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datumnova/ms-fabric-mcp

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A comprehensive Python-based MCP (Model Context Protocol) server for interacting with Microsoft Fabric APIs, featuring advanced PySpark notebook development, testing, and optimization capabilities...

概览

A comprehensive Python-based MCP (Model Context Protocol) server for interacting with Microsoft Fabric APIs, featuring advanced PySpark notebook development, testing, and optimization capabilities with LLM integration. - ✅ Workspace, lakehouse, warehouse, and table management - ✅ Delta table schemas and metadata retrieval - ✅ SQL query execution and data loading - ✅ Report and semantic model operations - 📓 with 6 specialized templates - 🔧 for common PySpark operations - ✅ with syntax and best practices checking - 🎯 and compatibility checks - 📊 with scoring and optimization recommendations - 🚀 and execution insights - 🤖 for PySpark development - 🧠 with conversation memory - 🎨 and explanations - 📈 based on project patterns - - for authentication - (from astral): Installation instructions - : Installation instructions - for MCP inspector: Installation instructions This starts the server with inspector at http://localhost:6274.

README

以下为原文 README 节选,完整内容请查看原文。

Microsoft Fabric MCP Server

A comprehensive Python-based MCP (Model Context Protocol) server for interacting with Microsoft Fabric APIs, featuring advanced PySpark notebook development, testing, and optimization capabilities with LLM integration.

🚀 Features

Core Fabric Operations

  • ✅ Workspace, lakehouse, warehouse, and table management
  • ✅ Delta table schemas and metadata retrieval
  • ✅ SQL query execution and data loading
  • ✅ Report and semantic model operations

Advanced PySpark Development

  • 📓 Intelligent notebook creation with 6 specialized templates
  • 🔧 Smart code generation for common PySpark operations
  • ✅ Comprehensive validation with syntax and best practices checking
  • 🎯 Fabric-specific optimizations and compatibility checks
  • 📊 Performance analysis with scoring and optimization recommendations
  • 🚀 Real-time monitoring and execution insights

LLM Integration

  • 🤖 Natural language interface for PySpark development
  • 🧠 Context-aware assistance with conversation memory
  • 🎨 Intelligent code formatting and explanations
  • 📈 Smart optimization suggestions based on project patterns

🏗️ Architecture

graph TB
    subgraph "Developer Environment"
        IDE[IDE/VSCode]
        DEV[Developer]
        PROJ[Project Files]
    end
    
    subgraph "AI Layer"
        LLM[Large Language ModelClaude/GPT/etc.]
        CONTEXT[Conversation Context]
        REASONING[AI Reasoning Engine]
    end
    
    subgraph "MCP Layer"
        MCP[MCP Server]
        TOOLS[PySpark Tools]
        HELPERS[PySpark Helpers]
        TEMPLATES[Template Manager]
        VALIDATORS[Code Validators]
        GENERATORS[Code Generators]
    end
    
    subgraph "Microsoft Fabric"
        API[Fabric API]
        WS[Workspace]
        LH[Lakehouse]
        NB[Notebooks]
        TABLES[Delta Tables]
        SPARK[Spark Clusters]
    end
    
    subgraph "Operations Flow"
        CREATE[Create Notebooks]
        VALIDATE[Validate Code]
        GENERATE[Generate Code]
        ANALYZE[Analyze Performance]
        DEPLOY[Deploy to Fabric]
    end
    
    %% Developer interactions
    DEV --> IDE
    IDE --> PROJ
    
    %% LLM interactions
    IDE  LLM
    LLM  CONTEXT
    LLM --> REASONING
    
    %% MCP interactions
    LLM  MCP
    MCP --> TOOLS
    TOOLS --> HELPERS
    TOOLS --> TEMPLATES
    TOOLS --> VALIDATORS
    TOOLS --> GENERATORS
    
    %% Fabric interactions
    MCP  API
    API --> WS
    WS --> LH
    WS --> NB
    LH --> TABLES
    NB --> SPARK
    
    %% Operation flows
    TOOLS --> CREATE
    TOOLS --> VALIDATE
    TOOLS --> GENERATE
    TOOLS --> ANALYZE
    CREATE --> DEPLOY
    
    %% Data flow arrows
    REASONING -.->|"Intelligent Decisions"| TOOLS
    CONTEXT -.->|"Project Awareness"| VALIDATORS
    
    %% Styling
    classDef devEnv fill:#e1f5fe
    classDef aiLayer fill:#fff9c4
    classDef mcpLayer fill:#f3e5f5
在 GitHub 查看完整 README

安装

This server does not publish a one-line install command.

Open the repository installation guide 新手?先看 mcpskill.org 教程 →