Yocoolab/mcp-server
by Various
Pin visual feedback on any live web page and send it to Claude Code, Cursor or your AI agent.
MCP
Yocoolab/mcp-server
Added 8 Sept 2026
Overview
Yocoolab/mcp-server is a TypeScript-based MCP server that lets users pin visual feedback directly on any live web page and send that feedback to AI agents such as Claude Code or Cursor. It provides a way to attach visual annotations to a running site and transmit them to supported coding tools for context.
Best for
Best for
Developers using Claude Code or Cursor who want to give visual feedback to their AI agent.
Use cases
- Pin UI issues on a live page for Claude Code to address
- Send visual annotations to Cursor during frontend development
- Provide visual context to an AI agent for debugging or design review
Notes
Yocoolab/mcp-server is a TypeScript-based MCP server that lets users pin visual feedback directly on any live web page and send that feedback to AI agents such as Claude Code or Cursor. It provides a way to attach visual annotations to a running site and transmit them to supported coding tools for context.
1 stars on GitHub. Last updated 2026-09-07. Licensed Apache-2.0.
Use cases
- Pin UI issues on a live page for Claude Code to address
- Send visual annotations to Cursor during frontend development
- Provide visual context to an AI agent for debugging or design review
Pros
- Enables direct visual feedback on live web pages
- Integrates with popular AI coding tools like Claude Code and Cursor
- Written in TypeScript, offering type safety and maintainability
Cons
- Very low star count (1) indicates minimal community validation
- Limited to the described integration path with specific AI agents
- No evidence of extensive testing or documentation beyond the basic description
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Enables direct visual feedback on live web pages
- Integrates with popular AI coding tools like Claude Code and Cursor
- Written in TypeScript, offering type safety and maintainability
Cons
- Very low star count (1) indicates minimal community validation
- Limited to the described integration path with specific AI agents
- No evidence of extensive testing or documentation beyond the basic description
Pairs with
Other entries in the index that connect to this one. Click through to see the chain.
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