Tableau CRM Analytics MCP Server by CData

Enables querying ADP data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Airtable data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Amazon DynamoDB data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Amazon S3 data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Asana data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Basecamp data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying BigCommerce data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Bitbucket data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Box data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Confluence data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Couchbase data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Databricks data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Dropbox data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying eBay data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Elasticsearch data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying EnterpriseDB data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Facebook data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying GitHub data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Gmail data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Google Ads data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Google Analytics data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Google Calendar data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Google Campaign Manager 360 data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Google Cloud Storage data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Google Drive data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Google Sheets data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying GraphQL data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Greenhouse data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Hive data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying HubSpot data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Instagram data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Jira data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying MailChimp data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying MariaDB data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying MongoDB data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying MYOB data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying MySQL data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Neo4j data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Odoo data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Okta data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying PayPal data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Pinterest data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying PostgreSQL data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Presto data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying QuickBooks data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Redis data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying RSS data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Sage data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Salesforce data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying SAP data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying SendGrid data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Shopify data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying SingleStore data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Slack data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Snapchat data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Snowflake data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Splunk data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Square data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Stripe data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying SurveyMonkey data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Teradata data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Trello data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Trino data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Twilio data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying WooCommerce data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying WordPress data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Xero data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying XML data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying YouTube Analytics data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Zendesk data sources by exposing them as relational SQL models that can be accessed through natural language queries.

Enables querying Zoho data sources by exposing them as relational SQL models that can be accessed through natural language queries.

tableau-crm-analytics-mcp-server-by-cdata

CData's Model Context Protocol (MCP) Server for Tableau CRM Analytics

: This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Tableau CRM Analytics (beta).

Purpose

We created this read-only MCP Server to allow LLMs (like Claude Desktop) to query live data Tableau CRM Analytics supported by the CData JDBC Driver for Tableau CRM Analytics.

CData JDBC Driver connects to Tableau CRM Analytics by exposing them as relational SQL models.

This server wraps that driver and makes Tableau CRM Analytics data available through a simple MCP interface, so LLMs can retrieve live information by asking natural language questions — no SQL required.

Setup Guide

Clone the repository:
git clone https://github.com/cdatasoftware/tableau-crm-analytics-mcp-server-by-cdata.git cd tableau-crm-analytics-mcp-server-by-cdata
Build the server:
mvn clean install
This creates the JAR file: CDataMCP-jar-with-dependencies.jar
Download and install the CData JDBC Driver for {source}: https://www.cdata.com/drivers/tableaucrm/download/jdbc
License the CData JDBC Driver:
- Navigate to the lib folder in the installation directory, typically:
  - (Windows) C:\Program Files\CData\CData JDBC Driver for Tableau CRM Analytics\
  - (Mac/Linux) /Applications/CData JDBC Driver for Tableau CRM Analytics/
- Run the command java -jar cdata.jdbc.tableaucrmanalytics.jar --license
- Enter your name, email, and "TRIAL" (or your license key).
Configure your connection to the data source (Salesforce as an example):
- Run the command java -jar cdata.jdbc.tableaucrmanalytics.jar to open the Connection String utility.
- Configure the connection string and click "Test Connection"
  Note: If the data sources uses OAuth, you will need to authenticate in your browser.
- Once successful, copy the connection string for use later.
Create a .prp file for your JDBC connection (e.g. tableau-crm-analytics.prp) using the following properties and format:
- Prefix - a prefix to be used for the tools exposed
- ServerName - a name for your server
- ServerVersion - a version for your server
- DriverPath - the full path to the JAR file for your JDBC driver
- DriverClass - the name of the JDBC Driver Class (e.g. cdata.jdbc.tableaucrmanalytics.TableauCRMAnalyticsDriver)
- JdbcUrl - the JDBC connection string to use with the CData JDBC Driver to connect to your data (copied from above)
- Tables - leave blank to access all data, otherwise you can explicitly declare the tables you wish to create access for
  Prefix=tableaucrmanalytics ServerName=CDataTableauCRMAnalytics ServerVersion=1.0 DriverPath=PATH\TO\cdata.jdbc.tableaucrmanalytics.jar DriverClass=cdata.jdbc.tableaucrmanalytics.TableauCRMAnalyticsDriver JdbcUrl=jdbc:tableaucrmanalytics:InitiateOAuth=GETANDREFRESH; Tables=

