How to Use the Mem0 MCP in AutoGen

Q: Can multiple AutoGen agents access Mem0 simultaneously?

Yes, any agent in your AutoGen group can call searchmemories to retrieve context. This ensures that both the creative writer agent and the editor agent work with the same user preferences.

Q: Can I inspect all facts stored for a user?

Use the getmemories tool to fetch the entire list of facts. This allows your agents to run background checks and verify if a user has existing records before starting a new task.

Let your AutoGen agents debate and agree on user preferences that persist across different conversations.

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Create your Vinkius account to connect Mem0 to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Mem0 with AutoGen

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Manage AutoGen consensus with `add_memory`

The `add_memory` tool registers structured facts in the Mem0 database once your agents reach a consensus about a user preference. Instead of writing every conversational detail, the group debates what is actually worth remembering. AutoGen routes this MCP Server tool to the specific agent responsible for memory management. Once the performance and security agents agree the fact is valid, they commit it to long-term storage.

Recall group context using `search_memories`

The `search_memories` tool searches the user's past interactions to supply relevant context to all active agents using the MCP standard. When a new agent joins the debate, it uses this tool to quickly get up to speed on user preferences. Querying the database at the start of a session prevents agents from asking redundant questions. By distributing user constraints to the rest of the group, the coordinator agent ensures everyone is on the same page.

Resolve conflicting facts using `delete_memory`

The `delete_memory` tool deletes specific facts by ID, and `get_memories` retrieves the entire list of saved facts for a user. These tools allow agents to resolve contradictions when a user changes their mind. In AutoGen, a moderator agent can call these tools to update the user's profile. If a user states a new preference, the agent retrieves the old list, identifies the conflict, and deletes the stale record.

Setup guide

Set up Mem0 MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Mem0 tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Mem0_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Mem0 data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Mem0_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Mem0 data")
    print(result.messages[-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Mem0. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Mem0 MCP in AutoGen

Pass the server URL to StreamableHttpServerParams and fetch the tools. You then pass this tool list to your AssistantAgent constructor, which automatically handles the schema conversion.

Yes, any agent in your AutoGen group can call search_memories to retrieve context. This ensures that both the creative writer agent and the editor agent work with the same user preferences.

You can configure a supervisor agent to monitor the conversation. Once a clear user preference is established, the supervisor instructs the memory agent to call the add_memory tool.

Use the get_memories tool to fetch the entire list of facts. This allows your agents to run background checks and verify if a user has existing records before starting a new task.

User facts and conversational memories are routed through ephemeral, zero-trust environments. Vinkius secures these MCP transactions with strict token authorization, ensuring no raw data is exposed to external networks.

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