chore: replace local MCP and Smithery with cloud MCP server (#4532)
This commit is contained in:
Saket Aryan
@@ -9,11 +9,48 @@ description: "Connect any AI client to Mem0 using Model Context Protocol for uni
|
||||
|
||||
When building AI applications, memory management often requires manual integration. MCP eliminates this complexity by:
|
||||
|
||||
- **Universal compatibility**: Works with any MCP-compatible client (Claude Desktop, Cursor, custom agents)
|
||||
- **Universal compatibility**: Works with any MCP-compatible client (Claude, Claude Code, Cursor, Windsurf, VS Code, OpenCode)
|
||||
- **Agent autonomy**: AI agents decide when to save, search, or update memories
|
||||
- **Zero infrastructure**: No servers to maintain - Mem0 handles everything
|
||||
- **Zero infrastructure**: No servers to maintain - Mem0's cloud MCP handles everything
|
||||
- **Standardized protocol**: One integration works across all your AI tools
|
||||
|
||||
## Setup
|
||||
|
||||
Add Mem0 MCP to all supported clients with a single command:
|
||||
|
||||
```bash
|
||||
npx mcp-add \
|
||||
--name mem0-mcp \
|
||||
--type http \
|
||||
--url "https://mcp.mem0.ai/mcp" \
|
||||
--clients "claude,claude code,cursor,windsurf,vscode,opencode"
|
||||
```
|
||||
|
||||
Or configure a specific client:
|
||||
|
||||
```bash
|
||||
npx mcp-add \
|
||||
--name mem0-mcp \
|
||||
--type http \
|
||||
--url "https://mcp.mem0.ai/mcp" \
|
||||
--clients "cursor"
|
||||
```
|
||||
|
||||
For manual configuration, add this to your MCP client config:
|
||||
|
||||
```json
|
||||
{
|
||||
"mcpServers": {
|
||||
"mem0-mcp": {
|
||||
"type": "http",
|
||||
"url": "https://mcp.mem0.ai/mcp"
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
For detailed per-client instructions, see the [Mem0 MCP Quickstart](/platform/mem0-mcp).
|
||||
|
||||
## Available tools
|
||||
|
||||
The MCP server exposes 9 memory tools to your AI client:
|
||||
@@ -30,139 +67,12 @@ The MCP server exposes 9 memory tools to your AI client:
|
||||
| `get_memory` | Retrieve single memory by ID |
|
||||
| `list_entities` | View stored entities |
|
||||
|
||||
## Deployment options
|
||||
## How it works
|
||||
|
||||
Choose the deployment method that fits your workflow:
|
||||
|
||||
<AccordionGroup>
|
||||
<Accordion title="Python package (recommended)">
|
||||
Install and run locally with uvx:
|
||||
|
||||
```bash
|
||||
uv pip install mem0-mcp-server
|
||||
```
|
||||
|
||||
Configure your client:
|
||||
```json
|
||||
{
|
||||
"mcpServers": {
|
||||
"mem0": {
|
||||
"command": "uvx",
|
||||
"args": ["mem0-mcp-server"],
|
||||
"env": {
|
||||
"MEM0_API_KEY": "m0-...",
|
||||
"MEM0_DEFAULT_USER_ID": "your-handle"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="Docker container">
|
||||
Containerized deployment with HTTP endpoint:
|
||||
|
||||
```bash
|
||||
docker build -t mem0-mcp-server https://github.com/mem0ai/mem0-mcp.git
|
||||
docker run --rm -d -e MEM0_API_KEY="m0-..." -p 8080:8081 mem0-mcp-server
|
||||
```
|
||||
|
||||
Configure for HTTP:
|
||||
```json
|
||||
{
|
||||
"mcpServers": {
|
||||
"mem0-docker": {
|
||||
"command": "curl",
|
||||
"args": ["-X", "POST", "http://localhost:8080/mcp", "--data-binary", "@"],
|
||||
"env": {
|
||||
"MEM0_API_KEY": "m0-..."
