core/docs/providers/zed.mdx
Harshith Mullapudi b0e141c2a2 1. fix: delete api key is not working
2. moved docs into main repo
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---
title: "Zed"
description: "Connect your Zed editor to CORE's memory system via MCP"
---
![Core Zed](/images/core-zed.png)
### Prerequisites
- Zed editor (latest version recommended)
- CORE account (sign up at [core.heysol.ai](https://core.heysol.ai))
### 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](/images/add-mcp-zed.png)
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
```json
{
/// The name of your MCP server
"core-memory": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://core.heysol.ai/api/v1/mcp?source=Zed"]
}
}
```
### 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
### Step 3: Verify Connection
- Once authenticated CORE Memory will show in the MCP server connected
![Core Cursor](/images/zed-core-connected.png)
### Step 4: Enable Automatic Memory Search and Ingest in Zed (Recommended)
To make Zed automatically use your CORE memory in conversations:
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:
```text
---
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.
```
## 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
### Need Help?
Join our [Discord community](https://discord.gg/YGUZcvDjUa) 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.