Devart MCP Server for SQLite enables AI clients to interact with your data through a secure server running in your environment. It turns a regular AI chat into a practical way to work with real-world business data — and it is faster than conventional export or manual querying.
Devart MCP Server for SQLite allows you to:
- Work with data intuitively through natural language.
- Retrieve the required data for analysis within minutes.
- Report on your data faster with AI-powered assistance.
- Minimize manual data handling and integration maintenance.
Devart MCP Server for SQLite helps AI clients communicate directly with SQLite databases using natural-language prompts. It translates AI requests into structured queries, executes them through Devart connectivity drivers, and returns clean, structured results for seamless AI-powered data access.
To get started with Devart MCP Server for SQLite:
1. Download and install Devart ODBC Driver for SQLite.
2. Download and install Devart MCP Server for SQLite.
3. In Devart MCP Server for SQLite, configure your data connection and integration settings.
4. Run your first natural-language query.
Prerequisites
Before building and running Devart MCP Server for SQLite, ensure the following components are installed:
- .NET 8 SDK
- ADO.NET connection — Devart.AI.McpServer.AdoNet.Sqlite.csproj Devart dotConnect for SQLite (installed automatically via NuGet during build)
- ODBC connection — Devart.AI.McpServer.Odbc.Sqlite.csproj Devart ODBC Driver for SQLite (requires manual download and installation)
Step 1: Clone the repository
Clone the project repository and navigate to the project directory:
1. Open Command Prompt.
2. Enter the following command:
git clone https://github.com/devart-ai-connectivity/devart-mcp-server-sqlite.git
cd devart-mcp-server-sqliteStep 2: Build the MCP Server from source
You can build Devart MCP Server for SQLite from source using either of the supported database connectivity technologies: ADO.NET or ODBC.
- To build the MCP server with ADO.NET, run the following command:
dotnet publish Devart.AI.McpServer.AdoNet/Devart.AI.McpServer.AdoNet.Sqlite/Devart.AI.McpServer.AdoNet.Sqlite.csproj -c ReleaseSqlite /p:TargetFramework=net8.0The Devart dotConnect for SQLite NuGet package is downloaded and restored automatically.
- To build the MCP server with ODBC, select the command based on the bitness of your data source.
For 64-bit data source, run the following command:
dotnet publish Devart.AI.McpServer.Odbc/Devart.AI.McpServer.Odbc.Sqlite/Devart.AI.McpServer.Odbc.Sqlite.csproj -c ReleaseSqlite -r "win-x64" /p:TargetFramework=net8.0For 32-bit data source, run the following command:
dotnet publish Devart.AI.McpServer.Odbc/Devart.AI.McpServer.Odbc.Sqlite/Devart.AI.McpServer.Odbc.Sqlite.csproj -c ReleaseSqlite -r "win-x86" /p:TargetFramework=net8.0Note
The target platform must match the bitness of your ODBC data source.
Step 3: Configure the database connection for the MCP Server
1. Create an mcpserver.json configuration file in the directory containing the built MCP Server executable.
2. In the file, configure the database connection.
- Configure a connection with ADO.NET.
Add the following configuration to the mcpserver.json file:
{
"Connections": [
{
"Name": "my_sqlite",
"ConnectionString": "Server=localhost;User Id=sqlite;Password=your_password;Database=your_database;",
"ProtocolType": "stdio"
}
]
}- Configure a connection with ODBC.
Add the following configuration to the mcpserver.json file:
{
"Connections": [
{
"Name": "my_sqlite",
"DsnName": "your_dsn_name",
"ProtocolType": "stdio"
}
]
}- Configure a connection with ODBC using a connection string.
