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.
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
- SAP Analytics Cloud tenant with API access enabled
- OAuth 2.0 client configured in SAC (Administration → App Integration → OAuth Clients)
- Grant type: Client Credentials
- Note down: Client ID, Client Secret, Token URL
- 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_models → sac_get_model_metadata → sac_read_fact_data
"List all users" → calls sac_list_users
"Import this sales data into model X" → calls sac_create_import_job → sac_post_import_data → sac_validate_import → sac_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
- Fork the repository
- Create a feature branch (
git checkout -b feature/my-feature) - Commit your changes (
git commit -am 'Add my feature') - Push to the branch (
git push origin feature/my-feature) - Open a Pull Request
License
ISC — see LICENSE for details.
推荐服务器
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。
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。
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。
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。
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。
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。
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。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
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。