exception-mcp-server
Provides AI-powered analysis of exceptions using Azure OpenAI's language models, enabling intelligent reasoning and categorization of stack traces and error data.
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
Exception Analysis Framework
AI-powered exception analysis for operations teams
π Quick Start
# 1. Install dependencies
pip install -r requirements.txt
# 2. Configure credentials
# Edit config.yaml and paste your Azure OpenAI endpoint and API key:
# azure_openai:
# endpoint: "https://your-resource.openai.azure.com/"
# api_key: "your-api-key-here"
# 3. Run tests
python test_framework.py
# 4. Ingest data
python ingest.py
# 5. Launch UI
streamlit run streamlit_app.pyRelated MCP server: SAP RCA MCP Server
π Full Documentation
See FRAMEWORK_README.md for complete documentation including:
Configuration guide
Testing procedures
Usage examples
Adaptation for other projects
Troubleshooting
π§ͺ Test Framework
python test_framework.pyExpected: 5/7 tests pass (2 expected failures: ChromaDB install, Azure credentials)
π Project Structure
βββ config.yaml # Configuration
βββ llm_client.py # Azure OpenAI client
βββ stacktrace_parser.py # Parse stack traces
βββ vector_store.py # ChromaDB wrapper
βββ server.py # MCP server
βββ streamlit_app.py # UI
βββ ingest.py # Load data into vector DB
βββ test_framework.py # Test suite
βββ data/
β βββ exceptions.csv # Exception data (100 samples)
βββ FRAMEWORK_README.md # Complete documentationβ¨ Features
Vector similarity search using ChromaDB
AI analysis with Azure OpenAI
Simple architecture that works across projects
Comprehensive tests included
Copy-paste schema - no manual definitions
Framework is production-ready. Run tests and start analyzing exceptions! π―
Tool Schema Changelog
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Maintenance
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