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๐ŸฅŠ reShapr vs Official GitHub MCP: What happens when you optimize tool calls for AI agents? In our latest benchmark, we put the official @github.com Model Context Protocol (MCP) tools head-to-head with a purpose-built reShapr action to measure pull request velocity on microsoft/vscode. The results?

reshapr.ioreShapr vs Official GitHub MCP ๐ŸฅŠ | reShaprA live, curl-reproducible benchmark showing how reShapr turns a 31-call GitHub MCP pull-request workflow into one predictable agent action, then trims the response further with output filters andโ€ฆ

โŒ Official @github.com MCP: 31 separate tool calls (1 list + 30 follow-ups) โœ… reShapr: 1 predictable, task-shaped agent action By shaping the API exactly to the agent's needs, we eliminated unnecessary API loops, resulting in a ๐Ÿต๐Ÿณ.๐Ÿฎ% ๐—ฟ๐—ฒ๐—ฑ๐˜‚๐—ฐ๐˜๐—ถ๐—ผ๐—ป ๐—ถ๐—ป ๐—ฟ๐—ฒ๐˜€๐—ฝ๐—ผ๐—ป๐˜€๐—ฒ ๐—ฏ๐˜†๐˜๐—ฒ๐˜€ and a drastic improvement in latency.

reshapr.ioreShapr vs Official GitHub MCP ๐ŸฅŠ | reShaprA live, curl-reproducible benchmark showing how reShapr turns a 31-call GitHub MCP pull-request workflow into one predictable agent action, then trims the response further with output filters andโ€ฆ

Stop context overload and make your AI agents predictable and reproducible. Check out the full benchmark and methodology here: ๐Ÿ‘‰ reshapr.io/blog/reshapr... #AI #AgenticAI #MCP #GitHub #LLM @aaif.io @linuxfoundation.org ๐Ÿ™Œ

reshapr.ioreShapr vs Official GitHub MCP ๐ŸฅŠ | reShaprA live, curl-reproducible benchmark showing how reShapr turns a 31-call GitHub MCP pull-request workflow into one predictable agent action, then trims the response further with output filters andโ€ฆ

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