Connect to watsonx.data Intelligence
IBM's official MCP server for watsonx.data intelligence - secure, modular integration with IBM Data Intelligence SaaS or CPD.
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Why it matters
Integrate with IBM watsonx.data Intelligence to access and manage your data assets. This connector allows you to find, understand, and work with data for analysis, quality control, and lineage tracking.
Outcomes
What it gets done
Connect to the watsonx.data Intelligence MCP server.
Extract data for further processing.
Query databases within the watsonx.data environment.
Facilitate data management and cataloging.
Install
Add it to your toolbox
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/vb-ibm-watsonx-data-intelligence | bash Overview
IBM watsonx.data intelligence MCP server
IBM watsonx.data intelligence MCP server bridges MCP clients to IBM's Data Intelligence platform, supporting SaaS or Cloud Pak for Data deployments over stdio or HTTP/HTTPS. Use it for enterprise data governance/catalog access from Claude, Copilot, or Watsonx Orchestrate; requires an active IBM Data Intelligence subscription and valid credentials.
What it does
IBM watsonx.data intelligence MCP server is a modular, scalable MCP implementation purpose-built to integrate with IBM Data Intelligence services, enabling secure interaction between MCP clients (Claude Desktop, VS Code Copilot, Watsonx Orchestrate, IBM Bob) and IBM's data intelligence capabilities. It supports both IBM Data Intelligence SaaS and Cloud Pak for Data (CPD) 5.2.1 environments, and ships an optional "skills" setup command (wxdi-setup-skills) that copies packaged skill definitions to a local folder for easy reference.
It runs in stdio mode (for local client integration, no separate server process needed) or in HTTP/HTTPS mode (for remote deployments), with client authentication via API key, username (for CPD), or bearer token, and no persistent storage of user data or credentials on the server itself - all communication to IBM Data Intelligence is over HTTPS/TLS.
When to use - and when NOT to
Use this connector when you need an AI assistant integrated with IBM watsonx.data intelligence - whether hosted as SaaS or on-prem via Cloud Pak for Data - for enterprise data governance/catalog workflows accessible from Claude, Copilot, Watsonx Orchestrate, or IBM Bob.
Do not use it without an active IBM Data Intelligence SaaS or CPD 5.2.1 subscription and valid API credentials - the server is a bridge to that platform, not a standalone data tool. For CPD environments you may also need to configure SSL/TLS certificates separately.
Inputs and outputs
Configuration inputs are environment variables or headers: DI_SERVICE_URL, DI_ENV_MODE (SaaS or CPD), and authentication via DI_APIKEY/DI_USERNAME/DI_AUTH_TOKEN (stdio) or x-api-key/username/authorization headers (HTTP). Outputs are IBM Data Intelligence query results and tool responses, with returned URLs contextualized via DI_CONTEXT (df, cpdaas, or cpd).
Capabilities
- Bridges MCP clients to IBM Data Intelligence services over HTTPS, supporting both SaaS and CPD deployments
- Runs in stdio mode (client-invoked, no separate server process) or HTTP/HTTPS mode (remote server)
- Optional skills setup (
wxdi-setup-skills) to install packaged skill definitions locally - Configurable request timeout, logging, and SSL/TLS for CPD environments
- No persistent storage of credentials or user data on the server
How to install
Via PyPI:
pip install ibm-watsonx-data-intelligence-mcp-server
Or via uv:
uvx ibm-watsonx-data-intelligence-mcp-server --transport stdio
For Claude Desktop (stdio):
{
"mcpServers": {
"wxdi-mcp-server": {
"command": "uvx",
"args": ["ibm-watsonx-data-intelligence-mcp-server", "--transport", "stdio"],
"env": {
"DI_SERVICE_URL": "https://api.dataplatform.cloud.ibm.com",
"DI_APIKEY": "<data intelligence api key>",
"DI_ENV_MODE": "SaaS"
}
}
}
}
Requires Python 3.11+ and an active Data Intelligence SaaS or CPD 5.2.1 environment.
Who it's for
Enterprise data teams using IBM watsonx.data intelligence who want AI assistant access to their data catalog and governance platform from Claude, Copilot, or Watsonx Orchestrate.
