How to Use the Neon MCP in AutoGen
Let AutoGen agents debate your Neon infrastructure changes. Build consensus-driven systems that provision serverless Postgres environments.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Neon MCP to AutoGen
Create your Vinkius account to connect Neon 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.
Multi-agent consensus for Neon
The `delete_project` tool destroys all branches, databases, and data within a workspace. You configure a security agent to challenge any deletion request. It debates the operational agent, demanding proof that the project is truly obsolete before allowing the execution. The operational agent pulls data using `list_endpoints` to show that all compute nodes have been suspended for weeks. Once both agents agree the resource is dead, they proceed with the deletion.
Coordinate schema tests via MCP Server
The `create_branch` tool generates a copy-on-write clone of your primary database. A developer agent requests a sandbox environment, and an infrastructure agent provisions it. They negotiate the exact naming convention and parent branch ID based on the current project state. Once the sandbox is ready, the infrastructure agent calls `get_connection_uri`. It hands the credentials back to the developer agent, which then runs its migration scripts against the isolated branch.
Provision roles through agent debate
The `create_role` tool generates new database credentials. If an application agent requests full admin access, a DBA agent intercepts the request. It runs `list_roles` to see existing privileges and argues for a more restricted user role instead. They settle on a read-only configuration. The DBA agent calls `create_endpoint` to spin up a read replica, binds the new role to it, and delivers the secure connection string to the application agent.
Set up Neon 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 includesmcp_server_toolsfor 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
AssistantAgentand callagent.run(). The agent invokes Neon tools and returns structured results.
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="Neon_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Neon data")
print(result.messages[-1].content) 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.
McpWorkbenchis 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=workbenchto your agent. State is preserved across multiple tool calls within the same session.
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="Neon_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Neon data")
print(result.messages[-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Neon. 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 Neon MCP in AutoGen
Use it with your favorite AI tools
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