Add the following configuration to the mcpserver.json file:
{
"Connections": [
{
"Name": "my_sqlite",
"ConnectionString": "Driver={Devart ODBC Driver for SQLite};Server=localhost;User ID=sqlite;Password=your_password;Database=your_database;",
"ProtocolType": "stdio"
}
]
}where:
-
Name— The connection name. -
ConnectionString(applies to ADO.NET) — A database-specific connection string used to establish a connection to the target database. -
DsnName(applies to ODBC) — The name of your data source. -
ProtocolType— A transport protocol. The possible options are:stdioorhttp. -
HttpPort(required ifProtocolTypeis set tohttp) — The port number for thehttpprotocol.
Step 4: Run the MCP server
After you configure the MCP Server, you can start it.
Note
This step is required only when
ProtocolTypeis configured ashttp. If you use thestdiotransport protocol, your AI client starts the server automatically.
- To start the server with ADO.NET, run the following command:
Devart.AI.McpServer.AdoNet.Sqlite.exe run my_sqlite- To start the server with ODBC, run the following command:
Devart.AI.McpServer.Odbc.Sqlite.exe run my_sqlitewhere my_sqlite is the name of the ODBC connection.
Step 5: Integrate with Claude Desktop
1. Open claude_desktop_config.json, the Claude configuration file.
Tip
If you can't locate the configuration file, it may not exist yet. To create it, open Claude Desktop and navigate to File > Settings > Developer, then click Edit Config. The folder with the
claude_desktop_config.jsonfile opens.
2. Add one of the following objects, depending on the transport protocol used by MCP Server:
- STDIO
{
"mcpServers": {
"devart": {
"command": "C:\\path\\to\\Devart.AI.McpServer.AdoNet.Sqlite.exe",
"args": [
"run",
"my_sqlite"
]
}
}
}where:
-
devartis the connector name that will appear in Claude Desktop. -
C:\\path\\to\\Devart.AI.McpServer.AdoNet.Sqlite.exeis the path to the executable file. For an ODBC connection, useDevart.AI.McpServer.Odbc.Sqlite.exe. -
my_sqliteis the connection name specified in themcpserver.jsonconfiguration file. -
HTTP
"mcpServers": { "devart": { "command": "npx", "args": [ "-y", "mcp-remote", "http://localhost:5000/sse" ] } }
where:
devartis the connector name that will appear in Claude Desktop.5000is the MCP Server listening port.
3. Save the file.
4. Restart Claude Desktop.
Devart MCP Server for SQLite is now integrated with Claude, and devart appears in the Claude Desktop app in Customize > Connectors.
You can also integrate Devart MCP Server for SQLite with other AI clients such as Cline, Codex, Cursor, Visual Studio Code, Windsurf, Zed.
Devart MCP Server for SQLite supports integration with the following AI clients:
- Claude Desktop
- Visual Studio Code
- Cursor
- Codex
- Windsurf
- Cline
- Zed
- ...and other MCP-compatible AI clients
Devart MCP Server for SQLite is a practical fit for teams working with SQLite as their primary data source.
-
Mobile and desktop app data analysis
Query SQLite databases embedded in mobile applications or desktop tools to analyze user behavior, local state, cached data, and application logs. -
Development and testing data exploration
Let developers use AI to explore test datasets, seed data, and local development databases stored as SQLite files during development workflows. -
IoT and edge device data access
Analyze sensor readings, event logs, and telemetry data stored in SQLite on edge devices or IoT gateways without shipping data to the cloud. -
Embedded application reporting
Access operational data from applications that use SQLite as an internal data store, such as point-of-sale systems, field service tools, and kiosk software. -
Data science and notebook workflows
Connect AI tools to SQLite databases used in Python data science environments, Jupyter notebooks, and local analysis pipelines. -
Offline-first application analytics
Analyze data from offline-capable applications that sync or store locally in SQLite files, without requiring network access or cloud sync.
Devart MCP Server for SQLite is distributed as a free single-source MCP server.
To connect to SQLite, the server requires the corresponding Devart ODBC Driver for SQLite, which is a paid product.
A 30-day free trial is available for the Devart ODBC Driver for SQLite.
See the product page and documentation for the latest installation and activation details.



