punkpeye/awesome-mcp-servers
May 2025 – May 2025
1 Month active
Languages Used
Markdown
Technical Skills
AI integrationAPI integrationGitdocumentationevent managementlocalization
Arley Daniel Peter
PROFILE
Arley Daniel Peter
Worked on expanding the Cal.com MCP server integration documentation within the punkpeye/awesome-mcp-servers repository, focusing on clarifying event types, appointment handling, and scheduling data, as well as supporting LLM-based calendar data. The approach emphasized comprehensive, multilingual documentation, adding and updating README files in English, Portuguese (pt-BR), Japanese, Korean, and Chinese variants to improve accessibility and onboarding for global developers. Leveraged skills in API integration, AI integration, and Git to ensure documentation accuracy and maintainability. The work addressed localization readiness and integration reliability, providing clear technical guidance for developers integrating Cal.com MCP servers into diverse environments.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
7Total
Bugs
0
Commits
7
Features
1
Lines of code
0
Activity Months1
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1220 peopleSame Organization
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Work History
May 2025
7 Commits • 1 Features
May 1, 2025May 2025: Expanded Cal.com MCP server integration documentation for punkpeye/awesome-mcp-servers, covering event types, appointments, scheduling data, and LLM-based calendar data support, with multi-language coverage (English, Portuguese -pt-BR, Japanese, Korean) and Chinese variants. Updated core README and locale READMEs to improve developer onboarding and integration reliability.
7 Commits • 1 Features
May 1, 2025May 2025: Expanded Cal.com MCP server integration documentation for punkpeye/awesome-mcp-servers, covering event types, appointments, scheduling data, and LLM-based calendar data support, with multi-language coverage (English, Portuguese -pt-BR, Japanese, Korean) and Chinese variants. Updated core README and locale READMEs to improve developer onboarding and integration reliability.
May 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance100.0%
AI Usage54.2%
Skills & Technologies
Programming Languages
Markdown
Technical Skills
AI integrationAPI integrationGitdocumentationevent managementlocalizationreadme management
Repositories Contributed To
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