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Add peer review agents to AI coding workflows for review, debugging, and collaboration.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "peer-agents-mcp" yet — see the docs or source repo.
Use peer-agents-mcp to call Grok and Antigravity as peer reviewers for this Python API code. Focus on readability, potential bugs, edge cases, and security risks, then summarize agreements and disagreements.
A consolidated code review report with key issues, improvement suggestions, and a comparison of agent opinions.
I am seeing intermittent timeout errors in a Node.js service. Through peer-agents-mcp, have Grok and Antigravity analyze the logs, infer root causes, propose validation steps, and recommend the highest-priority fix.
A debugging summary with ranked root causes, validation methods, fix recommendations, and next steps.
Use peer-agents-mcp to bring in Grok and Antigravity to plan a new feature: break down tasks, identify technical risks, suggest a testing strategy, and produce an actionable implementation plan.
A structured implementation plan with task breakdowns, risk list, testing suggestions, and execution order.
Review code and execute engineering tasks through natural-language AI workflows.
Orchestrate multi-agent workflows with parallel tasks, pipelines, scheduling, and peer review.
Generate focused, actionable code reviews from Git diffs and source context.
Get intelligent, context-aware code reviews and improvement suggestions with MCP.
Connect coding agents to multiple models for in-chat consultation and code review.
Review code diffs for bugs, security risks, and generate fixes.