> ## 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. # Codex CLI > Connect your Codex CLI to CORE's memory system ### Prerequisites * [Codex CLI](https://codex.so) installed * CORE account - [Sign up at app.getcore.me](https://app.getcore.me) ### Step 1: Configure CORE MCP Server Create or open your Codex configuration file at `~/.codex/config.toml`: ```bash theme={null} # Create config directory if needed mkdir -p ~/.codex # Open config file in your editor code ~/.codex/config.toml -r ``` ### Step 2: Add CORE MCP Configuration **Option 1: URL-based Configuration (Recommended)** Try this simpler configuration first. Add the following to your `config.toml` file: ```toml theme={null} [features] rmcp_client=true [mcp_servers.memory] url = "https://app.getcore.me/api/v1/mcp?source=codex" ``` Then run the login command: ```bash theme={null} codex mcp memory login ``` This will authenticate your Codex CLI with CORE's memory system. **Option 2: API Key Configuration (If Option 1 doesn't work)** If the URL-based configuration doesn't work, use this API key-based configuration: ```toml theme={null} [features] rmcp_client=true [mcp_servers.memory] url = "https://app.getcore.me/api/v1/mcp?source=codex" http_headers = { "Authorization" = "Bearer CORE_API_KEY" } ``` To get your API key: 1. Log into your CORE dashboard at [app.getcore.me](https://app.getcore.me) 2. Navigate to **Settings** (bottom left) CORE Settings 3. Go to **API Key** → **Generate new key** → Name it "codex" Create API Key 4. Copy the generated key and replace `CORE_API_KEY` in your config file Then run: ```bash theme={null} codex mcp memory login ``` ### Step 3: Verify Connection Start Codex CLI and test your setup: 1. **Start Codex CLI** - The CORE memory MCP server should now be available 2. **Test memory storage**: Ask Codex to create a comprehensive summary of your codebase and add it to CORE memory for future reference 3. **Test memory retrieval**: Ask Codex to search your memory for the stored summary ## Enable Automatic Memory Integration (Recommended) To make Codex automatically search and store memories for seamless project continuity: Create `AGENTS.md` in your project root (if it doesn't exist, just append if it already exists): ```bash theme={null} touch AGENTS.md ``` Add the following to `AGENTS.md`: ```markdown theme={null} --- trigger: always_on --- ⚠️ **CRITICAL: READ THIS FIRST - MANDATORY MEMORY PROTOCOL** ⚠️ You are an AI coding assistant with access to CORE Memory - a persistent knowledge system that maintains project context, learnings, and continuity across all coding sessions. ## 🔴 MANDATORY STARTUP SEQUENCE - DO NOT SKIP 🔴 **BEFORE RESPONDING TO ANY USER MESSAGE, YOU MUST EXECUTE THESE TOOLS IN ORDER:** ### STEP 1 (REQUIRED): Search for Relevant Context EXECUTE THIS TOOL FIRST: `memory_search` - Previous discussions about the current topic - Related project decisions and implementations - User preferences and work patterns - Similar problems and their solutions **Additional search triggers:** - User mentions "previously", "before", "last time", or "we discussed" - User references past work or project history - Working on the CORE project (this repository) - User asks about preferences, patterns, or past decisions - Starting work on any feature or bug that might have history **How to search effectively:** - Write complete semantic queries, NOT keyword fragments - Good: `"User's preferences for API design and error handling"` - Bad: `"manoj api preferences"` - Ask: "What context am I missing that would help?" - Consider: "What has the user told me before that I should remember?" ### Query Patterns for Memory Search **Entity-Centric Queries** (Best for graph search): - ✅ GOOD: `"User's preferences for product positioning and messaging"` - ✅ GOOD: `"CORE project authentication implementation decisions"` - ❌ BAD: `"manoj product positioning"` - Format: `[Person/Project] + [relationship/attribute] + [context]` **Multi-Entity Relationship Queries** (Excellent for episode graph): - ✅ GOOD: `"Manoj and Harshith discussions about BFS search implementation"` - ✅ GOOD: `"relationship between entity extraction and recall quality in CORE"` - ❌ BAD: `"manoj harshith bfs"` - Format: `[Entity1] + [relationship type] + [Entity2] + [context]` **Semantic Question Queries** (Good for vector search): - ✅ GOOD: `"What causes BFS search to return empty results? What are the requirements for BFS traversal?"