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Provides a modular MCP server to connect MCP clients with IBM Data Intelligence services for secure, extensible interactions.
Configuration
View docs{
"mcpServers": {
"hingaibm-data-intelligence-mcp-server": {
"url": "<url_to_mcp_server>",
"headers": {
"DI_CONTEXT": "df",
"DI_ENV_MODE": "SaaS",
"LOG_FILE_PATH": "/tmp/di-mcp-server-logs",
"DI_SERVICE_URL": "https://api.dataplatform.cloud.ibm.com",
"REQUEST_TIMEOUT_S": "60"
}
}
}
}The Data Intelligence MCP Server provides a modular, scalable bridge between MCP clients and IBM Data Intelligence services. It enables secure, extensible interactions so you can automate workflows, integrate tools, and run prompts against Data Intelligence capabilities from clients like Claude, Copilot, or VS Code Copilot.
You connect MCP clients to the Data Intelligence MCP Server in either stdio (local) mode or HTTP/HTTPS (remote) mode. In stdio mode, your client communicates directly through standard input/output, ideal for local development. In HTTP/HTTPS mode, the server runs as a network service you reach via a remote URL and API key. Once connected, you can send prompts, receive tool responses, and orchestrate data intelligence tasks through supported clients.
Typical usage patterns include: connecting Claude Desktop or VS Code Copilot to a locally running MCP server in stdio mode for fast iteration, or configuring a remote HTTP(S) endpoint for cloud-based workflows. You can switch between local and remote setups by adjusting the client configuration to point at the appropriate transport and endpoints.
Prerequisites vary slightly by installation method. Ensure you have a supported runtime and access to the Data Intelligence service you plan to integrate with.
pip install ibm-watsonx-data-intelligence-mcp-serverConfiguration details, environment variables, and client settings are described in the sections below. You will set up environment variables for the client, choose between stdio or HTTP/HTTPS transports, and provide authentication information as required by your deployment.