MindsDB (AI Database & Predictors) Connector for AI agents.
6 live capabilities
Manage machine learning models and predictive analytics through SQL.
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Why people use MindsDB (AI Database & Predictors)
MindsDB for Automated ML Model Management
This Connector changes that by putting your entire ML lifecycle into a single conversation. You can trigger model creation, check training stats, and run live predictions using natural language. You get the results you need without the tab-switching fatigue.
What Vinkius changes
You get a direct line between your AI agent and your full machine learning pipeline.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Monitoring training progress
A Data Scientist needs to know if a model is done training.
- Real-world use case 02
Adding price predictors to apps
A developer wants to add a price predictor to a web app.
- Real-world use case 03
Generating forward-looking reports
A BI analyst needs a report on next week's stock.
Complete set · 6capabilities
The complete MindsDB (AI Database & Predictors) capability set.
These are the exact actions your AI can choose when you ask it to work with MindsDB (AI Database & Predictors).
01—03
3 capabilities in this set.
Part of 6 available through MindsDB (AI Database & Predictors).
- 01 Capability
List databases
See all external databases like Snowflake or Postgres connected to MindsDB. This helps you audit your data pipeline boundaries.
- 02 Capability
Execute sql query
Run SQL commands like CREATE MODEL or SELECT...PREDICT on your data. It lets you trigger model training and get live predictions in one step.
- 03 Capability
List views
See all virtual data views and SQL mappings in a specific project. Use this to find pre-built data transformations instead of writing new ones.
04—06
3 capabilities in this set.
Part of 6 available through MindsDB (AI Database & Predictors).
- 04 Capability
List models
View all trained AI tables and models ready for querying in a project. Use this to check which algorithms are finished training.
- 05 Capability
Get model
Fetch a specific trained AI prediction engine to see its details. This helps you identify which models are ready for production.
- 06 Capability
Get status
Check the current health and version of your MindsDB cluster. Use this to verify your environment is active and up to date.
Set up in minutes
One URL. Then ask MindsDB (AI Database & Predictors) to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use MindsDB (AI Database & Predictors) from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_wo8z4btUozCcWNcaSyNerjmMILAoiY0Mm4LOh9m9/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it MindsDB (AI Database & Predictors), and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable MindsDB (AI Database & Predictors) for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_wo8z4btUozCcWNcaSyNerjmMILAoiY0Mm4LOh9m9/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the MindsDB (AI Database & Predictors) URL.
- Step 03
Save and start
Save the connection and enable MindsDB (AI Database & Predictors) in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"mindsdb-ai-database-predictors": {
"url": "https://edge.vinkius.com/vk_preview_wo8z4btUozCcWNcaSyNerjmMILAoiY0Mm4LOh9m9/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using MindsDB (AI Database & Predictors)
Open Agent mode in chat and ask: "Using MindsDB (AI Database & Predictors), help me...". 6 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"mindsdb-ai-database-predictors": {
"url": "https://edge.vinkius.com/vk_preview_wo8z4btUozCcWNcaSyNerjmMILAoiY0Mm4LOh9m9/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using MindsDB (AI Database & Predictors)
Ask Copilot: "Using MindsDB (AI Database & Predictors), help me...". 6 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"mindsdb-ai-database-predictors": {
"url": "https://edge.vinkius.com/vk_preview_wo8z4btUozCcWNcaSyNerjmMILAoiY0Mm4LOh9m9/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using MindsDB (AI Database & Predictors)
Open Cascade and ask: "Using MindsDB (AI Database & Predictors), help me...". 6 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"mindsdb-ai-database-predictors": {
"url": "https://edge.vinkius.com/vk_preview_wo8z4btUozCcWNcaSyNerjmMILAoiY0Mm4LOh9m9/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using MindsDB (AI Database & Predictors)
Ask Cline: "Using MindsDB (AI Database & Predictors), help me...". 6 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add mindsdb-ai-database-predictors --transport http "https://edge.vinkius.com/vk_preview_wo8z4btUozCcWNcaSyNerjmMILAoiY0Mm4LOh9m9/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using MindsDB (AI Database & Predictors)
Ask Claude: "Using MindsDB (AI Database & Predictors), show me...". 6 tools are ready
Where the request belongs
Work MindsDB can move forward.
This is for the data professional who's tired of context-switching between SQL editors, ML platforms, and notebooks just to see if a model is actually working.
Data Scientist
Monitors model training progress and tests predictor accuracy using natural language.
Software Developer
Integrates AI predictions into applications by querying the MindsDB SQL interface directly.
BI Analyst
Combines historical data with future forecasts in a single SQL query to build better reports.
Build the capability set
Add more capabilities.
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Bring your own AI
Change the model, client or framework. Keep MindsDB connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
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Warp -
Amazon Q -
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AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about MindsDB.
The practical details behind the request, access and result.
Can I use the MindsDB MCP to train new models?
Yes, you can use the Connector to trigger 'CREATE MODEL' commands via SQL. This lets your agent start the training process for you based on the data sources you've already connected.
Does the MindsDB MCP support Snowflake and Postgres?
Yes, it allows you to see and interact with any external databases you've connected to MindsDB, including Snowflake, PostgreSQL, and ClickHouse.
How do I run a prediction using this Connector?
You can simply ask your agent to run a SELECT statement that includes a PREDICT clause. It will query your trained models and return the results directly in the chat.
Can I see my model training progress?
Yes, you can ask the agent to list your models. It will show you which ones are complete and provide status updates on those currently in the training phase.
Is the MindsDB MCP good for BI reporting?
It's great for BI because it lets you combine historical data and future predictions in a single query, making it much faster to generate forward-looking reports.
How do I keep my queries from crashing the agent?
When running large queries, just ask your agent to include a LIMIT clause. This ensures the results stay within the context limits while still giving you the data you need.
Can I train a machine learning model using SQL through my agent?
Yes. Use the execute_sql_query capability with the 'CREATE MODEL' statement. Your agent will dispatch the command to MindsDB, which will automatically handle the data processing and training of your predictor asynchronously.
How do I connect an external database like PostgreSQL to MindsDB using the agent?
The execute_sql_query capability supports the 'CREATE DATABASE' syntax. You can command your agent to link a new data source by providing the connection parameters, allowing MindsDB to query your existing data natively.
Can my agent retrieve the status of an ongoing model training?
Absolutely. Use the get_model capability by providing the model name and project. Your agent will report the current training state, accuracy metrics, and any errors encountered during the AI generation process.
One connection away
Give your agent a direct line to MindsDB.
Connect MindsDB once. Keep it beside 5,900+ managed Connectors when the next task needs more.
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