
Radoslav Klic developed and maintained the keboola/mcp-server repository, delivering a robust backend platform for configuration and data management. Over seven months, he engineered features such as async API clients, partial configuration updates using JSONPath, and unified tooling for metadata and description management. His technical approach emphasized code quality, test automation with Pytest, and disciplined release management, ensuring stable deployments and maintainable code. Leveraging Python, FastAPI, and SQL, Radoslav refactored core components for consistency, improved error handling, and streamlined integration with cloud services like BigQuery. His work demonstrated depth in backend architecture, configuration workflows, and continuous integration practices.

Month: 2025-10 focused on advancing the keboola/mcp-server configuration workflow by delivering targeted tooling enhancements, reliability improvements, API simplifications, and release coordination. The work improves configuration management reliability, traceability, and deployment velocity, while aligning tests and documentation with new behavior.
Month: 2025-10 focused on advancing the keboola/mcp-server configuration workflow by delivering targeted tooling enhancements, reliability improvements, API simplifications, and release coordination. The work improves configuration management reliability, traceability, and deployment velocity, while aligning tests and documentation with new behavior.
September 2025 monthly summary for keboola/mcp-server: Implemented environment modernization and dependency updates to stabilize MCP server, clarified component_id handling, and introduced partial configuration updates via JSONPath, with strengthened tests and documentation. These workstreams improved security, reliability, and developer productivity.
September 2025 monthly summary for keboola/mcp-server: Implemented environment modernization and dependency updates to stabilize MCP server, clarified component_id handling, and introduced partial configuration updates via JSONPath, with strengthened tests and documentation. These workstreams improved security, reliability, and developer productivity.
August 2025: Focused MCP server improvements delivering concurrent transport capabilities, a unified description tooling, and reinforced release discipline. These changes reduce integration friction, improve runtime efficiency, and streamline release management, delivering measurable business value and stronger platform foundations.
August 2025: Focused MCP server improvements delivering concurrent transport capabilities, a unified description tooling, and reinforced release discipline. These changes reduce integration friction, improve runtime efficiency, and streamline release management, delivering measurable business value and stronger platform foundations.
This month focused on delivering a major MCP Server release (1.15.0) and ensuring packaging and dependencies were updated to support the new functionality. The work establishes a stable foundation for upcoming features and improves production readiness through careful versioning, dependency management, and release engineering.
This month focused on delivering a major MCP Server release (1.15.0) and ensuring packaging and dependencies were updated to support the new functionality. The work establishes a stable foundation for upcoming features and improves production readiness through careful versioning, dependency management, and release engineering.
June 2025 | keboola/mcp-server monthly summary Key features delivered: - Config Creation API and metadata support: added client method to create configs and attach metadata for created configs. Commits: 599884dc2679bdd0758de3ca7959fc013451fc6d; 6a039770669156fc28ac049642c3cf01124bcb76 - Config Update API and metadata: added metadata for updated configs, tests for update component root configuration, and improvements to metadata key handling. Commits: e07fc474422278781965df45a2df139b1386445d; 0227ad7722c7a5b125ec4f52994ce5376f31a68c; 2e079f83b248d1d35a883ae2a2e3fddec8ab5cae - Storage Client enhancements: add component_list method to storage client and related client improvements for bucket/table metadata and SQL query. Commits: 8161e1c049ff5efd7f76c13afac1bcefba97f68e; d79a3192769101568d511970ad26b0af15924b58; 05582fec3a110a0ce310f97386ccb9ab0c49c115; b2300c59caaafcc0aec0114faea86924dba5b740; 903f4db608b921c83fa1d62ac49b10220a81bfad; 53471824327d2ec0c2cf4633c3046a6dade709d0; 48a56872030314a843ea5b0ca7031917063448d5 - BigQuery query integration: use API endpoint for running BigQuery queries; update README; bump version. Commits: 81e07d17dd1e6761add68616cfcd1d1797f46d66; 04df72863e974be29d8fe3e97620d402ab8ef455; fb348e9765460b6f3d82f19ffb9b8e540b322837 - Release readiness and versioning: Release 1.0.0 and related version updates. Commits: a71b0c6412dd182f9743b3f7b8e77007a5fc588e; 81e07d17dd1e6761add68616cfcd1d1797f46d66; cf419d4ca9af9d3a4b84069deedc4bf22728ac3b Major bugs fixed: - Double deletion of configs (commit 8a9b8872ef800b6de6f2b3a4481efbfbf708867a) Overall impact and accomplishments: - Accelerated config lifecycle with reliable create/update flows and metadata support, improving traceability and rollout safety. - Safer operations with fix for double-delete of configs. - Expanded storage client capabilities (component discovery via component_list, bucket/table metadata, SQL query) enabling more automation and observability. - End-to-end readiness for release cycles with consistent versioning, documentation improvements, and BigQuery integration. - Strengthened testing posture via integration tests, improved assertions, and encapsulated API calls for stability. Technologies/skills demonstrated: - API design and client ergonomics, metadata handling, test-driven development, integration testing, logging and docstrings improvements, and disciplined versioning and release management.