Source README
Data Intelligence MCP Server
The IBM Data Intelligence MCP Server provides a modular and scalable implementation of the Model Context Protocol (MCP), purpose-built to integrate with IBM Data Intelligence services. It enables secure and extensible interaction between MCP clients and IBM’s data intelligence capabilities.
For the list of tools supported in this version and sample prompts, refer to TOOLS_PROMPTS.md
For the list of skills supported in this version and instructions on how to use them, refer to SKILLS_REFERENCE.md
Note: For MCP clients that don't support
MCP prompts templateregistration, manual prompt templates are available in thePROMPTS_TEMPLATE_SAMPLES/directory.
flowchart LR
github["data-intelligence-mcp Github"] -- publish --> registry
registry["PyPi registry"] -- pip install ibm-watsonx-data-intelligence-mcp-server--> server
subgraph MCP Host
client["MCP Client"] <-- MCP/STDIO --> server("Data Intelligence MCP Server")
end
server -- HTTPS --> runtime("IBM Data Intelligence")
subgraph id["Services"]
runtime
end
client <-- MCP/HTTP --> server2("Data Intelligence MCP Server") -- HTTPS --> runtime
Resources:
- Integrating Claude with Watsonx Data Intelligence A step-by-step guide showing how Claude Desktop connects to the Data Intelligence MCP Server.
- Watsonx Orchestrate + Data Intelligence Demonstrates how Watsonx Orchestrate integrates with the MCP Server for automation.
- IBM Bob + Data Intelligence A step-by-step guide showing how IBM Bob connects to the Data Intelligence MCP Server.
Table of Contents
Quick Install - PyPI
Prerequisites
- Python 3.11 or higher
- Data Intelligence SaaS or CPD 5.2.1
Installation
Standard Installation
Use pip/pip3 for standard installation:
pip install ibm-watsonx-data-intelligence-mcp-server
Skills Setup (Optional)
After installation, you can copy the included skills folder to your location for easy access:
wxdi-setup-skills
This interactive command will:
- Ask for your confirmation before copying
- Copy the skills folder to your given location
- Handle overwrites if the folder already exists
Quick Install and run - uv
Prerequisites
- uv installation guide
- Data Intelligence SaaS or CPD 5.2.1
Install and Running
stdio mode
uvx ibm-watsonx-data-intelligence-mcp-server --transport stdio
http mode
uvx ibm-watsonx-data-intelligence-mcp-server
To setup skills (optional):
uvx --from ibm-watsonx-data-intelligence-mcp-server wxdi-setup-skills
Server
If you have installed the ibm-watsonx-data-intelligence-mcp-server locally on your host machine and want to connect from a client such as Claude, Copilot, or LMStudio, you can use the stdio mode as described in the examples under the Client Configuration section.
The server can also be configured and run in http/https mode.
Refer to Client Settings section on applicable environment variables for http mode. Update as required before starting the server below. Default DI_ENV_MODE is SaaS
HTTP Mode
ibm-watsonx-data-intelligence-mcp-server --transport http --host 0.0.0.0 --port 3000
HTTPS Mode
Refer to SERVER_HTTPS.md for detailed HTTPS server configuration and setup.
stdio Mode
When configuring the server through Claude, Copilot, or an MCP client in stdio mode, the server does not need to be started separately. The client will invoke the server directly using standard input/output.
Client Configuration
Claude Desktop
stdio (Recommended for local mcp server setup)
Prereq: uv installation guide
Add the MCP server to your Claude Desktop configuration:
{
"mcpServers": {
"wxdi-mcp-server": {
"command": "uvx",
"args": ["ibm-watsonx-data-intelligence-mcp-server", "--transport", "stdio"],
"env": {
"DI_SERVICE_URL": "https://api.dataplatform.cloud.ibm.com",
"DI_APIKEY": "<data intelligence api key>",
"DI_ENV_MODE": "SaaS",
"LOG_FILE_PATH": "/tmp/di-mcp-server-logs"
}
}
}
}
http/https (Remote setup)
If the MCP server is running on a local/remote server in http/https mode.
