Neon (Serverless PostgreSQL) MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Neon (Serverless PostgreSQL) through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"neon-serverless-postgresql": {
"transport": "streamable_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,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using Neon (Serverless PostgreSQL), show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Neon (Serverless PostgreSQL) MCP Server
Connect your Neon account to any AI agent and take full control of your serverless PostgreSQL infrastructure, database branching, and project orchestration through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Neon (Serverless PostgreSQL) through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
What you can do
- Project Orchestration — List all managed serverless workspaces and retrieve detailed regional deployment metrics and regional Caps directly from your agent
- Zero-Copy Branching — Instantly spawn brand new database branches (CoW) containing identical production schema duplicates for isolated feature testing or rapid CI/CD cycles
- Compute Management — Discover and list explicit compute endpoints (e.g., ep-misty-water-123) to retrieve the exact connection strings required for your application drivers
- Branch Audit — Inspect the execution footprint of specific branches, tracking storage deltas and timeline points (LSN) to understand exactly when a branch split from its parent
- Database Inventory — Enumerate internal SQL database schemas and catalog namespaces mapped inherently to specific branches to guide your connection logic
- Role Management — List and audit PostgreSQL user identities and credential roles capable of querying against specific bounded logical nodes securely
- Resource Provisioning — Initialize fresh serverless workspaces or permanently wipe out entire database ecosystems with irreversible architectural commands
The Neon (Serverless PostgreSQL) MCP Server exposes 10 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Neon (Serverless PostgreSQL) to LangChain via MCP
Follow these steps to integrate the Neon (Serverless PostgreSQL) MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 10 tools from Neon (Serverless PostgreSQL) via MCP
Why Use LangChain with the Neon (Serverless PostgreSQL) MCP Server
LangChain provides unique advantages when paired with Neon (Serverless PostgreSQL) through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Neon (Serverless PostgreSQL) MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across Neon (Serverless PostgreSQL) queries for multi-turn workflows
Neon (Serverless PostgreSQL) + LangChain Use Cases
Practical scenarios where LangChain combined with the Neon (Serverless PostgreSQL) MCP Server delivers measurable value.
RAG with live data: combine Neon (Serverless PostgreSQL) tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Neon (Serverless PostgreSQL), synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Neon (Serverless PostgreSQL) tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Neon (Serverless PostgreSQL) tool call, measure latency, and optimize your agent's performance
Neon (Serverless PostgreSQL) MCP Tools for LangChain (10)
These 10 tools become available when you connect Neon (Serverless PostgreSQL) to LangChain via MCP:
create_branch
Duplicates Petabytes of PostgreSQL storage instantly using filesystem CoW links, generating an isolated query testing ground tied back directly to the `parent_id` source. Spawn a zero-copy clone (Branch) of a PostgreSQL dataset
create_project
Provision an empty Neon Project Serverless Workspace
delete_project
Destroys all edge-served connection strings, severs active client connections, and completely evaporates physical NVMe-backed storage blocks. Permanently wipe out a complete Neon Postgres ecosystem
get_branch
Deconstruct the execution footprint of one specific Branch
get_project
g. AWS eu-central-1) and storage size consumption caps bounded specifically to this project ID. Analyze core routing logic mapping a Neon Project
list_branches
Maps `main` branches to experimental `feature-123` branches spawned in milliseconds containing identical production schema duplicates. List Copy-on-Write (CoW) Branches resolving to a Project
list_databases
g. `main_db`, `analytics_db_schema`). Crucial for forming absolute Postgres connection strings resolving directly to correct schemas. Identify internal SQL Database schemas mapped inherently to a Branch
list_endpoints
eu-central-1.aws.neon.tech`) used practically within standard PgBouncer drivers to actively ingest real query traffic to associated active branches. Discover connection routing endpoints spanning the Neon project
list_projects
List architectural Neon Serverless PostgreSQL Projects
list_roles
Maps directly to standard SQL internal `CREATE USER` outputs wrapped safely upstream. Extract PostgreSQL user Roles operating on a Branch
Example Prompts for Neon (Serverless PostgreSQL) in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Neon (Serverless PostgreSQL) immediately.
"List all serverless projects in my Neon account"
"Create a new branch called 'feat-user-auth' from the 'main' branch"
"What databases and roles are configured on branch 'br-12345'?"
Troubleshooting Neon (Serverless PostgreSQL) MCP Server with LangChain
Common issues when connecting Neon (Serverless PostgreSQL) to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersNeon (Serverless PostgreSQL) + LangChain FAQ
Common questions about integrating Neon (Serverless PostgreSQL) MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect Neon (Serverless PostgreSQL) with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
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TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Neon (Serverless PostgreSQL) to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.
