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sequa-ai/sequa-mcp

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๐Ÿ“‡ โ˜๏ธ ๐Ÿง ๐ŸŽ ๐ŸชŸ - Stop stitching context for Copilot and Cursor. With Sequa MCP, your AI tools know your entire codebase and docs out of the box.

S

MCP

sequa-ai/sequa-mcp

Added 1 June 2026

Overview

Sequia MCP is an open-source TypeScript tool that provides a Model Context Protocol server for AI coding assistants like GitHub Copilot and Cursor. It automatically surfaces your entire codebase and documentation to these tools, eliminating the need to manually paste context.

Best for

Best for
Developers who want their AI coding assistants to automatically understand the full codebase and docs.

Use cases

  • Give Copilot full codebase awareness without manual context stitching
  • Integrate with Cursor for context-rich code suggestions
  • Automatically include project documentation in AI prompts

Notes

Sequia MCP is an open-source TypeScript tool that provides a Model Context Protocol server for AI coding assistants like GitHub Copilot and Cursor. It automatically surfaces your entire codebase and documentation to these tools, eliminating the need to manually paste context.

20 stars on GitHub. Last updated 2025-12-09. Licensed MIT.

Use cases

  • Give Copilot full codebase awareness without manual context stitching
  • Integrate with Cursor for context-rich code suggestions
  • Automatically include project documentation in AI prompts

Pros

  • Saves time by automating context delivery to AI assistants
  • Works with multiple popular AI coding tools (Copilot, Cursor)
  • Open-source and written in TypeScript for easy customization

Cons

  • Requires initial setup and configuration per project or IDE
  • Limited to AI tools that support the Model Context Protocol
  • Small community (20 GitHub stars) may mean slower support or updates

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Saves time by automating context delivery to AI assistants
  • Works with multiple popular AI coding tools (Copilot, Cursor)
  • Open-source and written in TypeScript for easy customization

Cons

  • Requires initial setup and configuration per project or IDE
  • Limited to AI tools that support the Model Context Protocol
  • Small community (20 GitHub stars) may mean slower support or updates