4,000+ servers built on vurb.ts
Vinkius
LangChainFramework
Kintone MCP Server

Bring Low Code
to LangChain

Learn how to connect Kintone to LangChain and start using 8 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.

MCP Inspector GDPR Free for Subscribers
Add RecordsDelete RecordsGet App FieldsGet RecordGet Space DetailsList AppsList RecordsUpdate Records

Compatible with every major AI agent and IDE

ClaudeClaude
ChatGPTChatGPT
CursorCursor
GeminiGemini
WindsurfWindsurf
VS CodeVS Code
JetBrainsJetBrains
VercelVercel
+ other MCP clients
Kintone

What is the Kintone MCP Server?

Connect your Kintone instance to any AI agent and manage business applications through natural conversation.

What you can do

  • App Management — List all apps and inspect their field configurations
  • Record Operations — Create, read, update, and query records in any app
  • Data Queries — Search records using Kintone query syntax with field filters
  • Field Access — Browse app fields and their types for data modeling

How it works

  1. Subscribe to this server
  2. Enter your Kintone domain and API Token
  3. Start managing apps from Claude, Cursor, or any MCP-compatible client

Who is this for?

  • Operations Teams — manage business data without opening each app
  • Developers — integrate Kintone data into AI workflows
  • Managers — query records and track metrics across apps

Built-in capabilities (8)

add_records

Input should be a JSON array of record objects. Add one or more records to an app

delete_records

Delete records from an app

get_app_fields

Get app field settings

get_record

Get details for a specific record

get_space_details

Get details for a space

list_apps

List all accessible Kintone apps

list_records

You can provide an optional query string. List records from a Kintone app

update_records

Update one or more records

Why LangChain?

LangChain's ecosystem of 500+ components combines seamlessly with Kintone through native MCP adapters. Connect 8 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.

  • 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

See it in action

Kintone in LangChain

AI AgentVinkius
High Security·Kill Switch·Plug and Play
Why Vinkius

Kintone and 4,000+ other MCP servers. One platform. One governance layer.

Teams that connect Kintone to LangChain through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.

4,000+MCP Servers ready
<40msCold start
60%Token savings
Raw MCP
Vinkius
Server catalogFind and host yourself4,000+ managed
InfrastructureSelf-hostedSandboxed V8 isolates
Credential handlingPlaintext in configVault + runtime injection
Data loss preventionNoneConfigurable DLP policies
Kill switchNoneGlobal instant shutdown
Financial circuit breakersNonePer-server limits + alerts
Audit trailNoneEd25519 signed logs
SIEM log streamingNoneSplunk, Datadog, Webhook
HoneytokensNoneCanary alerts on leak
Custom domainsNot applicableDNS challenge verified
GDPR complianceManual effortAutomated purge + export
Enterprise Security

Why teams choose Vinkius for Kintone in LangChain

The Kintone 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. All 8 tools execute in hardened sandboxes optimized for native MCP execution.

Your AI agents in LangChain only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.

Kintone
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

The Vinkius Advantage

How Vinkius secures Kintone for LangChain

Every tool call from LangChain to the Kintone MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.

< 40msCold start
Ed25519Signed audit chain
60%Token savings
FAQ

Frequently asked questions

01

Can I query records across Kintone apps?

Yes. Query records using Kintone's query syntax with field filters, sorting, and pagination. Works across any app in your instance.

02

Does Kintone require a custom domain?

Yes. Each Kintone account has a unique domain (e.g., your-company.cybozu.com). Provide the domain and an API Token generated for the specific app.

03

Can I create and update records?

Yes. Create new records with field values, update existing records, and manage data across all your Kintone apps.

04

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.

05

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.

06

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.

07

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

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