Chat2DB

What is Chat2DB?

Chat2DB is an AI database client designed for developers, database administrators, analysts, and data teams. It combines traditional SQL editing, data management, and visualization functions with the ability to generate SQL statements in natural language, as well as query interpretation and optimization suggestions.

The Community version is designed with local priority in mind, and it can run on Windows, macOS, Linux, Docker, and command-line environments. The Business version adds features such as managed AI, account management, cloud storage, multi-device synchronization, and team governance to the same core infrastructure.

A one-sentence summary

Chat2DB is a cross-platform database tool that supports over 40 different databases, Text2SQL, data analysis, and integration with MCP agents.

Main functions

Multiple database connections

Chat2DB supports more than 40 different data sources, including MySQL, PostgreSQL, Oracle, SQL Server, ClickHouse, MongoDB, Redis, SQLite, MariaDB, TiDB, Hive, DB2, Snowflake, and BigQuery. New JDBC databases can also be added through configuration and drivers.

SQL Workspace

Users can edit, complete, format, execute, and save SQL queries, as well as view the history and execution results. Common queries can be organized by data source and project to avoid repeated typing.

Text2SQL

Users describe their query objectives in natural language, and the AI generates SQL statements based on the table structure. Before execution, it is still necessary to manually verify the tables, fields, connection conditions, filtering criteria, and write operations.

SQL Interpretation and Optimization

AI can interpret complex queries, provide suggestions for performance optimization, and assist in understanding execution plans. Optimization suggestions must be tested in a development environment; it is not possible to modify production indexes based solely on textual descriptions.

AI table creation and test data

Chat2DB can generate table creation statements and test data based on a business description, making it suitable for rapid prototyping. However, field types, constraints, indexes, character sets, and compliance requirements still need to be reviewed by database engineers.

Data management

Users can view metadata, manage tables and objects, edit data, and perform DDL and DML operations. Production connections should use accounts with the minimum required permissions to prevent accidental deletions or bulk updates.

Import and Export

The platform offers capabilities for data import, export, migration, and structure synchronization. Before migrating large tables, it is necessary to assess issues related to locking, transactions, character encoding, networking, and rollback strategies.

Charts and AI reports

The query results can be turned into charts, dashboards, and analysis reports; AI can also assist in interpreting trends. The calculation methods, time ranges, and handling of missing values in the reports require manual verification.

AI datasets

Users can create controlled datasets, allowing AI to conduct analyses based on specified tables and query ranges. Permission boundaries should be established at the database level, rather than relying solely on prompts.

CLI and MCP

Chat2DB CLI can read data sources, test connections, retrieve metadata, and execute SQL queries. The MCP endpoint allows agents such as Codex and Claude Code to utilize the local Chat2DB capabilities.

Examples of supported databases

Which users are it suitable for

• Developer: Writes, explains, and debugs SQL.
• Database administrator: Manages objects, permissions, execution plans, and data.
• Data analyst: Uses natural language to run queries and generate charts.
• Product and operations staff: Perform self-service analysis on controlled datasets.
• Data team: Shares connections, models, as well as the results of queries and analyses.
• AI developers: Use CLI and MCP to enable agents to access databases.

Version and package prices

As of August 24, 2026, Chat2DB offers a free Community version, as well as commercial plans named Starter, Pro, Team, and Enterprise. The prices listed on the pricing page may vary depending on whether payment is made on a monthly or annual basis or as part of a promotion; the final costs, including taxes, trial periods, renewals, and associated benefits, are indicated on the settlement page.

The annual subscription costs for Starter and Pro, as well as the price for Team plans, should be checked again before making a purchase, as the billing cycle may change on the page. The amounts of $9, $15, or other figures mentioned in older articles may correspond to previous pricing.

Differences between Community and Business versions

Installation and Getting Started Guide

1. Download the Community or Pro installation package from the system.
2. Create read-only or accounts with minimal permissions for databases.
3. Add a new data source by entering the host, port, database, and authentication details.
4. First perform a connection test, then browse the tables, fields, and indexes.
5. Run a read-only query in the SQL editor to verify the results and character encoding.
6. When AI is needed, either a custom model or a hosted commercial model can be configured.
7. Generate queries in simple, natural language, but check them first before executing.
8. Save frequently used SQL queries and assign distinct identifiers to production connections.

Precautions for Docker deployment

The Community version can be run using Docker; it requires Docker version 19.03 or higher, Compose version 2.0 or higher, as well as at least 2 CPU cores and 4 GB of memory. The application should be bound to the local loopback address only and not exposed directly to the public internet.

1. Generate and save the Community encryption key first.
2. Configure persistent volumes for application data.
3. Bind the service to the local address and a fixed port.
4. After it is started, access is possible only from the browser on the local machine.
5. The original encryption keys and data volumes are retained during the upgrade.
6. Regularly back up the connection configurations and essential SQL files.

