snippet as **hello‑world**”.



### VS Code Dev Containers



Prerequisites: [Docker Desktop](https://www.docker.com/products/docker-desktop) + the [Dev Containers](https://aka.ms/vscode/dev-containers) extension.



1. Click the **Dev Containers** badge (second badge) or run *Remote‑Containers: Open Repository in Container* from VS Code.

2. Sign in and launch as shown for Codespaces:



   ```bash

   azd auth login

   azd up

   ```



### Local Environment



#### Prerequisites



* [azd](https://aka.ms/install-azd) CLI

* Python 3.11 + [`uv`](https://github.com/astral-sh/uv)

* Node 18+ (for Functions Core Tools)

* Azure Functions Core Tools v4 (`npm i -g azure-functions-core-tools@4 --unsafe-perm`)



#### Quickstart



```bash

# 1. Clone & init

azd init --template Azure-Samples/snippy



# 2. Sign in

azd auth login



# 3. Provision & deploy

azd up

```



The CLI prints the Function App URL, MCP endpoint and system key when finished. To remove all resources later:



```bash

azd down --purge

```



---



## Guidance



### Region Availability



Azure OpenAI model support varies by region. Verify availability [here](https://learn.microsoft.com/azure/ai-services/openai/concepts/models#standard-deployment-model-availability) and choose the same region for all Azure resources. **eastus** and **swedencentral** are good default choices.



### Costs



Estimate monthly cost using the [Azure Pricing Calculator](https://azure.microsoft.com/pricing/calculator/). Major components:



* Azure Functions – Consumption / Flex tiers

* Cosmos DB – Serverless or provisioned throughput

* Azure OpenAI – pay‑as‑you‑go per 1K tokens

* Azure AI Agents – per‑execution billing (preview)



### Security



Snippy uses User-Assigned Managed Identity for secure service-to-service authentication. The infrastructure is configured with:



* **User-Assigned Managed Identity** on the Function App with appropriate RBAC roles:

  * Cosmos DB Data Contributor

  * Storage Blob Data Owner and Queue Data Contributor

  * Application Insights Monitoring Metrics Publisher

  * Azure AI Project Developer



For production deployments, we recommend:



* Restrict inbound traffic with Private Endpoints + VNet integration

* Enable network security features like service endpoints and firewall rules



---



## Resources



* Blog – *Build AI agent tools using Remote MCP with Azure Functions* ([https://aka.ms/snippy-blog](https://aka.ms/snippy-blog))

* Model Context Protocol spec – [https://aka.ms/mcp](https://aka.ms/mcp)

* Azure Functions Remote MCP docs – [https://aka.ms/azure-functions-mcp](https://aka.ms/azure-functions-mcp)

* Develop Python apps for Azure AI – [https://learn.microsoft.com/azure/developer/python/azure-ai-for-python-developers](https://learn.microsoft.com/azure/developer/python/azure-ai-for-python-developers)



---



## Contributing



Standard **fork → branch → PR** workflow. Use *Conventional Commits* (`feat:`, `fix:`) in commit messages.



---



## License



MIT © Microsoft Corporation