` - ✅ GOOD: `"How does episode graph search improve recall quality compared to traditional search?"` - ❌ BAD: `"bfs empty results"` - Format: Complete natural questions with full context **Concept Exploration Queries** (Good for BFS traversal): - ✅ GOOD: `"concepts and ideas related to semantic relevance in knowledge graph search"` - ✅ GOOD: `"topics connected to hop distance weighting and graph topology in BFS"` - ❌ BAD: `"semantic relevance concepts"` - Format: `[concept] + related/connected + [domain/context]` **Temporal Queries** (Good for recent work): - ✅ GOOD: `"recent changes to search implementation and reranking logic"` - ✅ GOOD: `"latest discussions about entity extraction and semantic relevance"` - ❌ BAD: `"recent search changes"` - Format: `[temporal marker] + [specific topic] + [additional context]` ## 🔴 MANDATORY SHUTDOWN SEQUENCE - DO NOT SKIP 🔴 **AFTER FULLY RESPONDING TO THE USER, YOU MUST EXECUTE THIS TOOL:** ### FINAL STEP (REQUIRED): Store Conversation Memory EXECUTE THIS TOOL LAST: `memory_ingest` Optionally include labelIds array to organize the conversation with workspace labels. ⚠️ **THIS IS NON-NEGOTIABLE** - You must ALWAYS store conversation context as your final action. **What to capture in the message parameter:** From User: - Specific question, request, or problem statement - Project context and situation provided - What they're trying to accomplish - Technical challenges or constraints mentioned From Assistant: - Detailed explanation of solution/approach taken - Step-by-step processes and methodologies - Technical concepts and principles explained - Reasoning behind recommendations and decisions - Alternative approaches discussed - Problem-solving methodologies applied **Include in storage:** - All conceptual explanations and theory - Technical discussions and analysis - Problem-solving approaches and reasoning - Decision rationale and trade-offs - Implementation strategies (described conceptually) - Learning insights and patterns **Exclude from storage:** - Code blocks and code snippets - File contents or file listings - Command examples or CLI commands - Raw data or logs **Quality check before storing:** - Can someone quickly understand project context from memory alone? - Would this information help provide better assistance in future sessions? - Does stored context capture key decisions and reasoning? --- ## Summary: Your Mandatory Protocol 1. **FIRST ACTION**: Execute `memory_search` with semantic query about the user's request 2. **RESPOND**: Help the user with their request 3. **FINAL ACTION**: Execute `memory_ingest` with conversation summary and optional labelIds **If you skip any of these steps, you are not following the project requirements.** ``` ## How It Works Once installed, CORE memory integrates seamlessly with Codex: * **During conversation**: Codex has access to your full memory graph and stored context * **Memory operations**: Use natural language to store and retrieve information across sessions * **Across tools**: Your memory is shared across Codex, Claude Code, Cursor, ChatGPT, and other CORE-connected tools * **Project continuity**: Context persists across all your AI coding sessions ## Troubleshooting **Connection Issues:** * Verify your API key is correct and hasn't expired * Check that the `config.toml` file is properly formatted (valid TOML syntax) * Ensure the Bearer token format is correct: `Bearer YOUR_API_KEY_HERE` * Restart Codex CLI if the connection seems stuck **API Key Issues:** * Make sure you copied the complete API key from CORE dashboard * Try regenerating your API key if authentication fails * Check that the key is active in your CORE account settings ### Need Help? Join our [Discord community](https://discord.gg/dVTC3BmgEq) 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.