---
title: REST API Server
description: Reach every Mem0 OSS capability through a FastAPI-powered REST layer.
icon: "code"
---
The Mem0 REST API server exposes every OSS memory operation over HTTP. Run it alongside your stack to add, search, update, and delete memories from any language that speaks REST.
**You’ll use this when…**
- Your services already talk to REST APIs and you want Mem0 to match that style.
- Teams on languages without the Mem0 SDK still need access to memories.
- You plan to explore or debug endpoints through the built-in OpenAPI page at `/docs`.
Add your own authentication and HTTPS before exposing the server to anything beyond your internal network. The default image does not include auth.
---
## Feature
- **CRUD endpoints:** Create, retrieve, search, update, delete, and reset memories by `user_id`, `agent_id`, or `run_id`.
- **Status health check:** Access base routes to confirm the server is online.
- **OpenAPI explorer:** Visit `/docs` for interactive testing and schema reference.
---
## Configure it
### Run with Docker Compose (development)
1. Create `server/.env` with your keys:
```bash
OPENAI_API_KEY=your-openai-api-key
```
2. Start the stack:
```bash
cd server
docker compose up
```
3. Reach the API at `http://localhost:8888`. Edits to the server or library auto-reload.
### Run with Docker
```bash
docker pull mem0/mem0-api-server
```
```bash
docker build -t mem0-api-server .
```
1. Create a `.env` file with `OPENAI_API_KEY`.
2. Run the container:
```bash
docker run -p 8000:8000 --env-file .env mem0-api-server
```
3. Visit `http://localhost:8000`.
### Run directly (no Docker)
```bash
pip install -r requirements.txt
uvicorn main:app --reload
```
Use a process manager such as `systemd`, Supervisor, or PM2 when deploying the FastAPI server for production resilience.
The REST server reads the same configuration you use locally, so you can point it at your preferred LLM, vector store, graph backend, and reranker without changing code.
---
## See it in action
### Create and search memories via HTTP
```bash
curl -X POST http://localhost:8000/memories \
-H "Content-Type: application/json" \
-d '{
"messages": [
{"role": "user", "content": "I love fresh vegetable pizza."}
],
"user_id": "alice"
}'
```
Expect a JSON response containing the new memory IDs and events (`ADD`, etc.).
```bash
curl "http://localhost:8000/memories/search?user_id=alice&query=vegetable"
```
### Explore with OpenAPI docs
1. Navigate to `http://localhost:8000/docs`.
2. Pick an endpoint (e.g., `POST /memories/search`).
3. Fill in parameters and click **Execute** to try requests in-browser.
Export the generated `curl` snippets from the OpenAPI UI to bootstrap integration tests.
---
## Verify the feature is working
- Hit the root route and `/docs` to confirm the server is reachable.
- Run a full cycle: `POST /memories` → `GET /memories/{id}` → `DELETE /memories/{id}`.
- Watch server logs for import errors or provider misconfigurations during startup.
- Confirm environment variables (API keys, vector store credentials) load correctly when containers restart.
---
## Best practices
1. **Add authentication:** Protect endpoints with API gateways, proxies, or custom FastAPI middleware.
2. **Use HTTPS:** Terminate TLS at your load balancer or reverse proxy.
3. **Monitor uptime:** Track request rates, latency, and error codes per endpoint.
4. **Version configs:** Keep environment files and Docker Compose definitions in source control.
5. **Limit exposure:** Bind to private networks unless you explicitly need public access.
---
Fine-tune LLMs, vector stores, and graph backends that power the REST server.
See how services call the REST endpoints as part of an automation pipeline.