For Cloud SaaS:
{
"mcpServers": {
"wxdi-mcp-server": {
"url": "<url_to_mcp_server>",
"type": "http",
"headers": {
"x-api-key": "your api key from cloud SaaS"
}
}
}
}
For CPD:
{
"mcpServers": {
"wxdi-mcp-server": {
"url": "<url_to_mcp_server>",
"type": "http",
"headers": {
"x-api-key": "your api key from cpd env",
"username": "<user name from cpd env>"
}
}
}
}
VS Code Copilot
stdio (Recommended for local mcp server setup)
Prereq: uv installation guide
Add the MCP server to your VS Code Copilot MCP configuration:
{
"servers": {
"wxdi-mcp-server": {
"command": "uvx",
"args": ["ibm-watsonx-data-intelligence-mcp-server", "--transport", "stdio"],
"env": {
"DI_SERVICE_URL": "https://api.dataplatform.cloud.ibm.com",
"DI_APIKEY": "<data intelligence api key>",
"DI_ENV_MODE": "SaaS",
"LOG_FILE_PATH": "/tmp/di-mcp-server-logs"
}
}
}
}
http/https (Remote setup)
If the MCP server is running on a local/remote server in http/https mode.
For Cloud SaaS:
{
"servers": {
"wxdi-mcp-server": {
"url": "<url_to_mcp_server>",
"type": "http",
"headers": {
"x-api-key": "your api key from cloud SaaS"
}
}
}
}
For CPD:
{
"servers": {
"wxdi-mcp-server": {
"url": "<url_to_mcp_server>",
"type": "http",
"headers": {
"x-api-key": "your api key for cpd env",
"username": "<user name from cpd env>"
}
}
}
}
Watsonx Orchestrate
Watsonx Orchestrate + Data Intelligence blog post demonstrates how Watsonx Orchestrate integrates with the MCP Server for automation.
IBM Bob
IBM Bob + Data Intelligence blog post demonstrates how IBM Bob integrates with the MCP Server for automation.
Configuration
The MCP server can be configured using environment variables or a .env file. Copy .env.example to .env and modify the values as needed.
Client Settings
Below client settings are common whether http or stdio mode
| Environment Variable | Default | Description |
|---|---|---|
DI_SERVICE_URL |
None |
Base URL for Watsonx Data Intelligence instance. Example: api.dataplatform.cloud.ibm.com for SaaS and cluster url for CPD |
DI_ENV_MODE |
SaaS |
Environment mode (SaaS or CPD) |
REQUEST_TIMEOUT_S |
60 |
HTTP request timeout in seconds |
LOG_FILE_PATH |
None |
Logs will be written here if provided. Mandatory for stdio mode |
DI_CONTEXT |
df |
Context for URLs returned from tool responses ( df, cpdaas for DI_ENV_MODE=SaaS; df, cpd for DI_ENV_MODE=CPD ). url will be appended by query parameter accordingly.context=df in the url for example |
Below client settings are only applicable for stdio mode
| Environment Variable | Default | Description |
|---|---|---|
DI_APIKEY |
None |
API key for authentication |
DI_USERNAME |
None |
Username (required when using API key for CPD) |
DI_AUTH_TOKEN |
None |
Bearer token for alternative to API key |
For http/https mode client can send below headers
| Headers | Default | Description |
|---|---|---|
x-api-key |
None |
API key related to SaaS/CPD |
username |
None |
username for CPD env If API key is provided |
authorization |
None |
Bearer token alternative to apikey |
e.g:
{
"servers": {
"wxdi-mcp-server": {
"url": "<url_to_mcp_server>",
"type": "http",
"headers": {
"x-api-key": "your api key from cloud SaaS/cpd"
}
}
}
}
{
"servers": {
"wxdi-mcp-server": {
"url": "<url_to_mcp_server>",
"type": "http",
"headers": {
"authorization": "Bearer token"
}
}
}
}
SSL/TLS Configuration
If running in CPD environment, you might need to configure SSL certificate for client connection. Please look into SSL_CERTIFICATE_GUIDE.md for more details.
FAQ
Common questions
Discussion
Questions & comments · 0
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