Skip to main content
Glama
config.template.json3.01 kB
{ "description": "Configuration template for Microsoft Fabric Analytics MCP Server testing", "fabric_credentials": { "bearer_token": "YOUR_BEARER_TOKEN_HERE", "workspace_id": "YOUR_WORKSPACE_ID_HERE", "lakehouse_id": "YOUR_LAKEHOUSE_ID_HERE", "notebook_id": "YOUR_NOTEBOOK_ID_HERE" }, "testing_options": { "include_performance_tests": true, "timeout_seconds": 300, "retry_attempts": 3, "verbose_logging": true }, "spark_cluster_configs": { "small": { "driverCores": 2, "driverMemory": "4g", "executorCores": 1, "executorMemory": "2g", "numExecutors": 2 }, "medium": { "driverCores": 4, "driverMemory": "8g", "executorCores": 2, "executorMemory": "4g", "numExecutors": 3 }, "large": { "driverCores": 8, "driverMemory": "16g", "executorCores": 4, "executorMemory": "8g", "numExecutors": 5 } }, "sample_data_scenarios": { "sales_analysis": { "description": "Comprehensive sales data analysis with forecasting", "estimated_runtime": "5-10 minutes", "required_permissions": ["lakehouse_read", "spark_compute"] }, "customer_segmentation": { "description": "Customer lifetime value and segmentation analysis", "estimated_runtime": "3-7 minutes", "required_permissions": ["lakehouse_read", "spark_compute"] }, "inventory_optimization": { "description": "Inventory forecasting and optimization", "estimated_runtime": "8-15 minutes", "required_permissions": ["lakehouse_read", "spark_compute", "ml_workspace"] } }, "notebook_test_scenarios": [ { "name": "Financial Reporting Automation", "parameters": { "report_period": "Q4-2024", "include_forecasts": true, "departments": ["Sales", "Marketing", "Finance"], "export_formats": ["xlsx", "pdf"], "email_distribution": true } }, { "name": "Real-time Dashboard Updates", "parameters": { "refresh_interval_minutes": 15, "data_sources": ["sales_db", "marketing_api", "finance_warehouse"], "alert_thresholds": { "revenue_variance": 0.1, "conversion_rate_drop": 0.05 } } } ], "environment_variables": { "FABRIC_BEARER_TOKEN": "Set this to your actual bearer token", "FABRIC_WORKSPACE_ID": "Set this to your workspace ID", "FABRIC_LAKEHOUSE_ID": "Set this to your lakehouse ID", "FABRIC_NOTEBOOK_ID": "Set this to your notebook ID", "MCP_SERVER_HOST": "localhost", "MCP_SERVER_PORT": "3000", "LOG_LEVEL": "INFO" }, "usage_instructions": { "quick_start": "Copy this file to config.json and replace YOUR_*_HERE with actual values", "command_line": "python real_fabric_test.py --config config.json", "interactive": "python real_fabric_test.py --interactive", "performance": "python real_fabric_test.py --config config.json --performance" } }

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/santhoshravindran7/Fabric-Analytics-MCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server