The UTC constant was added in Python 3.11. Changed to use
timezone.utc which is available in Python 3.10+.
Fixed ImportError: cannot import name 'UTC' from 'datetime'
Replace outdated text-embedding-ada-002 with the newer, more efficient
text-embedding-3-small model as the default embedder. The new model
offers better performance and is more cost-effective.
Updated:
- config/config.yaml: Changed default model
- README.md: Updated documentation to reflect new default
Since the MCP server no longer supports SSE transport, removed the
mention of SSE from the mcp-remote description. The server only
uses HTTP transport.
Addresses review comment on line 514
- Shorten Kuzu database description to be more concise
- Update Ollama model example to use 'gpt-oss:120b'
- Restore Azure OpenAI environment variables documentation
- Remove implementation details from Docker section (irrelevant to container users)
- Clarify mcp-remote supports both HTTP and SSE transports
Addresses review comments #1-7 on the PR
- Add comprehensive features list including all supported databases, LLM providers, and transports
- Document Kuzu as the default database with explanation of its benefits and archived status
- Add detailed instructions for running with different databases (Kuzu, Neo4j, FalkorDB)
- Update transport references from SSE to HTTP (default transport)
- Add database-specific Docker Compose instructions
- Update MCP client configurations to use /mcp/ endpoint
- Clarify prerequisites to reflect optional nature of external databases
- Add detailed database configuration examples for all supported backends
- Replace try-except-pass with contextlib.suppress in test_async_operations.py
- Replace try-except-pass with contextlib.suppress in test_fixtures.py
- Fixes ruff SIM105 linting errors
- Replace bare except with except Exception
- Remove unused imports and variables
- Fix type hints to use modern syntax
- Apply ruff formatting for line length
- Ensure all tests pass linting checks
- Add dotenv loading support in test runner
- Fix duplicate os import issue
- Improve prerequisite checking with helpful hints
- Update error messages to guide users
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Co-Authored-By: Claude <noreply@anthropic.com>
* conductor-checkpoint-start
* conductor-checkpoint-msg_01B1n4yHQFoVrWWdKcqPQ4Qa
* conductor-checkpoint-msg_01LS1v8ok5qtzAofv1TFRDHt
* conductor-checkpoint-msg_01H5pxrRKDpizF4wv1irnvRz
* conductor-checkpoint-msg_01EFo2gQBKSFkGcJoJ4bUWNS
* conductor-checkpoint-msg_01QW92pnqMv17sfV4CxFKn7Y
* conductor-checkpoint-msg_01VqPRMaBRGpBf9E8sdpPeFa
* Fix critical issues in MCP server release workflow
- Fix Docker tag format: use version only (0.4.0) instead of mcp-v0.4.0
- Add Python 3.11 setup for tomllib compatibility
- Add workflow_dispatch trigger for testing without creating tags
- Add conditional push logic for manual testing
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Co-Authored-By: Claude <noreply@anthropic.com>
* Remove workflow_dispatch trigger from MCP server release
Simplify workflow to only trigger on mcp-v*.*.* tags.
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Co-Authored-By: Claude <noreply@anthropic.com>
* conductor-checkpoint-msg_019AX8ymwf9eec2KF979CJCM
* conductor-checkpoint-msg_01LMofTLUNkicSq5vpFmsd1C
* Add semantic version validation to MCP server release
Validate tag follows X.Y.Z format before processing.
Rejects malformed tags like mcp-v1.0 or mcp-v1.0.0.0.
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Co-Authored-By: Claude <noreply@anthropic.com>
* conductor-checkpoint-msg_01Ndj59qcprSNRfe3vuciwwA
* conductor-checkpoint-msg_01PmA8bfCLKv7yHiaBz2MypS
---------
Co-authored-by: Claude <noreply@anthropic.com>
- Use simplified format matching uvicorn's default (LEVEL message)
- Remove timestamps from custom logger format
- Suppress verbose MCP and uvicorn access logs
- Improve readability of server startup output
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Co-Authored-By: Claude <noreply@anthropic.com>
- Remove incorrect /status endpoint reference
- Update logging to show correct MCP endpoint at /mcp/
- Align with FastMCP documentation standards
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Co-Authored-By: Claude <noreply@anthropic.com>
- Added comprehensive logging showing exact URLs to access the MCP server
- Display localhost instead of 0.0.0.0 for better usability
- Show MCP endpoint, transport type, and status endpoint information
- Added visual separators to make server info stand out in logs
This helps users understand exactly how to connect to the MCP server
and troubleshoot connection issues.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Changed hardcoded default in schema.py from gpt-4o to gpt-4.1
- Fixed default config path to look in config/config.yaml relative to mcp_server directory
- This ensures the server uses gpt-4.1 as the default model everywhere
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Changed the default LLM model from gpt-4o-mini to gpt-4.1 as requested.
This is the latest GPT-4 series model.
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Co-Authored-By: Claude <noreply@anthropic.com>
Changed the default LLM model from gpt-4o to gpt-4o-mini across all
configuration files for better cost efficiency while maintaining quality.
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Co-Authored-By: Claude <noreply@anthropic.com>
- Changed default transport to 'http' as SSE is deprecated
- Updated all configuration files to use HTTP transport
- Updated Docker compose commands to use HTTP transport
- Updated comments to reflect HTTP transport usage
This change ensures the MCP server uses the recommended HTTP transport
instead of the deprecated SSE transport.
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Co-Authored-By: Claude <noreply@anthropic.com>
- Fix API key detection: Remove hardcoded OpenAI checks, let factories handle provider-specific validation
- Fix .env file loading: Search for .env in mcp_server directory first
- Change default transport to SSE for broader compatibility (was stdio)
- Add proper error handling with warnings for failed client initialization
- Model already defaults to gpt-4o as requested
These changes ensure the MCP server properly loads API keys from .env files
and creates the appropriate LLM/embedder clients based on configuration.
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Co-Authored-By: Claude <noreply@anthropic.com>
This is a major refactoring of the MCP Server to support multiple providers
through a YAML-based configuration system with factory pattern implementation.
## Key Changes
### Architecture Improvements
- Modular configuration system with YAML-based settings
- Factory pattern for LLM, Embedder, and Database providers
- Support for multiple database backends (Neo4j, FalkorDB, KuzuDB)
- Clean separation of concerns with dedicated service modules
### Provider Support
- **LLM**: OpenAI, Anthropic, Gemini, Groq
- **Embedders**: OpenAI, Voyage, Gemini, Anthropic, Sentence Transformers
- **Databases**: Neo4j, FalkorDB, KuzuDB (new default)
- Azure OpenAI support with AD authentication
### Configuration
- YAML configuration with environment variable expansion
- CLI argument overrides for runtime configuration
- Multiple pre-configured Docker Compose setups
- Proper boolean handling in environment variables
### Testing & CI
- Comprehensive test suite with unit and integration tests
- GitHub Actions workflows for linting and testing
- Multi-database testing support
### Docker Support
- Updated Docker images with multi-stage builds
- Database-specific docker-compose configurations
- Persistent volume support for all databases
### Bug Fixes
- Fixed KuzuDB connectivity checks
- Corrected Docker command paths
- Improved error handling and logging
- Fixed boolean environment variable expansion
Co-authored-by: Claude <noreply@anthropic.com>
