mondaycom/mcp
Jun 2026 – Jun 2026
1 Month active
Languages Used
GraphQLTypeScript
Technical Skills
GraphQLTypeScriptfull stack development
shaygr92
PROFILE
Shaygr92
Developed the AI Column Configuration Toolkit within the mondaycom/mcp repository, enabling automated configuration and removal of AI-driven columns on monday.com boards. Leveraging GraphQL and TypeScript in a full stack context, the work introduced two MCP tools supporting eight distinct AI block types, such as categorization, summarization, and translation. The implementation featured robust validation, explicit input requirements, and comprehensive error handling, including boardId guards and field constraints. A suite of 27 unit tests ensured reliability across all block types and edge cases. The project also included migration to the 2026-10 API version, aligning with the AIMS GraphQL subgraph.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
2,309
Activity Months1
Your Network
114 peopleWork History
June 2026
1 Commits • 1 Features
Jun 1, 2026June 2026: Delivered the AI Column Configuration Toolkit for monday.com Boards within mondaycom/mcp, introducing two MCP tools to configure and remove AI column configurations with support for 8 AI block types. Implemented robust validation, error handling, and a comprehensive unit test suite (27 tests) to ensure reliability across all block types and edge cases. Strengthened security and correctness with boardId guards, explicit input requirements, and field validations. Migrated tooling to the 2026-10 API version, aligning with the AIMS GraphQL subgraph. Result: production-ready automation capabilities for AI-driven board configurations, improved reliability, and a stronger foundation for future AI features.
1 Commits • 1 Features
Jun 1, 2026June 2026: Delivered the AI Column Configuration Toolkit for monday.com Boards within mondaycom/mcp, introducing two MCP tools to configure and remove AI column configurations with support for 8 AI block types. Implemented robust validation, error handling, and a comprehensive unit test suite (27 tests) to ensure reliability across all block types and edge cases. Strengthened security and correctness with boardId guards, explicit input requirements, and field validations. Migrated tooling to the 2026-10 API version, aligning with the AIMS GraphQL subgraph. Result: production-ready automation capabilities for AI-driven board configurations, improved reliability, and a stronger foundation for future AI features.
June 2026
Activity
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Quality Metrics
Correctness100.0%
Maintainability80.0%
Architecture100.0%
Performance80.0%
AI Usage80.0%
Skills & Technologies
Programming Languages
GraphQLTypeScript
Technical Skills
GraphQLTypeScriptfull stack development
Repositories Contributed To
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