fix: model definition re-introduced into the schema but intelligently and only a summary is generated per tool. Required to ensure CLI calls and uses the correct model
fix: removed `model` param from some tools where this wasn't needed
fix: fixed adherence to `*_ALLOWED_MODELS` by advertising only the allowed models to the CLI
fix: removed duplicates across providers when passing canonical names back to the CLI; the first enabled provider wins
docs: document provider base class
refactor: cleanup custom provider, it should only deal with `is_custom` model configurations
fix: make sure openrouter provider does not load `is_custom` models
fix: listmodels tool cleanup
Fixed issue where OpenAI models appeared twice in listmodels output by:
- Removing self-referencing aliases from OpenAI model definitions (e.g., "gpt-5" no longer includes "gpt-5" in its aliases)
- Adding filter in listmodels.py to skip aliases that match the model name
- Cleaned up inconsistent alias naming (o3-pro -> o3pro)
This ensures each model appears only once in the listing while preserving all useful aliases.
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Co-Authored-By: Claude <noreply@anthropic.com>
- Extract restriction checking logic into reusable helper method
- Refactor validate_model_name to reduce code duplication
- Fix logging import by using existing module-level logger
- Clean up test file by removing print statement and main block
- All tests continue to pass after refactoring
- OpenAI provider now checks custom models registry for user configurations
- Custom models with supports_temperature=false no longer send temperature to API
- Fixes 400 errors for custom o3/gpt-5 models configured without temperature support
- Added comprehensive tests to verify the fix works correctly
- Maintains backward compatibility with built-in models
Fixes#245
Improvements to model name resolution
Improved instructions for multi-step workflows when continuation is available
Improved instructions for chat tool
Improved preferred model resolution, moved code from registry -> each provider
Updated tests
Moved aliases as part of SUPPORTED_MODELS instead of shorthand, more in line with how custom_models are declared
Further refactoring to cleanup some code
Fix for: https://github.com/BeehiveInnovations/zen-mcp-server/issues/102
- Removed centralized MODEL_CAPABILITIES_DESC from config.py
- Added model descriptions to individual provider SUPPORTED_MODELS
- Updated _get_available_models() to use ModelProviderRegistry for API key filtering
- Added comprehensive test suite validating bug reproduction and fix
* Migration from docker to standalone server
Migration handling
Fixed tests
Use simpler in-memory storage
Support for concurrent logging to disk
Simplified direct connections to localhost
* Migration from docker / redis to standalone script
Updated tests
Updated run script
Fixed requirements
Use dotenv
Ask if user would like to install MCP in Claude Desktop once
Updated docs
* More cleanup and references to docker removed
* Cleanup
* Comments
* Fixed tests
* Fix GitHub Actions workflow for standalone Python architecture
- Install requirements-dev.txt for pytest and testing dependencies
- Remove Docker setup from simulation tests (now standalone)
- Simplify linting job to use requirements-dev.txt
- Update simulation tests to run directly without Docker
Fixes unit test failures in CI due to missing pytest dependency.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* Remove simulation tests from GitHub Actions
- Removed simulation-tests job that makes real API calls
- Keep only unit tests (mocked, no API costs) and linting
- Simulation tests should be run manually with real API keys
- Reduces CI costs and complexity
GitHub Actions now only runs:
- Unit tests (569 tests, all mocked)
- Code quality checks (ruff, black)
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* Fixed tests
* Fixed tests
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Co-authored-by: Claude <noreply@anthropic.com>
