Already using CData Drivers with BI tools, ETL pipelines, or custom applications? Add CData MCP Server for instant schema discovery and AI-assisted query building.
MCP Server
Build Data-Driven Applications with AI—Not Guesswork
No more digging through API docs. CData MCP Server gives AI coding tools direct access to your schemas—generate production-ready queries and application code in minutes.
Free for development. No trial period. No credit card required.
Supported AI Coding Tools
Unmatched productivity with reliable results—AI validates against your real data model
10x faster development—because AI understands your actual data structure before writing a single line of code.
- Schema-aware code generation: AI understands your exact table structures, column types, and relationships
- Validated SQL syntax: Queries tested against live connections before integration into your application
- CData Driver compatibility: Generated queries and code that work identically with JDBC, ADO.NET, ODBC and Python Drivers
- Production-ready applications: From prototype to deployment without rewriting
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Context is everything: AI + MCP
Why this works better than AI guessing API docs and failing every time
Generic AI guesses
This architecture is constrained by how data systems actually behave.
- MCP provides real schema and data from Systems
- No more guessing API calls with wrong parameters or invented field names
- Outputs are deterministic and testable
Works in real environments
You stay in control. The system removes the guesswork.
- Compatible with CData JDBC, ADO.NET, ODBC and Python Drivers
- Supports enterprise auth, TLS, proxies, and OS differences
- Designed for local dev, CI and production workflows
What teams see after adopting it
Measurable impact from day one
- Faster time to first working integration
- Fewer production surprises
- Less time lost to configuration debugging
- Fewer repetitive support questions
// Generic AI might generate this: // Wrong: "AccountName" doesn't exist cursor.execute("SELECT AccountName, Total FROM Accounts") // With CData MCP Server: // Correct: AI knows the schema cursor.execute("SELECT [Name], [AnnualRevenue] FROM [Account] WHERE [Type] = 'Customer'") // Wrong: AI guesses "Closed" — the picklist value is "Closed Won" String sql = "SELECT Name, Amount FROM Opportunity WHERE StageName = 'Closed'"; // Correct: Claude sees Stage picklist values from Salesforce metadata String sql = "SELECT [Name], [Amount] FROM [Opportunity] WHERE [StageName] = 'Closed Won'";
AI connects, explores, ships. You just direct.
Build with MCP Server. Deploy with CData Drivers.
Provide:
- Data source connection via the MCP Server UI
Get:
- Schema discovery from a live connection to your source
- Standardized SQL and Stored Procedure access
Provide:
- Natural language queries
- Prompts for application code requirements
Get:
- Accurate queries based on live-schema from the source
- Precise filtering and JOINs by retrieving sample values, picklist values
- Validation during exploration, no guessing
- Executable code for your data-driven applications
- Schema and syntax parity between MCP and CData Drivers in production
- Standardize integration patterns across services and teams
# AI helped write this. No AI runs it. import cdata.salesforce as sf conn = sf.connect("User=...;Password=...") cursor = conn.cursor() cursor.execute(""" SELECT Id, Name, Industry, AnnualRevenue FROM Account WHERE AnnualRevenue > 1000000 ORDER BY AnnualRevenue DESC """) for row in cursor.fetchall(): process_account(row) # Runs as scheduled job, cron, or service # No LLM. No tokens. Just reliable execution.
Your path to AI-assisted development
CData Driver Users
ISV Partners with Embedded Drivers
Embedding CData Drivers into your platform? Accelerate connector development and QA with AI-assisted schema validation.
AI-First Developers
AI coding tools are powerful, but they are limited by what they can see. CData MCP Server provides AI with conversational access to schema metadata and live data.
With AI coding tools and CData MCP Server, you can…
Your Java, .NET, C/C++, Go, Node.js, PHP, or Python application can now interact with Salesforce, Dynamics 365, or SAP data faster than ever. The biggest challenges in data-driven application development were schema discovery and query tuning. AI can handle that.
Test JOINs, filters, and aggregations in your AI coding environment. Validated queries integrate directly into your applications without modification.
Generate scripts that query, transform, and sync data to your warehouse. Built-in support for incremental updates across data sources.
