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.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Fix ModelContext constructor call in consensus tool (remove invalid parameters)
- Refactor temperature pattern matching for better readability per code review
- All tests now passing (799/799 passed)
- Fix consensus tool hardcoded temperature=0.2 bypassing model capabilities
- Add intelligent temperature inference for unknown custom models
- Support multi-model collaboration (O3, Gemini, Claude, Mistral, DeepSeek)
- Only OpenAI O-series and DeepSeek reasoner models reject temperature
- Most reasoning models (Gemini Pro, Claude, Mistral) DO support temperature
- Comprehensive logging for temperature decisions and user guidance
Resolves: https://github.com/BeehiveInnovations/zen-mcp-server/issues/245
Disabled secondary tools by default (for new installations), updated README.md with instructions on how to enable these in .env
run-server.sh now displays disabled / enabled tools (when DISABLED_TOOLS is set)
fix: Minor tweaks to prompts
fix: Improved support for smaller models that struggle with strict structured JSON output
Rearranged reasons to use the MCP above quick start (collapsed)
This commit updates all references to Claude Opus 4 and Sonnet 4 to their newer 4.1 versions throughout the codebase.
The changes include:
- Updating model names in `conf/custom_models.json` and `providers/dial.py`.
- Updating aliases and descriptions to match the new model versions.
- Updating `.env.example` to reflect the new model names.
- Updating all relevant test suites to use the new model names and ensure all tests pass.
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
- Update arguments parameter type hint from Optional[dict] to Optional[dict[str, Any]] in workflow_mixin.py
- Ensures consistency with BaseTool and improves static analysis and code clarity
- No functional changes, only type annotation improvement
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
- Add LOCALE-based localization support to all workflow tools
- Harmonize method signatures for prepare_prompt and _prepare_file_content_for_prompt
- Remove obsolete methods and clarify comments
- Ensure consistent behavior between SimpleTool and WorkflowTool
Added new confidence values (very_high, almost_certain) to all workflow tools
to provide more granular confidence tracking. Updated enum declarations in:
- analyze.py, codereview.py, debug.py, precommit.py, secaudit.py, testgen.py
- Updated debug.py's get_required_actions to handle new confidence values
- All tools now use consistent 7-value confidence scale
- refactor.py kept its unique scale (exploring/incomplete/partial/complete)
Also fixed model thinking configuration:
- Added very_high and almost_certain to MODEL_THINKING_PREFERENCES
- Set medium thinking for very_high, high thinking for almost_certain
- Updated prompts to clarify certain means 100% local confidence
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
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
## Description
This PR implements a new [DIAL](https://dialx.ai/dial_api) (Data & AI Layer) provider for the Zen MCP Server, enabling unified access to multiple AI models through the DIAL API platform. DIAL provides enterprise-grade AI model access with deployment-specific routing similar to Azure OpenAI.
## Changes Made
- [x] Added support of atexit:
- Ensures automatic cleanup of provider resources (HTTP clients, connection pools) on server shutdown
- Fixed bug using ModelProviderRegistry.get_available_providers() instead of accessing private _providers
- Works with SIGTERM/Ctrl+C for graceful shutdown in both development and containerized environments
- [x] Added new DIAL provider (`providers/dial.py`) inheriting from `OpenAICompatibleProvider`
- [x] Updated server.py to register DIAL provider during initialization
- [x] Updated provider registry to include DIAL provider type
- [x] Implemented deployment-specific routing for DIAL's Azure OpenAI-style endpoints
- [x] Implemented performance optimizations:
- Connection pooling with httpx for better performance
- Thread-safe client caching with double-check locking pattern
- Proper resource cleanup with `close()` method
- [x] Added comprehensive unit tests with 16 test cases (`tests/test_dial_provider.py`)
- [x] Added DIAL configuration to `.env.example` with documentation
- [x] Added support for configurable API version via `DIAL_API_VERSION` environment variable
- [x] Added DIAL model restrictions support via `DIAL_ALLOWED_MODELS` environment variable
### Supported DIAL Models:
- OpenAI models: o3, o4-mini (and their dated versions)
- Google models: gemini-2.5-pro, gemini-2.5-flash (including search variant)
- Anthropic models: Claude 4 Opus/Sonnet (with and without thinking mode)
### Environment Variables:
- `DIAL_API_KEY`: Required API key for DIAL authentication
- `DIAL_API_HOST`: Optional base URL (defaults to https://core.dialx.ai)
- `DIAL_API_VERSION`: Optional API version header (defaults to 2025-01-01-preview)
- `DIAL_ALLOWED_MODELS`: Optional comma-separated list of allowed models
### Breaking Changes:
- None
### Dependencies:
- No new dependencies added (uses existing OpenAI SDK with custom routing)
* feat: Update Claude model references from v3 to v4
- Update model configurations from claude-3-opus to claude-4-opus
- Update model configurations from claude-3-sonnet to claude-4-sonnet
- Maintain backward compatibility through existing aliases (opus, sonnet, claude)
- Update provider registry preferred models list
- Update all test cases and assertions to reflect new model names
- Update documentation and examples consistently across all files
- Add Claude 4 model support while preserving existing functionality
Files modified: 15 (config, docs, providers, tests, tools)
Pattern: Systematic claude-3-* → claude-4-* model reference migration
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* PR feedback: changed anthropic/claude-4-opus -> anthropic/claude-opus-4 and anthropic/claude-4-haiku -> anthropic/claude-3.5-haiku
* changed anthropic/claude-4-sonnet -> anthropic/claude-sonnet-4
* PR feedback removed specific model from test mock
* PR feedback removed base.py
---------
Co-authored-by: Omry Nachman <omry@wix.com>
Co-authored-by: Claude <noreply@anthropic.com>
Description: This feature adds support for UTF-8 encoding in JSON responses, allowing for proper handling of special characters and emojis.
- Implement unit tests for UTF-8 encoding in various model providers including Gemini, OpenAI, and OpenAI Compatible.
- Validate UTF-8 support in token counting, content generation, and error handling.
- Introduce tests for JSON serialization ensuring proper handling of French characters and emojis.
- Create tests for language instruction generation based on locale settings.
- Validate UTF-8 handling in workflow tools including AnalyzeTool, CodereviewTool, and DebugIssueTool.
- Ensure that all tests check for correct UTF-8 character preservation and proper JSON formatting.
- Add integration tests to verify the interaction between locale settings and model responses.