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="Smithery">
|
||||
One-click setup with managed service:
|
||||
|
||||
Visit [smithery.ai/server/@mem0ai/mem0-memory-mcp](https://smithery.ai/server/@mem0ai/mem0-memory-mcp) and:
|
||||
|
||||
1. Select your AI client (Cursor, Claude Desktop, etc.)
|
||||
2. Configure your Mem0 API key
|
||||
3. Set your default user ID
|
||||
4. Enable graph memory (optional)
|
||||
5. Copy the generated configuration
|
||||
|
||||
Your client connects automatically - no installation required.
|
||||
</Accordion>
|
||||
</AccordionGroup>
|
||||
|
||||
## Configuration
|
||||
|
||||
### Required environment variables
|
||||
```bash
|
||||
MEM0_API_KEY="m0-..." # Your Mem0 API key
|
||||
MEM0_DEFAULT_USER_ID="your-handle" # Default user ID
|
||||
```
|
||||
|
||||
### Optional variables
|
||||
```bash
|
||||
MEM0_ENABLE_GRAPH_DEFAULT="true" # Enable graph memories
|
||||
MEM0_MCP_AGENT_MODEL="gpt-4o-mini" # LLM for bundled examples
|
||||
```
|
||||
|
||||
<AccordionGroup>
|
||||
<Accordion title="Test your setup with the Python agent">
|
||||
The included Pydantic AI agent provides an interactive REPL to test memory operations:
|
||||
|
||||
```bash
|
||||
# Install the package
|
||||
pip install mem0-mcp-server
|
||||
|
||||
# Set your API keys
|
||||
export MEM0_API_KEY="m0-..."
|
||||
export OPENAI_API_KEY="sk-openai-..."
|
||||
|
||||
# Clone and test with the agent
|
||||
git clone https://github.com/mem0ai/mem0-mcp.git
|
||||
cd mem0-mcp-server
|
||||
python example/pydantic_ai_repl.py
|
||||
```
|
||||
|
||||
**Testing different server configurations:**
|
||||
|
||||
- **Local server** (default): `python example/pydantic_ai_repl.py`
|
||||
|
||||
- **Docker container**:
|
||||
```bash
|
||||
export MEM0_MCP_CONFIG_PATH=example/docker-config.json
|
||||
export MEM0_MCP_CONFIG_SERVER=mem0-docker
|
||||
python example/pydantic_ai_repl.py
|
||||
```
|
||||
|
||||
- **Smithery remote**:
|
||||
```bash
|
||||
export MEM0_MCP_CONFIG_PATH=example/config-smithery.json
|
||||
export MEM0_MCP_CONFIG_SERVER=mem0-memory-mcp
|
||||
python example/pydantic_ai_repl.py
|
||||
```
|
||||
|
||||
Try these test prompts:
|
||||
- "Remember that I love tiramisu"
|
||||
- "Search for my food preferences"
|
||||
- "Update my project: the mobile app is now 80% complete"
|
||||
- "Show me all memories about project Phoenix"
|
||||
- "Delete memories from 2023"
|
||||
</Accordion>
|
||||
</AccordionGroup>
|
||||
|
||||
## How the testing works
|
||||
|
||||
1. **Configuration loads** - Reads from `example/config.json` by default
|
||||
2. **Server starts** - Launches or connects to the Mem0 MCP server
|
||||
3. **Agent connects** - Pydantic AI agent (Mem0Guide) attaches to the server
|
||||
4. **Interactive REPL** - You get a chat interface to test all memory operations
|
||||
1. **Configure the MCP server** - Add Mem0 MCP to your AI client using the setup command above
|
||||
2. **Agent connects** - Your AI client connects to Mem0's cloud MCP server over HTTP
|
||||
3. **Autonomous memory** - The agent decides when to store/retrieve memories as part of its reasoning
|
||||
4. **No manual API calls** - The agent manages memory automatically through MCP tools
|
||||
|
||||
## Example interactions
|
||||
|
||||
@@ -225,14 +135,11 @@ The Mem0 MCP server enables powerful memory capabilities for your AI application
|
||||
|
||||
## Best practices
|
||||
|
||||
- **Start simple**: Use the Python package for development
|
||||
- **Use the cloud MCP**: The hosted MCP server at `https://mcp.mem0.ai/mcp` handles infrastructure for you
|
||||
- **Use wildcards**: `user_id: "*"` to search across all users
|
||||
- **Test locally**: Use the bundled Python agent to verify setup
|
||||
- **Monitor usage**: Track memory operations in the dashboard
|
||||
- **Document patterns**: Share successful prompt patterns with your team
|
||||
|
||||
{/* DEBUG: verify CTA targets */}
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card
|
||||
title="Memory Filters"
|
||||
@@ -246,4 +153,4 @@ The Mem0 MCP server enables powerful memory capabilities for your AI application
|
||||
icon="book-open"
|
||||
href="/cookbooks/frameworks/gemini-3-with-mem0-mcp"
|
||||
/>
|
||||
</CardGroup>
|
||||
</CardGroup>
|
||||
|
||||
Reference in New Issue
Block a user