power-bi-mcp

power-bi-mcp

An MCP (Model Context Protocol) server that lets AI agents manage Power BI workspaces, datasets, and refreshes via natural language.

Category
访问服务器

README

Power BI MCP Server

An MCP (Model Context Protocol) server that lets AI agents manage Power BI workspaces, datasets, and refreshes via natural language.

Features

Authentication & Discovery

Tool Description
pbi_auth Authenticate via Azure AD device code flow (with token caching & auto-refresh)
pbi_list_workspaces List accessible workspaces (with optional name filter)
pbi_list_datasets List datasets in a workspace

Dataset & Refresh Management

Tool Description
pbi_dataset_info Aggregate dataset metadata + datasources + gateways + refresh schedule + impacted reports + PBIP locate (single call)
pbi_refresh_dataset Trigger an Enhanced refresh (supports table-level, polling, retry, timeout)
pbi_refresh_manage Refresh lifecycle: view history (status), get execution details (details), or cancel (cancel)

Diagnostics & Source Code

Tool Description
pbi_diagnose One-shot diagnostic report for refresh failures — root cause classification, error catalog, next actions, PBIP source hints
pbi_locate_pbip Locate PBIP source code for a dataset (fuzzy folder match + optional table TMDL & M source extraction)

Query & Reporting

Tool Description
pbi_execute_query Execute DAX queries against a dataset (supports RLS impersonation)
pbi_scheduled_refresh_report Generate a daily scheduled-refresh status report across all datasets in a workspace (JSON or Markdown table)

Architecture

server.py            # Entry point — configures logging, runs MCP via stdio
app.py               # FastMCP instance with server instructions
config.py            # Configuration loader (config.json, defaults, constants)
auth.py              # Azure AD device code flow, token caching, HTTP helpers
diagnostics.py       # Refresh error classification, PBIP folder/table locator
error_catalog.py     # Error code catalog + regex patterns for failure classification
tools/               # MCP tool modules (auto-registered via __init__.py)
  ├── auth_tool.py   #   pbi_auth
  ├── workspace.py   #   pbi_list_workspaces, pbi_list_datasets
  ├── dataset.py     #   pbi_dataset_info
  ├── refresh.py     #   pbi_refresh_dataset, pbi_refresh_manage
  ├── diagnose.py    #   pbi_diagnose, pbi_locate_pbip
  ├── query.py       #   pbi_execute_query
  └── report.py      #   pbi_scheduled_refresh_report
setup.ps1            # Azure AD App Registration automation (PowerShell)
config.json          # User-specific config (gitignored)

Quick Start

1. Install dependencies

git clone https://github.com/FreelexHo/power-bi-mcp.git && cd power-bi-mcp
uv venv && uv sync

<details> <summary>Don't have uv? Use pip instead</summary>

python -m venv .venv
# Windows
.venv\Scripts\activate
# macOS/Linux
source .venv/bin/activate

pip install -e .

</details>

2. Register in your MCP client

Add to your MCP client configuration:

Cursor / Windsurf / Antigravity IDE (mcp.json):

{
  "mcpServers": {
    "power-bi": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/power-bi-mcp", "server.py"],
      "transport": "stdio"
    }
  }
}

3. Authenticate (one-time)

Just use the MCP! On first use, the agent will call pbi_auth and show you a message like:

To sign in, visit https://microsoft.com/devicelogin
and enter the code XXXXXXXX
  1. Open the link in your browser
  2. Enter the code shown
  3. Sign in with your Microsoft work account
  4. Approve the permissions

That's it. Tokens are cached to ~/.powerbi-mcp/token.json and auto-refreshed — you won't need to do this again unless you revoke access.

Configuration

The server works out of the box with a built-in public client_id. Create a config.json in the project root to customize:

{
    "client_id": "<your-azure-ad-client-id>",
    "token_cache_dir": "~/.powerbi-mcp",
    "pbip_root": "C:/path/to/your/pbip-repo/data/power-bi-report"
}
Key Default Description
client_id Built-in public app Azure AD App Registration client ID
token_cache_dir ~/.powerbi-mcp Directory for cached OAuth tokens
pbip_root (none) Local PBIP repo root — enables pbi_locate_pbip and pbi_diagnose source-level hints

A setup.ps1 script is included to automate App Registration creation via Azure CLI. See Advanced Setup below.

Troubleshooting

AADSTS7000218: The request body must contain ... client_assertion

Your organization may block public client flows. Ask your Azure AD admin to either:

  • Allow public client flows on the app registration, or
  • Create a dedicated App Registration for your team (use setup.ps1)

AADSTS65001: The user or administrator has not consented

First-time users in a new Azure AD tenant need to consent to Power BI permissions. If your tenant requires admin consent:

  • Ask your admin to grant consent via Azure Portal -> App registrations -> API permissions -> "Grant admin consent"
  • Or use setup.ps1 to create your own App Registration where you are the owner

AADSTS50076: MFA required or AADSTS50079

Multi-factor authentication is required by your organization. The device code flow supports MFA — complete the MFA challenge in your browser when prompted.

Not authenticated. Call pbi_auth first.

Token has expired and could not be refreshed. The agent should automatically re-trigger pbi_auth. If it doesn't, ask the agent to call pbi_auth again.

Token keeps expiring

By default, tokens are cached at ~/.powerbi-mcp/token.json. Make sure:

  • The directory is writable
  • You are not running multiple instances that overwrite each other's tokens

Refresh details return 403

A 403 on pbi_refresh_manage action=details typically indicates insufficient permissions or the refresh record has expired.

Advanced Setup

For organizations that require their own App Registration:

Prerequisites

  • Azure CLI
  • Azure AD permissions to create App Registrations

Run setup

./setup.ps1

This creates an Azure AD App Registration with the correct configuration:

Setting Value
Sign-in audience Multi-tenant (any Azure AD directory)
Public client flows Enabled
Redirect URI https://login.microsoftonline.com/common/oauth2/nativeclient
API Permissions Power BI Service: Dataset.ReadWrite.All, Workspace.Read.All (Delegated)

Tech Stack

  • Python ≥ 3.10
  • FastMCP (mcp[cli] ≥ 1.6.0) — MCP server framework, stdio transport
  • httpx ≥ 0.27.0 — HTTP client for Azure AD & Power BI REST API calls

License

MIT

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选