ml-matrix Connector for AI agents.
1 live capability
Perform exact linear algebra and matrix math on large datasets.
Waiting for input…
Why people use ml-matrix
Matrix Operations Engine for Accurate Data Science Math
This Connector removes the guesswork. Your agent handles the data while the engine does the heavy lifting. You get a perfect result every time, regardless of how large the matrix is.
What Vinkius changes
Your AI gets a calculator that actually works for complex math.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
Validating model weights
A researcher asks the agent to multiply weight matrices and it returns the exact result without rounding errors.
- Real-world use case 02
Solving linear systems
A developer needs to find the inverse of a 10x10 matrix to solve Ax = b and gets the precise result.
- Real-world use case 03
Covariance analysis
A data scientist checks if a matrix is positive semi-definite by calculating the determinant.
Complete set · 1capability
The complete ml-matrix capability set.
These are the exact actions your AI can choose when you ask it to work with ml-matrix.
01
1 capability in this set.
Part of 1 available through ml-matrix.
- 01 Capability
Matrix operations
Perform exact matrix math like multiplication, addition, and inversion. This ensures your agent never hallucinates numbers in linear algebra tasks.
Set up in minutes
One URL. Then ask ml-matrix to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use ml-matrix 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_oQQkbQtJwMZBVl9Z7lHUjKWiTSyD5U3beNbMernJ/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 ml-matrix, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable ml-matrix for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_oQQkbQtJwMZBVl9Z7lHUjKWiTSyD5U3beNbMernJ/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 ml-matrix URL.
- Step 03
Save and start
Save the connection and enable ml-matrix in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"matrix-operations-engine": {
"url": "https://edge.vinkius.com/vk_preview_oQQkbQtJwMZBVl9Z7lHUjKWiTSyD5U3beNbMernJ/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 ml-matrix
Open Agent mode in chat and ask: "Using ml-matrix, help me...". 1 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"matrix-operations-engine": {
"url": "https://edge.vinkius.com/vk_preview_oQQkbQtJwMZBVl9Z7lHUjKWiTSyD5U3beNbMernJ/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 ml-matrix
Ask Copilot: "Using ml-matrix, help me...". 1 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"matrix-operations-engine": {
"url": "https://edge.vinkius.com/vk_preview_oQQkbQtJwMZBVl9Z7lHUjKWiTSyD5U3beNbMernJ/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 ml-matrix
Open Cascade and ask: "Using ml-matrix, help me...". 1 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"matrix-operations-engine": {
"url": "https://edge.vinkius.com/vk_preview_oQQkbQtJwMZBVl9Z7lHUjKWiTSyD5U3beNbMernJ/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 ml-matrix
Ask Cline: "Using ml-matrix, help me...". 1 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add matrix-operations-engine --transport http "https://edge.vinkius.com/vk_preview_oQQkbQtJwMZBVl9Z7lHUjKWiTSyD5U3beNbMernJ/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 ml-matrix
Ask Claude: "Using ml-matrix, show me...". 1 tools are ready
Where the request belongs
Work ml-matrix can move forward.
Data scientists and ML engineers who need to perform high-precision linear algebra on large datasets without risking the hallucinations or privacy leaks common in standard LLM math.
Data Scientist
Checking if a covariance matrix is positive semi-definite for a new research paper.
ML Engineer
Validating weight matrices in a production pipeline to ensure no rounding errors occur during inference.
Research Scientist
Solving complex linear systems for engineering simulations where precision is non-negotiable.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse ConnectorsFundamental Math
A deterministic, zero-latency mathematical engine for exact calculations. Safely compute percentages, square roots, factorials, and the rule of three completely local.
Newton
Perform advanced symbolic mathematics—simplify expressions, calculate derivatives, find integrals, and solve equations directly through your AI agent.
Math Evaluation Engine
Stop LLMs from hallucinating math. Evaluate complex mathematical expressions and handle exact float rounding deterministically.
Advanced Math Evaluator
Evaluate complex mathematical expressions. derivatives, complex numbers, parametric equations. deterministically using Math.js. Zero LLM guessing.
Matrix 4x4 Transforms
Create, compose, and apply 3D transformation matrices with rotation representations and coordinate transformations for graphics and simulation applications.
Deterministic Math Expression Evaluator
Equip your AI with flawless algebraic parsing. Safely evaluate complex mathematical string expressions without using vulnerable `eval()` execution.
Bring your own AI
Change the model, client or framework. Keep ml-matrix connected.
-
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 -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about ml-matrix.
The practical details behind the request, access and result.
Can the Matrix Operations Engine MCP handle large matrices?
Yes, it is designed to handle massive 2D arrays. It processes the math on your local CPU, so it isn't limited by the AI's context window or reasoning capabilities.
Does the Matrix Operations Engine MCP keep my data private?
Yes, all calculations happen locally on your machine. Your sensitive weight matrices and embeddings never leave your environment, making it safe for proprietary data.
How does the Matrix Operations Engine MCP prevent hallucinations?
It replaces the AI's pattern-based guessing with a dedicated linear algebra engine. This ensures that every multiplication, inversion, and determinant is mathematically perfect.
Can I use the Matrix Operations Engine MCP for data science?
It is a core capability for data science. It provides the precision needed for covariance analysis, weight validation, and solving linear systems in research and production.
Does the Matrix Operations Engine MCP work with Claude and Cursor?
Yes, it works with any MCP-compatible client, including Claude, Cursor, and Windsurf. You can connect it via Vinkius and start using it immediately.
What happens if I try to invert a singular matrix?
The engine throws a deterministic mathematical error that the AI will report to you, instead of hallucinating fake numbers. This is by design. fail loud, not wrong.
Is there a size limit for the matrices?
The engine handles very large matrices natively. The practical limit is your LLM's context window for serializing the JSON payload of the matrix data.
Can I use it for dot products between 1D vectors?
Yes! Treat your 1D vectors as 1xN and Nx1 matrices, then use the 'multiply' operation to get the exact dot product result.
One connection away
Give your agent a direct line to ml-matrix.
Connect ml-matrix once. Keep it beside 6,100+ managed Connectors when the next task needs more.
Explore every Connector No credit card required · Free tier available