Merge pull request #30 from sscargal/blogs

Added new blog posts

Author: sscargal

content/en/blog/2025/11/integrating-openai-agent-builder-with-memmachine-mcp-server/featured_image.png

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+---
+title: "Integrating OpenAI Agent Builder with MemMachine MCP Server"
+date: 2025-11-03T17:40:16-06:00
+featured_image: "featured_image.png"
+tags: ["AI Agent", "MCP", "Generative AI", "Agent Memory", "OpenAI", "OpenAI Builder", "featured"]
+author: "Decheng Xu"
+description: "Integrating OpenAI Agent Builder with MemMachine MCP Server is easy with our step-by-step guide."
+aliases:
+---
+
+Integrating OpenAI Agent Builder with the MemMachine MCP server allows your AI agents to store and recall information, effectively giving them memory.
+
+The setup connects your locally hosted MemMachine MCP endpoint with OpenAI’s cloud-based Agent Builder workflow system.
+
+## Prerequisites
+
+Before you begin, ensure the following are ready:
+
+- MemMachine MCP HTTP server running and accessible in a local or remote environment on port 8080 (default).
+- OpenAI account with access to Agent Builder.
+- ngrok or similar tool to expose your local MCP server to the internet.
+
+## Step 1: Start the MemMachine MCP Server
+
+Start your MCP HTTP server with:
+
+```bash
+export MEMORY_CONFIG=/path/to/configuration.yml
+uv run python -m memmachine.server.mcp_http --host 0.0.0.0 --port 8080
+```
+
+Ensure the server is running and accessible.
+
+## Step 2: Open the OpenAI Agent Builder
+
+In your browser, navigate to the OpenAI Agent Builder at https://platform.openai.com/agent-builder. Create a new workflow or open an existing one.
+
+![OpenAI Agent Builder](./openai-agent-builder-new-workflow.png)
+
+## Step 3: Configure MCP Endpoint in Agent Builder
+
+On the workflow canvas, you’ll see a Start node and a default agent block.
+Configure it as follows:
+
+- Name: MemMachineMCP
+- Instructions: You are an intelligent memory assistant powered by MemMachine
+- Model: gpt-5
+- Reasoning Effort: Low
+- Include Chat History: Enabled
+
+![Agent Configuration](./openai-agent-builder-configure-agent.png)
+
+## Step 4: Add MCP Memory Tools
+
+Click '+' next to the agent block to add tools. Search for "MCP" and add the following tools:
+
+![MCP Tools](./openai-agent-builder-add-new-mcp-tools.png)
+
+Then click "+ Server" to add your own connection.
+
+![Add MCP Server](./openai-agent-builder-add-new-server.png)
+
+## Step 5: Configure MCP Server Connection
+
+Run this command if you haven’t started ngrok yet:
+
+```bash
+ngrok http 8080
+```
+
+This command will create a secure tunnel to your local MCP server, providing you with a public URL.
+
+![ngrok MCP configuration](./ngrok-configuration.png)
+
+> Important: Ensure your ngrok URL includes the /mcp/ suffix, for example: `https://abc123.ngrok-free.dev/mcp/`
+
+You’ll now see a form titled “Connect to MCP Server”. Fill it out as follows:
+
+- MCP Endpoint URL: `https://your-ngrok-url.ngrok-free.dev/mcp/`
+- Label: Memmachine_MCP
+- Authentication Type: Custom Headers
+- Custom Headers:
+  - Key: user-id
+  - Value: user
+
+Click "Connect" to save the configuration.
+
+> Note: This `user-id` header is used by MemMachine MCP to associate memory operations (add/search) with a specific user.
+
+![MCP Server Connection](./openai-agent-build-connect-to-an-mcp-server.png)
+
+## Step 6: Approve Tools and Add Server
+
+After connecting, approve the MCP tools to use the newly added server.
+
+- add_memory → Memmachine_MCP
+- search_memory → Memmachine_MCP
+
+Select "Always require approval for all tool calls", then click "Add".
+
+![Approve MCP Tools](./openai-agent-builder-approve-tools.png)
+
+## Step 7: Test the Integration
+
+Once your MemMachine MCP server is added, it will appear under “Tools” for your agent.
+
+Try these example interactions in the Preview panel:
+
+### Add Memory
+
+In the chat input, type:
+
+```text
+I recently bought AirPods Pro 3.
+```
+
+### Search Memory
+
+Then ask:
+
+```text
+What did I buy recently?
+```
+
+You should see the agent successfully storing and retrieving information via the MemMachine MCP server.
+
+## Conclusion
+
+By integrating OpenAI Agent Builder with MemMachine MCP, you empower your AI agents with persistent memory capabilities. This setup allows agents to remember past interactions, enhancing their usefulness and user experience.
+
+## Recommendations
+
+- User ID Consistency: Use consistent user IDs across different sessions to maintain memory continuity.
+  - Why this matters: Keeping a consistent user ID ensures that your memory context stays linked across clients such as Claude Desktop and OpenAI Agent Builder.
+- ngrok: For production use, consider deploying your MCP server on a stable hosting solution rather than relying on ngrok for long-term accessibility.
+- Authentication: Use "Custom Headers" for authentication to easily manage user identities. In the future, OAuth support will be added for enhanced security.