Can my agent keep track of incremental updates to my CMS items?

Yes. The agent has tools specifically designed to fetch incremental updates using a sync token. It can request only the CMS items or pages that have changed (created, updated, or deleted) since the last automated sync, optimizing fetch latency.

How do I find the correct Reference Name to query content?

Reference Names match the identifiers predefined in your Agility CMS Models architecture (such as 'articles', 'authors', or 'posts'). If you are unsure, ask the agent to scan common variables based on your company's naming conventions.

Can my agent preview unpublished drafting content?

That depends on the API Token you supply during the integration. If you provide a Preview API Key, the agent will have read-access to the staging and drafted documents. If you provide a Fetch API key, it will only see published items.

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

Name: Agility CMS
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 Agility CMS 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({
        "agility-cms": {
            "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 Agility CMS, 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 Agility CMS MCP Server

Connect your Agility CMS instance to your AI agent and turn it into the ultimate Headless CMS assistant. Skip manual API queries and interact directly with your content architecture using natural language.

LangChain's ecosystem of 500+ components combines seamlessly with Agility CMS 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

Sitemap & Routing — Retrieve nested sitemap trees or flat router architectures to understand how your channels are structured
Content Lists — Search, list, and count items across specific CMS references like articles, authors, or products
Page Layouts — Fetch exact page modules, UI components mapping, and structural layout definitions using Page IDs
Content Operations — Read full content payloads for individual items and synchronize granular CMS updates over time
Media Galleries — Fetch specific media asset groups and tracking galleries for imagery

The Agility CMS 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 Agility CMS to LangChain via MCP

Follow these steps to integrate the Agility CMS 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 Agility CMS via MCP

Why Use LangChain with the Agility CMS MCP Server

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

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

Agility CMS + LangChain Use Cases

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

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

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

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

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

Agility CMS MCP Tools for LangChain (10)

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

count_reference_items

Get the total size/count of items in a specific Reference List

get_media_gallery

Retrieve a specific media gallery mapping containing photos

get_page_layout

Retrieve the layout and structural modules of a single Page

get_single_item

g., an article body) knowing its numeric content ID. Retrieve a single Agility CMS content item by its ID

get_site_flat_router

Retrieve the exact flat list of all CMS routes/pages

get_site_tree

Requires the target channel name. Retrieve the nested sitemap architecture of a digital channel

list_content_items

g. blog posts, articles, authors). The items are retrieved from the Headless CMS environment. List content items from an Agility CMS Reference list

search_content_reference

Search for specific keywords inside a Content Reference List

sync_incremental_items

Start with 0 for full backup. Get incrementally updated items since the last sync token

sync_incremental_pages

Start with 0 for a full fetch. Get incrementally updated pages since the last sync token

Example Prompts for Agility CMS in LangChain

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

"Get the flat sitemap for our website to see all registered routes."

"Search the 'blog_posts' reference list for the keyword 'announcement'."

"Retrieve the full page layout and modules for page ID 12."

Troubleshooting Agility CMS MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Agility CMS + LangChain FAQ

Common questions about integrating Agility CMS 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.