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Windsurf is an AI-native IDE built around Cascade, an autonomous coding agent that understands project context and executes multi-step tasks directly inside the editor. Cascade supports the Model Context Protocol (MCP), allowing the agent to discover and call external tools and data sources without leaving the development environment.
By integrating Windsurf with CData Connect AI through the built-in MCP server, the Cascade agent gains governed, real-time access to live Kintone data. This enables developers to list catalogs, inspect schemas, and query records from Kintone data within the IDE using natural language prompts.
This article explains how to configure Kintone connectivity in Connect AI, generate the required personal access token, configure the Connect AI MCP Server in Windsurf, and verify the integration by querying live Kintone data from the Cascade chat.
Connectivity to Kintone from Windsurf is made possible through Connect AI's Remote MCP Server. To interact with Kintone data from Windsurf, start by creating and configuring a Kintone connection in Connect AI.
In addition to the authentication values, set the following parameters to connect to and retrieve data from Kintone:
Kintone supports the following authentication methods.
You must set the following to authenticate:
If the basic authentication security feature is set on the domain, supply the additional login credentials with BasicAuthUser and BasicAuthPassword. Basic authentication requires these credentials in addition to User and Password.
Instead of basic authentication, you can specify a client certificate to authenticate. Set SSLClientCert, SSLClientCertType, SSLClientCertSubject, and SSLClientCertPassword. Additionally, set User and Password to your login credentials.
π Configuring a connection (Salesforce is shown)A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from Windsurf. It is best practice to create a separate PAT for each integration to maintain granular access control.
With the Kintone connection configured and a PAT generated, Windsurf can now connect to Kintone data.
Next, configure the Connect AI Remote MCP Server in Windsurf so that the Cascade agent can discover and call live data tools through Connect AI.
{
"mcpServers": {
"cdata-mcp": {
"serverUrl": "https://mcp.cloud.cdata.com/mcp",
"headers": {
"Authorization": "Basic your_base64_encoded_email_PAT",
"Content-Type": "application/json"
}
}
}
}
Note: Windsurf will use Basic authentication with Connect AI. Combine your Connect AI user email and the PAT you created earlier in the format email:PAT, base64 encode the combined string, and prefix it with Basic. For example, given [email protected]:ABC123...XYZ789, the Authorization header value becomes something like: Basic dXNlckBkb21haW4uY29tOkFCQzEyMy4uLlhZWjc4OQ==
π Pasting Connect AI MCP Server configurationWith the MCP server registered and enabled, Windsurf is ready to query live Kintone data through Connect AI.
With the integration complete, use the Cascade chat panel in Windsurf to interact with live Kintone data through natural language prompts.
At this point, your Windsurf IDE communicates with the Connect AI MCP Server and retrieves live Kintone data through remote MCP directly from the editor.
To access hundreds of SaaS, Big Data, and NoSQL sources directly from your cloud applications, try CData Connect AI today! Download a free 14-day trial of CData Connect AI today, and as always, our Support Team is available to assist you with any questions you may have.
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