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Documentation Index

Fetch the complete documentation index at: https://docs.getcore.me/llms.txt

Use this file to discover all available pages before exploring further.

Core Zed

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Prerequisites

  • Zed editor (latest version recommended)
  • CORE account (sign up at app.getcore.me)

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Step 1: Add CORE MCP Server

  1. Open Agent Panel Settings:
    • Press Cmd+Shift+I or Cmd+L (macOS) or Ctrl+Shift+I (Linux/Windows) to open Agent Panel
    • Click the Settings icon in the Agent Panel Or use Command Palette: agent: open settings MCP settings Zed
  2. Add Custom MCP Server:
    • In the Agent Panel Settings, click “Add Custom Server” button
    • A configuration modal will appear
  3. Configure CORE MCP Server:
Enter below code in configuraiton file and click on Add server button 
{
  /// The name of your MCP server
  "core-memory": {
    "command": "npx",
    "args": ["-y", "mcp-remote", "https://app.getcore.me/api/v1/mcp?source=Zed"]
  }
}

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Step 2: Authenticate with CORE

  • After adding the CORE MCP server Zed will prompt you to open a website for authentication.
  • When the authentication window opens, Grant Zed permission to access your CORE memory

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Step 3: Verify Connection

  • Once authenticated CORE Memory will show in the MCP server connected Core Cursor
Create AGENTS.md in your project root (or append if it already exists) and add the memory protocol from the Memory Rules guide. Use this frontmatter for AGENTS.md: 
---
trigger: always_on
---
Then paste the memory protocol content below it.

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Option 2: Using Zed Rules

Alternatively, you can use Zed’s native Rules Library feature:
  1. Open the Rules Library:
    • Open the Agent Panel
    • Click the Agent menu (...) in the top right corner
    • Select Rules... from the dropdown
  2. Use Cmd + N to create new rule and add below instruction: 
---
alwaysApply: true
---
I am Zed, an AI coding assistant with access to CORE Memory - a persistent knowledge system that maintains project context across sessions.

**MANDATORY MEMORY OPERATIONS:**

1. **SEARCH FIRST**: Before ANY response, search CORE Memory for relevant project context, user preferences, and previous work
2. **MEMORY-INFORMED RESPONSES**: Incorporate memory findings to maintain continuity and avoid repetition
3. **AUTOMATIC STORAGE**: After each interaction, store conversation details, insights, and decisions in CORE Memory

**Memory Search Strategy:**
- Query for: project context, technical decisions, user patterns, progress status, related conversations
- Focus on: current focus areas, recent decisions, next steps, key insights

**Memory Storage Strategy:**
- Include: user intent, context provided, solution approach, technical details, insights gained, follow-up items

**Response Workflow:**
1. Search CORE Memory for relevant context
2. Integrate findings into response planning
3. Provide contextually aware assistance
4. Store interaction details and insights

**Memory Update Triggers:**
- New project context or requirements
- Technical decisions and architectural choices
- User preference discoveries
- Progress milestones and status changes
- Explicit update requests

**Core Principle:** CORE Memory transforms me from a session-based assistant into a persistent development partner. Always search first, respond with context, and store for continuity.

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What’s Next?

With CORE connected to Zed, your AI assistant conversations will now:
  • Automatically save important context to your CORE memory
  • Retrieve relevant information from previous sessions
  • Maintain continuity across multiple coding sessions
  • Share context with other connected development tools

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Need Help?

Join our Discord community and ask questions in the #core-support channel Our team and community members are ready to help you get the most out of CORE’s memory capabilities.