Materialize (Streaming SQL DB) Connector for AI agents.
4 live capabilities
Manage streaming SQL databases and real-time data pipelines with natural language.
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Why people use Materialize (Streaming SQL DB)
Materialize for Managing Real-Time Data Pipelines
This Connector changes that by bringing your streaming database management directly into your AI agent. Instead of hunting for the right command or dashboard, you just tell your agent what you need. It handles the heavy lifting of interacting with your streaming infrastructure, so you can focus on the actual data.
What Vinkius changes
You get a natural language interface for your entire streaming SQL infrastructure.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Scaling for a traffic spike
An engineer sees a lag in data ingestion and asks the agent to use `create_cluster` to spin up an 'xl' instance.
- Real-world use case 02
Debugging a broken source
A data engineer asks the agent to `execute_sql` to `CREATE SOURCE` from a new Kafka topic to see if the connection works.
- Real-world use case 03
Morning health check
A DevOps lead asks the agent to `check_health` every morning to ensure all pipelines are operational.
Complete set · 4capabilities
The complete Materialize (Streaming SQL DB) capability set.
These are the exact actions your AI can choose when you ask it to work with Materialize (Streaming SQL DB).
01—04
4 capabilities in this set.
Part of 4 available through Materialize (Streaming SQL DB).
- 01 Capability
Execute sql
Run standard SQL or Materialize-specific commands on your live data feeds. This lets you interact with your streaming data without opening a separate editor.
- 02 Capability
Check health
Instantly check if your Materialize instance is healthy and running. This helps you monitor your pipeline status and spot issues before they cause downtime.
- 03 Capability
List clusters
Get a full list of all your available compute clusters in one go. This makes it easy to audit your environment and see what's currently running.
- 04 Capability
Create cluster
Create a new compute cluster with specific sizes like xs, s, m, l, or xl. This lets you scale your processing power instantly to handle data spikes.
Set up in minutes
One URL. Then ask Materialize (Streaming SQL DB) to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Materialize (Streaming SQL DB) 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_b3YATqNUmev2sLGakCv9DXqsXBiI2C8N6xSKsiWQ/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 Materialize (Streaming SQL DB), and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Materialize (Streaming SQL DB) for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_b3YATqNUmev2sLGakCv9DXqsXBiI2C8N6xSKsiWQ/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 Materialize (Streaming SQL DB) URL.
- Step 03
Save and start
Save the connection and enable Materialize (Streaming SQL DB) in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"materialize-streaming-sql-db": {
"url": "https://edge.vinkius.com/vk_preview_b3YATqNUmev2sLGakCv9DXqsXBiI2C8N6xSKsiWQ/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 Materialize (Streaming SQL DB)
Open Agent mode in chat and ask: "Using Materialize (Streaming SQL DB), help me...". 4 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"materialize-streaming-sql-db": {
"url": "https://edge.vinkius.com/vk_preview_b3YATqNUmev2sLGakCv9DXqsXBiI2C8N6xSKsiWQ/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 Materialize (Streaming SQL DB)
Ask Copilot: "Using Materialize (Streaming SQL DB), help me...". 4 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"materialize-streaming-sql-db": {
"url": "https://edge.vinkius.com/vk_preview_b3YATqNUmev2sLGakCv9DXqsXBiI2C8N6xSKsiWQ/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 Materialize (Streaming SQL DB)
Open Cascade and ask: "Using Materialize (Streaming SQL DB), help me...". 4 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"materialize-streaming-sql-db": {
"url": "https://edge.vinkius.com/vk_preview_b3YATqNUmev2sLGakCv9DXqsXBiI2C8N6xSKsiWQ/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 Materialize (Streaming SQL DB)
Ask Cline: "Using Materialize (Streaming SQL DB), help me...". 4 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add materialize-streaming-sql-db --transport http "https://edge.vinkius.com/vk_preview_b3YATqNUmev2sLGakCv9DXqsXBiI2C8N6xSKsiWQ/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 Materialize (Streaming SQL DB)
Ask Claude: "Using Materialize (Streaming SQL DB), show me...". 4 tools are ready
Where the request belongs
Work Materialize can move forward.
Data engineers and analytics folks who are tired of manual pipeline management. It's for the person who needs to see real-time data without the overhead of constant dashboard refreshing.
Data Engineer
Manages materialized views and sources via natural language to keep data flowing.
Analytics Engineer
Verifies pipeline health and inspects clusters during the development process.
DevOps Engineer
Automates resource scaling and monitors instance availability to ensure uptime.
Build the capability set
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Bring your own AI
Change the model, client or framework. Keep Materialize connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
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Cline -
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Before you connect
Questions about Materialize.
The practical details behind the request, access and result.
What can the Materialize MCP do for my data engineering workflow?
It lets you manage your streaming database using natural language. You can run SQL, manage clusters, and check health without leaving your agent's chat window.
Can I use the Materialize MCP to run SQL on live Kafka streams?
Yes, you can use it to execute SQL commands like creating sources from Kafka topics, allowing you to interact with your live data feeds immediately.
How does the Materialize MCP help with scaling my compute resources?
It allows you to spin up new compute clusters with specific sizes like 'm' or 'xl' on the fly, making it easy to handle traffic spikes without manual setup.
Is the Materialize MCP good for monitoring my database health?
It's perfect for quick health checks. You can ask your agent to verify the status of your instance at any time to ensure your pipelines are running smoothly.
Can I manage multiple Materialize clusters with this Connector?
Yes, you can use it to list all your available compute clusters, giving you a clear overview of your entire streaming SQL environment in one place.
How do I connect the Materialize MCP to my AI agent?
You just need to subscribe to the Connector and provide your Materialize API Key. From there, your agent can handle all your streaming SQL tasks.
Can I create a new materialized view using this server?
Yes. You can use the execute_sql capability to run any valid Materialize SQL command, including CREATE MATERIALIZED VIEW to start processing your data streams in real-time.
How do I scale my compute resources through the AI?
You can use the create_cluster capability and specify a size (xs, s, m, l, or xl). This allows you to provision new compute capacity directly through the conversation.
Is there a way to check if my Materialize instance is currently reachable?
Yes, the check_health capability is designed specifically for this. It returns the current status of your instance to confirm it is operational.
One connection away
Give your agent a direct line to Materialize.
Connect Materialize once. Keep it beside 5,900+ managed Connectors when the next task needs more.
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