Kintone MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Kintone 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
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({
"kintone": {
"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 Kintone, 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 Kintone MCP Server
Connect your Kintone platform to any AI agent to automate your business operations. This MCP server enables your agent to interact with custom apps, manage data records, and query organizational metadata directly.
LangChain's ecosystem of 500+ components combines seamlessly with Kintone 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
- Record Management — List, retrieve, add, and update records in any of your Kintone apps
- App Discovery — List all available applications and retrieve detailed configurations and field mappings
- Data Querying — Use Kintone's powerful query language to filter records based on complex criteria
- Form Inspection — Access form field settings and layouts to understand data structures
- Space Visibility — List members and participants within your Kintone collaboration spaces
The Kintone 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 Kintone to LangChain via MCP
Follow these steps to integrate the Kintone 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 Kintone via MCP
Why Use LangChain with the Kintone MCP Server
LangChain provides unique advantages when paired with Kintone through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Kintone 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 Kintone queries for multi-turn workflows
Kintone + LangChain Use Cases
Practical scenarios where LangChain combined with the Kintone MCP Server delivers measurable value.
RAG with live data: combine Kintone tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Kintone, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Kintone tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Kintone tool call, measure latency, and optimize your agent's performance
Kintone MCP Tools for LangChain (10)
These 10 tools become available when you connect Kintone to LangChain via MCP:
add_record
Requires a JSON object mapping field codes to values. Add a new record to an app
delete_records
Requires an array of record IDs. Delete records from an app
get_app_details
Get details for a specific app
get_app_layout
Get the field layout of an app
get_record
Get a specific record from an app
list_apps
Use this to identify App IDs for record operations. List all Kintone apps
list_form_fields
List form fields for an app
list_records
You can optionally provide a query string for filtering. List records from an app
list_space_members
List members of a Kintone space
update_record
Update an existing record
Example Prompts for Kintone in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Kintone immediately.
"List all my Kintone apps."
"Show records from app ID 10 where status is 'Pending'."
"Add a new record to app 12 with name 'Jane Doe' and role 'Designer'."
Troubleshooting Kintone MCP Server with LangChain
Common issues when connecting Kintone to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersKintone + LangChain FAQ
Common questions about integrating Kintone 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 Kintone with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
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 Kintone to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.