How to Use the Fieldfolio MCP in LangChain
Build multi-step LangChain chains that manage your Fieldfolio catalog, track wholesale orders, and update stock levels automatically.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Fieldfolio MCP to LangChain
Create your Vinkius account to connect Fieldfolio 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.
Chain wholesale lookups with LangChain
This MCP Server connects your LangChain agent to `list_orders` and `get_order` to automate order fulfillment pipelines. The output of an order lookup feeds directly into the next step of your chain, letting your agent inspect line items and customer details in a single execution loop. You trace the entire execution path in LangSmith to monitor latency and token usage. If an order lacks sufficient stock, your agent triggers a follow-up step to find alternative items without manual intervention.
Automate stock adjustments in LangGraph
Running `list_inventory` and `update_inventory` lets your LangGraph state machines modify wholesale stock levels based on live sales events. Your agent reads the current inventory, evaluates it against pending requests, and pushes the updated quantities straight back to Fieldfolio. Because LangChain handles state transition, you can build loops that check stock before writing changes. This prevents race conditions when multiple wholesale orders process at the same time.
Search catalogs using LangChain agents
Calling `search_catalog` and `list_products` exposes your entire Fieldfolio wholesale catalog to LangChain's tool-calling agents. Your agent searches by keyword, filters by category using `list_categories`, and retrieves specific product metadata on demand. This setup lets you build conversational catalog search systems for your sales team. They ask questions in plain English, and the agent translates those requests into precise API queries.
Set up Fieldfolio MCP in LangChain
Prerequisites
- Python 3.10+ installed
-
langchain-mcp-adapters+langgraphpackages - 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 LangChainBaseToolobjects. - 2
Connect via HTTP transport
Use
MultiServerMCPClientwith"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 Fieldfolio tool calls through the MCP protocol. - 4
Run with any LLM
Swap
ChatOpenAIforChatAnthropic,ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.
from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI
async with MultiServerMCPClient({
"fieldfolio-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 Fieldfolio transactions"
})
print(result["messages"][-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Fieldfolio. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Common questions about Fieldfolio MCP in LangChain
Use it with your favorite AI tools
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Start using the Fieldfolio MCP today
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