feat: Azure OpenAI / Azure AI Foundry support. Models should be defined in conf/azure_models.json (or a custom path). See .env.example for environment variables or see readme. https://github.com/BeehiveInnovations/zen-mcp-server/issues/265
feat: OpenRouter / Custom Models / Azure can separately also use custom config paths now (see .env.example )
refactor: Model registry class made abstract, OpenRouter / Custom Provider / Azure OpenAI now subclass these
refactor: breaking change: `is_custom` property has been removed from model_capabilities.py (and thus custom_models.json) given each models are now read from separate configuration files
fix: restrictions should resolve canonical names for openrouter
fix: tools now correctly return restricted list by presenting model names in schema
fix: tests updated to ensure these manage their expected env vars properly
perf: cache model alias resolution to avoid repeated checks
Adds support for OpenAI's GPT-5-Codex model which uses the new Responses API
endpoint (/v1/responses) instead of the standard Chat Completions API.
Changes:
- Add GPT-5-Codex to MODEL_CAPABILITIES with 400K context, 128K output
- Prioritize GPT-5-Codex for EXTENDED_REASONING tasks
- Add aliases: codex, gpt5-codex, gpt-5-code
- Update tests to expect GPT-5-Codex for extended reasoning
Benefits:
- 40-80% cost savings through Responses API caching
- 3% better performance on coding tasks (SWE-bench)
- Leverages existing dual-API infrastructure
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
- Updated sonnet alias to point to claude-sonnet-4.5 instead of 4.1
- Removed references to deprecated 'claude' alias
- Added sonnet4.1 alias for claude-sonnet-4.1 backwards compatibility
- All 809 tests passing
Adds flexible cassette matching that ignores system prompt changes
for o3 models, preventing CI failures when prompts are updated.
Changes:
- Semantic matching: Only compares model name, user question, and core params
- Ignores: System prompts, conversation memory instructions, metadata
- Prevents cassette breaks when prompts change between code versions
- Added comprehensive tests for semantic matching behavior
- Created maintenance documentation (tests/CASSETTE_MAINTENANCE.md)
This solves the CI failure where o3-pro test cassettes would break
whenever system prompts or conversation memory format changed.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Updated test_supported_models_aliases.py to reflect the removal of self-referencing aliases:
- Removed assertion for "o4-mini" in its own aliases (no longer self-referencing)
- Updated "o3-pro" alias test to use "o3pro" (normalized alias format)
- Fixed alias resolution test for o3pro -> o3-pro
These changes align with the fix for duplicate model listings in listmodels output.
🤖 Generated with [Claude Code](https://claude.ai/code)
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
Fixed runtime bug where _prepare_file_content_for_prompt was called
without required model_context parameter, causing RuntimeError when
processing requests with relevant_files.
- Create ModelContext instance with model_name in _consult_model method
- Pass model_context parameter to _prepare_file_content_for_prompt call
- Add comprehensive regression test to prevent future occurrences
- Maintain consensus tool's blinded design with independent model contexts
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.
- Fix test_resource_loading_success by removing outdated mock targeting non-existent 'files' import
- Simplify resource loading test to validate registry functionality directly
- Add .zen_venv exclusion to ruff and black in code_quality_checks.sh
- All tests now passing (793/793) with clean linting