Using the Server with Claude Desktop

Create the config file for Claude Desktop ( claude_desktop_config.json) to add the new MCP server, using the format below. If the file already exists, add the entry to the mcpServers in the config file. Windows
{ "mcpServers": { "{classname_dash}": { "command": "PATH\\TO\\java.exe", "args": [ "-jar", "PATH\\TO\\CDataMCP-jar-with-dependencies.jar", "PATH\\TO\\tableau-crm-analytics.prp" ] }, ... } }
Linux/Mac
{ "mcpServers": { "{classname_dash}": { "command": "/PATH/TO/java", "args": [ "-jar", "/PATH/TO/CDataMCP-jar-with-dependencies.jar", "/PATH/TO/tableau-crm-analytics.prp" ] }, ... } }
If needed, copy the config file to the appropriate directory (Claude Desktop as the example). Windows
cp C:\PATH\TO\claude_desktop_config.json %APPDATA%\Claude\claude_desktop_config.json
Linux/Mac
cp /PATH/TO/claude_desktop_config.json /Users/{user}/Library/Application\ Support/Claude/claude_desktop_config.json'
Run or refresh your client (Claude Desktop).

Note: You may need to fully exit or quit your Claude Desktop client and re-open it for the MCP Servers to appear.

Running the Server

Run the follow the command to run the MCP Server on its own
java -jar /PATH/TO/CDataMCP-jar-with-dependencies.jar /PATH/TO/Salesforce.prp > **Note:** The server uses `stdio` so can only be used with clients that run on the same machine as the server.

Usage Details

Once the MCP Server is configured, the AI client will be able to use the built-in tools to read, write, update, and delete the underlying data. In general, you do not need to call the tools explicitly. Simply ask the client to answer questions about the underlying data system. For example:

"What is the correlation between my closed won opportunities and the account industry?"
"How many open tickets do I have in the SUPPORT project?"
"Can you tell me what calendar events I have today?"

The list of tools available and their descriptions follow:

Tools & Descriptions

In the definitions below, {servername} refers to the name of the MCP Server in the config file (e.g. {classname_dash} above).

{servername}_get_tables - Retrieves a list of tables available in the data source. Use the {servername}_get_columns tool to list available columns on a table. The output of the tool will be returned in CSV format, with the first line containing column headers.
{servername}_get_columns - Retrieves a list of columns for a table. Use the {servername}_get_tables tool to get a list of available tables. The output of the tool will be returned in CSV format, with the first line containing column headers.
{servername}_run_query - Execute a SQL SELECT query

JSON-RPC Request Examples

If you are scripting out the requests sent to the MCP Server instead of using an AI Client (e.g. Claude), then you can refer to the JSON payload examples below – following the JSON-RPC 2.0 specification - when calling the available tools.

source_get_tables

{
    "jsonrpc": "2.0",
    "id": 1,
    "method": "tools/call",
    "params": {
        "name": "source_get_tables",
        "arguments": {}
    }
}

source_get_columns

{
    "jsonrpc": "2.0",
    "id": 2,
    "method": "tools/call",
    "params": {
        "name": "source_get_columns",
        "arguments": {
            "table":  "Account"
        }
    }
}

source_run_query

{
    "jsonrpc": "2.0",
    "id": 3,
    "method": "tools/call",
    "params": {
        "name": "source_run_query",
        "arguments": {
            "sql":  "SELECT * FROM [Account] WHERE [IsDeleted] = true"
        }
    }
}

Troubleshooting

If you cannot see your CData MCP Server in Claude Desktop, be sure that you have fully quit Claude Desktop (Windows: use the Task Manager, Mac: use the Activity Monitor)
If Claude Desktop is unable to retrieve data, be sure that you have configured your connection properly. Use the Connection String builder to create the connection string (see above) and copy the connection string into the property (.prp) file.
If you are having trouble connecting to your data source, contact the CData Support Team.
If you are having trouble using the MCP server, or have any other feedback, join the CData Community.

License

This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.

All Supported Sources

This server cannot be installed

security - not tested

license - permissive license

quality - not tested

How are these scores calculated?

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Tableau CRM Analytics (beta): https://www.cdata.com/download/download.aspx?sku=FSZK-V&type=beta

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