June 2025 | keboola/mcp-server monthly summary Key features delivered: - Config Creation API and metadata support: added client method to create configs and attach metadata for created configs. Commits: 599884dc2679bdd0758de3ca7959fc013451fc6d; 6a039770669156fc28ac049642c3cf01124bcb76 - Config Update API and metadata: added metadata for updated configs, tests for update component root configuration, and improvements to metadata key handling. Commits: e07fc474422278781965df45a2df139b1386445d; 0227ad7722c7a5b125ec4f52994ce5376f31a68c; 2e079f83b248d1d35a883ae2a2e3fddec8ab5cae - Storage Client enhancements: add component_list method to storage client and related client improvements for bucket/table metadata and SQL query. Commits: 8161e1c049ff5efd7f76c13afac1bcefba97f68e; d79a3192769101568d511970ad26b0af15924b58; 05582fec3a110a0ce310f97386ccb9ab0c49c115; b2300c59caaafcc0aec0114faea86924dba5b740; 903f4db608b921c83fa1d62ac49b10220a81bfad; 53471824327d2ec0c2cf4633c3046a6dade709d0; 48a56872030314a843ea5b0ca7031917063448d5 - BigQuery query integration: use API endpoint for running BigQuery queries; update README; bump version. Commits: 81e07d17dd1e6761add68616cfcd1d1797f46d66; 04df72863e974be29d8fe3e97620d402ab8ef455; fb348e9765460b6f3d82f19ffb9b8e540b322837 - Release readiness and versioning: Release 1.0.0 and related version updates. Commits: a71b0c6412dd182f9743b3f7b8e77007a5fc588e; 81e07d17dd1e6761add68616cfcd1d1797f46d66; cf419d4ca9af9d3a4b84069deedc4bf22728ac3b Major bugs fixed: - Double deletion of configs (commit 8a9b8872ef800b6de6f2b3a4481efbfbf708867a) Overall impact and accomplishments: - Accelerated config lifecycle with reliable create/update flows and metadata support, improving traceability and rollout safety. - Safer operations with fix for double-delete of configs. - Expanded storage client capabilities (component discovery via component_list, bucket/table metadata, SQL query) enabling more automation and observability. - End-to-end readiness for release cycles with consistent versioning, documentation improvements, and BigQuery integration. - Strengthened testing posture via integration tests, improved assertions, and encapsulated API calls for stability. Technologies/skills demonstrated: - API design and client ergonomics, metadata handling, test-driven development, integration testing, logging and docstrings improvements, and disciplined versioning and release management.
May 2025 monthly summary for keboola/mcp-server: Core backend improvements focused on async workflows, test reliability, code quality, and production hygiene. Delivered measurable business value by reducing runtime risks, increasing test confidence, and enabling faster feature delivery.
May 2025 monthly summary for keboola/mcp-server: Core backend improvements focused on async workflows, test reliability, code quality, and production hygiene. Delivered measurable business value by reducing runtime risks, increasing test confidence, and enabling faster feature delivery.
April 2025 (2025-04) delivered a foundational refresh to keboola/mcp-server, focusing on a robust, maintainable API client stack and strengthened testing practices. Key architectural work centralized API interaction through a new Base Client Class and a refactored API Client Core, enabling consistent behavior across endpoints. The testing layer was modernized by migrating to pytest-mocker fixtures and standardizing mocking usage and formatting. In addition, targeted code quality improvements (naming conventions and type annotations) and minor housekeeping across the repo were completed to reduce cognitive load and enable faster iteration. Major bug fixes included a repository clean-up that removed spurious files (including coverage.xml) and a comprehensive AI service fixes and maintenance effort (argument handling, imports/renames, formatting, tests, root_url usage, and MCP merge adjustments) that improved reliability of AI-related workflows and MCP integration.
April 2025 (2025-04) delivered a foundational refresh to keboola/mcp-server, focusing on a robust, maintainable API client stack and strengthened testing practices. Key architectural work centralized API interaction through a new Base Client Class and a refactored API Client Core, enabling consistent behavior across endpoints. The testing layer was modernized by migrating to pytest-mocker fixtures and standardizing mocking usage and formatting. In addition, targeted code quality improvements (naming conventions and type annotations) and minor housekeeping across the repo were completed to reduce cognitive load and enable faster iteration. Major bug fixes included a repository clean-up that removed spurious files (including coverage.xml) and a comprehensive AI service fixes and maintenance effort (argument handling, imports/renames, formatting, tests, root_url usage, and MCP merge adjustments) that improved reliability of AI-related workflows and MCP integration.
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