If the encryption key is lost or replaced, the saved database passwords and AI model keys will no longer be accessible. Version 5.3.0 uses a separate data directory and does not automatically migrate data from older images.

Text2SQL usage tutorial

1. Select the correct data source, database, and Schema.
2. Only the tables and fields required for the task are made available.
3. Explain the indicators, dimensions, filters, and time range in one sentence.
4. Let AI generate SQL and check the connections and conditions one by one.
5. First, add a row limit and view the execution plan.
6. Execute in read-only accounts and test environments.
7. Verify the results before saving or generating charts.
8. Manual approval is required for updates and deletions.

MCP and agent access

Chat2DB CLI can start a local MCP endpoint, allowing external agents to list data sources, databases, schemas, and table structures; it also enables the use of Text2SQL for executing SQL queries. The actual list of available tools is determined by the local version.

MCP security rules

• Do not share MCP tokens, request headers, and client configurations.
• Create a read-only database account for generating queries.
• Restrict schemas, tables, and operations at the database layer.
• Check the data source, database, and statements before executing SQL.
• Limit the number of rows returned, execution time, and concurrency.
• Log agent calls, SQL queries, and approvers.
• The local MCP port should not be exposed to untrusted networks.

Product advantages

• Supports over 40 SQL and NoSQL databases.
• The database client and the AI assistant are integrated within the same workspace.
• The Community version is free and supports custom models.
• It covers SQL generation, interpretation, optimization, and reporting.
• It supports desktop, Docker, Web, CLI, and MCP.
• Local priority is given to a design that facilitates the control of connection information.
• The business version offers team collaboration and cloud synchronization.

Usage restrictions and precautions

• SQL generated by AI can be erroneous, inefficient, or contain destructive operations.
• The Community version does not have multiple user accounts or authorization boundaries.
• Custom JDBC drivers are executable code, and only trusted packages can be used.
• The imported configurations, SQL statements, database contents, and AI responses should all be regarded as untrusted input.
• Managed AI may send structures or prompts to external models.
• The degree of functionality provided by different database drivers may vary.
• Starting from 5.3.0, the license is no longer purely Apache 2.0.
• Team and private deployment features require a commercial plan.

Data security

The Community version stores the data source passwords and AI model keys locally, using an independent AES-265-GCM key for encryption with each installation. The Desktop mode can generate missing keys automatically, while the Web and console modes require explicit configuration.

Running locally does not mean that no data is transmitted outside. When using cloud-based large models, database proxies, synchronization, and team features, it is necessary to check the actual content that is transferred, the data areas involved, and the retention policies.

Database connection recommendations

• Different accounts are used for development, testing, and production.
• Read-only permissions are used by default, with access to specific schemas being restricted.
• Disable unnecessary permissions for creating, modifying, and deleting tables.
• Connect to remote databases via a secure network or tunnel.
• Connection details are not exposed in screenshots, logs, or feedback.
• Regularly rotate database passwords and model keys.
• Enable database auditing and backup for high-risk operations.

License and open-source status

The Chat2DB repository is made available to the public and open to contributions from the community, but the licenses vary depending on the version. For versions 5.3.0 and later, the source code is licensed under Apache 2.0 with certain conditions; it cannot therefore be simply classified as standard Apache open-source software.

Historical versions released prior to 5.3.0 are still governed by the Apache License 2.0. When enterprises plan to redistribute, host services, or make commercial modifications, they must read the full license text for that specific version.

Basic information

Frequently Asked Questions

Is Chat2DB free?

The Community version is free; it allows the use of local database clients as well as connections to one’s own AI models. Hosted AI, synchronization, and team features require a commercial subscription.

Which databases does Chat2DB support?

It supports over 40 data sources, including MySQL, PostgreSQL, Oracle, SQL Server, MongoDB, Redis, ClickHouse, and BigQuery, among others.

Can AI execute SQL directly?

It can be executed through the interface, CLI, or MCP, but write permissions cannot be granted without review. In a production environment, read-only accounts and manual approval are required.

Is Chat2DB open-source software?

It is necessary to distinguish between different versions: starting from 5.3.0, a license that includes additional conditions applies to the source code, while earlier versions remain under the Apache 2.0 license. The commercial version also offers closed-source features.

Which agents can be connected to MCP?

The document lists Codex, Claude Code, and other MCP clients. Once connected, the agent may read metadata or execute SQL queries, so it is necessary to restrict its permissions.

Where are the database passwords stored?

The Community version is stored locally and encrypted using an installation-level AES-265-GCM key. This key must be backed up securely, as lost credentials cannot be recovered.

Summary

Chat2DB is suitable for users who wish to manage multiple databases, generate SQL statements using AI, create analytical reports, and integrate agents within a single tool. Its Community version offers comprehensive functionality with a focus on local operation; however, aspects such as AI execution rights, Docker integration, encryption keys, and the limitations associated with the newer licenses require careful management.