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LibreChat is an open-source, self-hosted AI chat platform that brings together multiple LLM providers, agents, and assistants behind a single interface. It also supports the Model Context Protocol (MCP), so you can connect external tools and data sources directly to the chat and pull in live data from the systems you already work with.
By integrating LibreChat with CData Connect AI through the built-in MCP Server, LibreChat gains governed, real-time access to live Presto data. This enables you to list catalogs, explore schemas, and query records from Presto data using natural language prompts, with all data access running securely against authorized sources.
This article explains how to configure Presto connectivity in Connect AI, generate the required personal access token, install LibreChat, register the Connect AI MCP Server, configure an LLM provider, and verify the integration by querying live Presto data from the LibreChat interface.
Accessing and integrating live data from Trino and Presto SQL engines has never been easier with CData. Customers rely on CData connectivity to:
Presto and Trino allow users to access a variety of underlying data sources through a single endpoint. When paired with CData connectivity, users get pure, SQL-92 access to their instances, allowing them to integrate business data with a data warehouse or easily access live data directly from their preferred tools, like Power BI and Tableau.
In many cases, CData's live connectivity surpasses the native import functionality available in tools. One customer was unable to effectively use Power BI due to the size of the datasets needed for reporting. When the company implemented the CData Power BI Connector for Presto they were able to generate reports in real-time using the DirectQuery connection mode.
Connectivity to Presto from LibreChat is made possible through Connect AI's Remote MCP Server. To interact with Presto data from LibreChat, start by creating and configuring a Presto connection in Connect AI.
Set the Server and Port connection properties to connect, in addition to any authentication properties that may be required.
To enable TLS/SSL, set UseSSL to true.
In order to authenticate with LDAP, set the following connection properties:
In order to authenticate with KERBEROS, set the following connection properties:
A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from LibreChat. It is best practice to create a separate PAT for each integration to maintain granular access control.
With the Presto connection configured and a PAT generated, LibreChat can now connect to Presto data through Connect AI.
Next, install LibreChat locally and configure the Connect AI Remote MCP Server so that the chat interface can discover and call live data tools through Connect AI.
Note: LibreChat will use Basic authentication with Connect AI. Combine your Connect AI user email and the PAT you created earlier in the format email:PAT, then base64 encode the combined string and paste it in the API Key field. For example, [email protected]:ABC123...XYZ789 base64-encoded becomes something like: dXNlckBkb21haW4uY29tOkFCQzEyMy4uLlhZWjc4OQ==
π Configuring the Connect AI MCP ServerLibreChat requires at least one LLM provider to power the chat. Enable the MCP server in the chat input and add an API key for your preferred provider so the model can interpret prompts and call MCP tools through Connect AI.
With the MCP server and an LLM provider configured, LibreChat is ready to query live Presto data through Connect AI.
With the integration complete, use the LibreChat chat input to interact with live Presto data through natural language prompts handled by the configured LLM.
At this point, your LibreChat instance communicates with the Connect AI MCP Server and retrieves live Presto data through remote MCP tools directly from the chat interface.
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