How do I get an Elemeno API Key?

Log in to your Elemeno dashboard, select your project, navigate to **Settings > API**, and you can retrieve your unique API Key from there.

Does the integration support draft content?

Yes, you can use the list_collection_items tool to see all items, including their status (e.g., draft or published). Specific content retrieval depends on your API key permissions.

Can the agent update content via the API?

This integration currently focuses on listing and auditing content. Creating or updating items and singletons should be managed via the Elemeno dashboard or specific management API endpoints.

Elemeno MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: Elemeno
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

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

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

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

asyncio.run(main())

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* 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 Elemeno MCP Server

Integrate Elemeno, the headless CMS designed for developers, directly into your AI workflow. Manage your content collections and singletons (global pages), track individual items and their publishing statuses, monitor field schemas, and oversee your entire content library using natural language.

LangChain's ecosystem of 500+ components combines seamlessly with Elemeno 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

Collection Oversight — List and retrieve detailed information and field schemas for all your content collections.
Content Intelligence — Monitor individual collection items, resolving titles, slugs, and real-time publishing statuses.
Singleton Management — Access and monitor singleton content blocks, resolving global settings and unique page data.
Content Auditing — Retrieve high-level summaries of collection activity, item counts, and organizational CMS health.

The Elemeno 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 Elemeno to LangChain via MCP

Follow these steps to integrate the Elemeno 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 Elemeno via MCP

Why Use LangChain with the Elemeno MCP Server

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

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

Elemeno + LangChain Use Cases

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

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

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

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

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

Elemeno MCP Tools for LangChain (10)

These 10 tools become available when you connect Elemeno to LangChain via MCP:

get_collection_details

Get detailed settings and field schema for a specific collection

get_collection_item_details

Get full content and metadata for a specific item in a collection

get_elemeno_account_metadata

Retrieve metadata and limits for your Elemeno account

get_singleton_content

Get the full content data for a specific singleton

list_collection_items

List all content items within a specific collection

list_content_collections

List all content collections configured in your Elemeno account

list_content_singletons

List all singleton content blocks (unique global pages/settings)

list_published_content

Identify items that are currently in a "Published" status

quick_content_volume_audit

Retrieve a high-level summary of collection and singleton activity

search_collection_content

Search for items within a collection using a title or slug keyword

Example Prompts for Elemeno in LangChain

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

"List all content collections in my project."

"Show me the items in the 'Services' collection."

"What is the content of the 'Contact Page' singleton?"

Troubleshooting Elemeno MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Elemeno + LangChain FAQ

Common questions about integrating Elemeno 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.