How to Use the Neon (Serverless PostgreSQL) MCP in LangChain

Q: Can LangChain use Neon (Serverless PostgreSQL) to test migrations?

Yes. You trigger createbranch to clone your schema, run migrations against the branch, and then verify the results before merging.

Build database-aware chains with LangChain and the Neon (Serverless PostgreSQL) MCP Server for instant schema cloning.

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Connect Neon (Serverless PostgreSQL) MCP to LangChain

Create your Vinkius account to connect Neon (Serverless PostgreSQL) to LangChain 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 Neon (Serverless PostgreSQL) with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Automate schema branching in LangChain

Chain your agents to spin up isolated environments on demand. You use `create_branch` to mirror production state without moving heavy data. This keeps your testing logic fast and your main database untouched. Your agents trigger these clones directly within the pipeline.

Monitor live compute in LangChain pipelines

Track your infrastructure health by chaining `list_endpoints` calls. You spot active connections and verify where your traffic hits. LangSmith tracing lets you see exactly what the server returns. It makes debugging database routing simple and predictable.

Manage project lifecycle via LangChain

Clean up abandoned experiments by calling `delete_project` from your agentic workflows. You remove stale NVMe storage blocks without manual intervention. This prevents resource bloat in your serverless infrastructure. Your agents maintain the project state automatically.

Setup guide

Set up Neon (Serverless PostgreSQL) MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Neon (Serverless PostgreSQL) tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "neon-serverless-postgresql-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent Neon (Serverless PostgreSQL) transactions"
    })
    print(result["messages"][-1].content)

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Common questions about Neon (Serverless PostgreSQL) MCP in LangChain

Install the MCP adapters and point your client to the server URL. Pass the tool list into your agent constructor to enable database control.

Yes. You trigger `create_branch` to clone your schema, run migrations against the branch, and then verify the results before merging.

It does. The client handles multiple servers, allowing your chain to query database status alongside other external data sources.

The server remains stateless. If you need persistent sessions, use the client session management to keep your context across multiple steps.

Your connection strings and data remain isolated to your project. The server only exposes the specific tools you authorize for your agent.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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