punkpeye/awesome-mcp-servers
Mar 2026 – Mar 2026
1 Month active
Languages Used
Markdown
Technical Skills
AI integrationAPI managementcloud computingdocumentationreadme management
newageflyfish-max
PROFILE
Newageflyfish-max
During March 2026, Newageflyfish developed and delivered the AI Price Compute Oracle feature for the punkpeye/awesome-mcp-servers repository, enabling real-time cross-provider AI inference pricing to enhance cost visibility and operational efficiency for AI workloads. The technical approach involved integrating AI pricing data from multiple providers into the MCP server architecture, leveraging API management and cloud computing skills. Additionally, Newageflyfish improved project documentation by updating the README in Markdown to include the VolthQ project link, supporting better onboarding and discoverability. The work demonstrated depth in AI integration and robust documentation practices, laying groundwork for future price-management capabilities without reported bugs.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
3
Activity Months1
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Work History
March 2026
2 Commits • 2 Features
Mar 1, 20262026-03 Monthly Summary for punkpeye/awesome-mcp-servers: Delivered the AI Price Compute Oracle feature on the MCP server to enable real-time cross-provider AI inference pricing, improving cost visibility and operational efficiency for AI workloads. Also updated documentation by adding the VolthQ project link to the README to improve discoverability and onboarding. No major bugs reported this month; focus was on feature delivery and documentation. Overall impact: stronger cost governance for AI ops, clearer project context for contributors, and a foundation for broader price-management capabilities. Technologies demonstrated: MCP server architecture, VolthQ integration, real-time pricing data processing, and robust documentation practices.
2 Commits • 2 Features
Mar 1, 20262026-03 Monthly Summary for punkpeye/awesome-mcp-servers: Delivered the AI Price Compute Oracle feature on the MCP server to enable real-time cross-provider AI inference pricing, improving cost visibility and operational efficiency for AI workloads. Also updated documentation by adding the VolthQ project link to the README to improve discoverability and onboarding. No major bugs reported this month; focus was on feature delivery and documentation. Overall impact: stronger cost governance for AI ops, clearer project context for contributors, and a foundation for broader price-management capabilities. Technologies demonstrated: MCP server architecture, VolthQ integration, real-time pricing data processing, and robust documentation practices.
March 2026
Activity
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance100.0%
AI Usage50.0%
Skills & Technologies
Programming Languages
Markdown
Technical Skills
AI integrationAPI managementcloud computingdocumentationreadme management
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