Portainer MCP Server for LangChainGive LangChain instant access to 6 tools to Add Endpoint, Authenticate, Create Docker Container, and more

Name: Portainer
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

LangChain is the leading Python framework for composable LLM applications. Connect Portainer through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Ask AI about this MCP Server for LangChain

Open in ChatGPT Open in Claude Open in Perplexity

The Portainer MCP Server for LangChain is a standout in the Ship It category — giving your AI agent 6 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

Claude

ChatGPT

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Gemini

Windsurf

VS Code

JetBrains

Vercel

+ other MCP clients

python

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({
        "portainer": {
            "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 Portainer, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Portainer MCP Server

Connect your Portainer instance to any AI agent and orchestrate your containerized infrastructure through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Portainer through native MCP adapters. Connect 6 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

Container Management — List all Docker containers in any environment, create new ones from images, and start existing containers.
Environment Orchestration — Add and manage new local or remote Docker/Kubernetes environments (endpoints) to your Portainer setup.
Admin Control — Initialize admin accounts on fresh installations and authenticate to receive secure JWT tokens.
Configuration Control — Deploy containers with custom configurations, including exposed ports and host settings via JSON.

The Portainer MCP Server exposes 6 tools through the Vinkius. Connect it to LangChain in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 6 Portainer tools available for LangChain

When LangChain connects to Portainer through Vinkius, your AI agent gets direct access to every tool listed below — spanning docker, kubernetes, container-management, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

add

Add endpoint on Portainer

Add a new environment (endpoint) to Portainer

action

Authenticate on Portainer

Authenticate to receive a JWT token

create

Create docker container on Portainer

Create a new Docker container

init

Init admin on Portainer

Initialize Portainer admin password

list

List docker containers on Portainer

List Docker containers in an environment

start

Start docker container on Portainer

Start a Docker container

Connect Portainer to LangChain via MCP

Follow these steps to wire Portainer into LangChain. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 6 tools from Portainer via MCP

Why Use LangChain with the Portainer MCP Server

LangChain provides unique advantages when paired with Portainer through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Portainer 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 Portainer queries for multi-turn workflows

Portainer + LangChain Use Cases

Practical scenarios where LangChain combined with the Portainer MCP Server delivers measurable value.

RAG with live data: combine Portainer tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Portainer, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Portainer tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Portainer tool call, measure latency, and optimize your agent's performance

Example Prompts for Portainer in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Portainer immediately.

"List all containers in Portainer endpoint 1."

"Create a new container named 'web-server' using the 'nginx:latest' image in endpoint 2."

"Start the container 'redis-cache' in endpoint 1."

Troubleshooting Portainer MCP Server with LangChain

Common issues when connecting Portainer to LangChain through Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Portainer + LangChain FAQ

Common questions about integrating Portainer MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use 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?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.