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cg3-llc/prior_mcp

by Various

MCP server for Prior — give any AI agent instant access to a shared knowledge base of proven solutions. Works with Claude Desktop, Cursor, Windsurf, and VS Code.

C

MCP

cg3-llc/prior_mcp

Added 1 June 2026

Overview

MCP server that connects AI agents (Claude Desktop, Cursor, Windsurf, VS Code) to a shared knowledge base of proven solutions. It enables agents to retrieve and apply prior work without manual context setup.

Best for

Best for
Teams using AI coding assistants who want a shared repository of vetted solutions.

Use cases

  • Share verified code examples across team projects.
  • Enable AI assistants to pull from a curated solution repository.
  • Reduce repeat problem-solving by reusing proven patterns.

How to use

Install

npx @cg3/equip prior

Tools exposed

  • prior_search
  • prior_contribute
  • prior_feedback
  • prior_retract
  • prior_status
  • PRIOR_API_KEY
  • PRIOR_ACCESS_TOKEN
  • PRIOR_REFRESH_TOKEN
  • PRIOR_API_URL

Notes

MCP server that connects AI agents (Claude Desktop, Cursor, Windsurf, VS Code) to a shared knowledge base of proven solutions. It enables agents to retrieve and apply prior work without manual context setup.

2 stars on GitHub. Last updated 2026-05-17.

Use cases

  • Share verified code examples across team projects.
  • Enable AI assistants to pull from a curated solution repository.
  • Reduce repeat problem-solving by reusing proven patterns.

Pros

  • Works with multiple popular AI coding tools.
  • Simple JavaScript implementation for easy setup.
  • Centralizes reusable knowledge for agent collaboration.

Cons

  • Low GitHub stars (2) indicates limited community adoption.
  • Requires Prior knowledge base setup and maintenance.
  • Narrow scope: only benefits teams that maintain a solution repository.

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

Pros

  • Works with multiple popular AI coding tools.
  • Simple JavaScript implementation for easy setup.
  • Centralizes reusable knowledge for agent collaboration.

Cons

  • Low GitHub stars (2) indicates limited community adoption.
  • Requires Prior knowledge base setup and maintenance.
  • Narrow scope: only benefits teams that maintain a solution repository.
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