Lakelogic MCP

Name: Lakelogic MCP
Author: LakeLogic

by LakeLogicversion 0.1.4i★ –iRuns on your computer

Registry nameio.github.LakeLogic/lakelogic-mcp

Install

Overview

Description from the maker (original English)

Validate, lint, test-run and explain Open Lakehouse Contracts with LakeLogic, from any AI assistant.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "lakelogic": {
      "command": "uvx",
      "args": [
        "lakelogic-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add lakelogic -- uvx lakelogic-mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "lakelogic": {
      "command": "uvx",
      "args": [
        "lakelogic-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "lakelogic": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "lakelogic-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account LakeLogic, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

More stars than 0% of the other 32558 servers in this category
Published to the registry more recently than 78% of the other 32558 servers in this category
Basic checks equal to or better than 100% of the other 32558 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Lakelogic MCP safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.4) reached the registry 9 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, FactLot

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

LakeLogic MCP

mcp-name: io.github.LakeLogic/lakelogic-mcp

Help AI assistants check and test data contracts locally.

Validate Open Lakehouse Contracts (OLC), find governance gaps, explain rules and generate sample data. Test-run contracts with LakeLogic Core using Polars or DuckDB, then inspect accepted rows, failed rows and the reasons they failed.

Works with MCP-compatible assistants — Claude Code, Claude Desktop, Cursor and others. No LakeLogic account required.

OLC defines the contract. Core executes it. MCP gives your assistant access to those tools.

📖 Documentation: https://mcp.lakelogic.io/

Example

*"Check orders.yaml, explain any findings, generate sample data and test it locally."*

The assistant validates the contract, lints it, explains each finding, writes test data shaped by the contract, runs it, and reports which rows passed and why the others failed — real results from LakeLogic, not plausible-looking YAML.

Tools

Tool	Answers
`validate_contract`	Does it match the OLC model? Each error's location and problem
`lint_contract`	Does it pass the lint checks? Governance findings, each with its fix
`explain_rule`	Why does a lint rule exist? What it checks, why it matters, a failing and a fixed contract
`contract_reference`	How is one part of a contract written? (`anatomy`, `quality`, `materialization`, …)
`export_odcs`	The contract as an Open Data Contract Standard document
`generate_test_data`	Synthetic data shaped by the contract, with a share of rows that deliberately break its rules
`run_contract`	How many rows pass, how many fail, and why (Polars or DuckDB, on a local file)

Details and inputs: Tools. A first run, start to finish: Walkthrough.

Install

All clients need uv on your PATH. Start your assistant in the project that holds your contracts (or pass --root ).

Claude Code — as a plugin:

/plugin marketplace add LakeLogic/lakelogic-mcp

/plugin install lakelogic-mcp@lakelogic-mcp

or directly: claude mcp add lakelogic -- uvx lakelogic-mcp

Cursor: Add to Cursor

Claude Desktop, VS Code and other MCP clients — add to the client's MCP settings:

"mcpServers": { "lakelogic": { "command": "uvx", "args": ["lakelogic-mcp", "--root", "/path/to/your/contracts/project"] } } }

It is listed in the official MCP Registry as io.github.LakeLogic/lakelogic-mcp.

Safety and privacy

Local. The server talks to your client over stdio; it opens no network connection itself, needs no account and sends no telemetry. (Installing with uvx downloads the package, as any install does.)
Tool paths stay in your project. Every path you give a tool, and the _domain.yaml / _system.yaml that lint takes into account, must be inside the project folder. Files a contract itself names (a links: dataset, for example) are read by Core as written.
Running a contract does what the contract configures. If a contract declares notifications or run-log delivery, LakeLogic Core may send them during run_contract. Nothing is written to the contract's target.
Results reach your AI provider. Tool results go into the assistant's context: quarantined sample rows, failure reasons (which can quote your data) and the contract itself. sample: 0 removes only the rows, so test with generated data if a file holds personal or confidential data.

More: Safety and privacy.

Contributing

To work on the server from a checkout, see Development.

Lakelogic MCP

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

FactLot

README from the maker

LakeLogic MCP

Example

Tools

Install

Safety and privacy

Contributing