mcp-sac-tools

mcp-sac-tools

MCP server for SAP Analytics Cloud, enabling AI assistants to interact with SAC stories, models, data, users, and audit logs via the SAC REST API.

Category
访问服务器

README

mcp-sac-tools

MCP (Model Context Protocol) server for SAP Analytics Cloud — enables AI assistants to interact with SAC stories, models, data, users, and audit logs via the SAC REST API.

27 tools across 7 categories: stories, data export, data import, user/team management (SCIM 2.0), audit, resources, and diagnostics.

Features

Stories & Resources

  • sac_list_stories / sac_get_story — Browse stories with optional model metadata
  • sac_list_resources / sac_get_resource — List content resources (stories, models, folders)

Data Export (Read)

  • sac_list_models — List all models/providers on the tenant
  • sac_get_model_metadata — Get model schema (dimensions, measures, types)
  • sac_read_fact_data — Query fact data with OData filtering, paging, column selection
  • sac_read_master_data — Read dimension member master data
  • sac_read_audit_data — Read model-level change logs

Data Import (Write)

  • sac_create_import_job — Allocate a staging area for data import
  • sac_post_import_data — Push rows to staging (does not touch model yet)
  • sac_validate_import — Validate staged data before committing
  • sac_run_import — Execute import (async)
  • sac_import_status — Check import job progress
  • sac_import_invalid_rows — Retrieve rejected rows

User & Team Management (SCIM 2.0)

  • sac_list_users / sac_get_user / sac_create_user / sac_update_user / sac_delete_user
  • sac_list_teams / sac_get_team / sac_create_team / sac_update_team / sac_delete_team

Audit & Diagnostics

  • sac_export_audit_activities — Export tenant audit/login activities
  • sac_server_status — MCP server health check

Prerequisites

  1. SAP Analytics Cloud tenant with API access enabled
  2. OAuth 2.0 client configured in SAC (Administration → App Integration → OAuth Clients)
    • Grant type: Client Credentials
    • Note down: Client ID, Client Secret, Token URL
  3. Node.js v18+

Setup

# Install dependencies
npm install

# Copy and fill in your credentials
cp .env.example .env
# Edit .env with your SAC tenant details

# Build
npm run build

# Test with MCP Inspector
npm run inspect

Configuration

Environment Variables

Variable Required Description
SAC_TENANT_URL Yes SAC tenant URL (e.g. https://mytenant.eu10.sapanalytics.cloud)
SAC_TOKEN_URL Yes OAuth token endpoint (e.g. https://mytenant.authentication.eu10.hana.ondemand.com/oauth/token)
SAC_CLIENT_ID Yes OAuth client ID
SAC_CLIENT_SECRET Yes OAuth client secret
CACHE_TTL_SECONDS No Cache TTL in seconds (default: 300)
LOG_LEVEL No Log level: info, debug, error (default: info)

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "sap-analytics-cloud": {
      "command": "node",
      "args": ["c:\\path\\to\\mcp-sac-tools\\dist\\index.js"],
      "env": {
        "SAC_TENANT_URL": "https://mytenant.eu10.sapanalytics.cloud",
        "SAC_TOKEN_URL": "https://mytenant.authentication.eu10.hana.ondemand.com/oauth/token",
        "SAC_CLIENT_ID": "your-client-id",
        "SAC_CLIENT_SECRET": "your-client-secret"
      }
    }
  }
}

Example Usage

"Show me all stories" → calls sac_list_stories

"What data is in the Revenue model?" → calls sac_list_modelssac_get_model_metadatasac_read_fact_data

"List all users" → calls sac_list_users

"Import this sales data into model X" → calls sac_create_import_jobsac_post_import_datasac_validate_importsac_run_import

Architecture

src/
├── index.ts              # Entry point (stdio transport)
├── server.ts             # Server factory (wires APIs → handlers)
├── auth/
│   ├── oauth.ts          # OAuth 2.0 client credentials
│   └── token-manager.ts  # Token caching with auto-refresh
├── api/
│   ├── sac-client.ts     # Authenticated HTTP client (CSRF handling)
│   ├── stories.ts        # /api/v1/stories
│   ├── data-export.ts    # /api/v1/dataexport (OData CDI)
│   ├── data-import.ts    # /api/v1/dataimport
│   ├── scim.ts           # /api/v1/scim2
│   ├── audit.ts          # /api/v1/audit
│   └── resources.ts      # /api/v1/Resources
├── handlers/
│   ├── BaseHandler.ts    # Abstract base (jsonResponse/errorResponse)
│   ├── StoryHandlers.ts
│   ├── DataExportHandlers.ts
│   ├── DataImportHandlers.ts
│   ├── ScimHandlers.ts
│   ├── AuditHandlers.ts
│   ├── ResourceHandlers.ts
│   └── DiagnosticHandlers.ts
├── cache/
│   └── cache-manager.ts  # TTL-based in-memory cache
└── types/
    └── sac.ts            # TypeScript interfaces

Contributing

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/my-feature)
  3. Commit your changes (git commit -am 'Add my feature')
  4. Push to the branch (git push origin feature/my-feature)
  5. Open a Pull Request

License

ISC — see LICENSE for details.

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