io.github.LakeLogic/lakelogic-mcp
Validate, lint, test-run and explain Open Lakehouse Contracts with LakeLogic, from any AI assistant.
Installation
Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).
lakelogic-mcpclaude mcp add lakelogic-mcp -- uvx lakelogic-mcp==0.1.4
{
"mcpServers": {
"lakelogic-mcp": {
"command": "uvx",
"args": [
"lakelogic-mcp==0.1.4"
]
}
}
}
Documentation
Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.
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 <folder>).
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
uvxdownloads the package, as any install does.) - Tool paths stay in your project. Every path you give a tool, and the
_domain.yaml/_system.yamlthat lint takes into account, must be inside the project folder. Files a contract itself names (alinks: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: 0removes 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.
Questions fréquentes
Qu'est-ce que io.github.LakeLogic/lakelogic-mcp ?
Validate, lint, test-run and explain Open Lakehouse Contracts with LakeLogic, from any AI assistant.
Comment installer io.github.LakeLogic/lakelogic-mcp ?
Il s'exécute sur votre machine. Dans Claude Code : claude mcp add lakelogic-mcp -- uvx lakelogic-mcp==0.1.4. Pour les autres clients, collez la configuration JSON de cette page dans leurs réglages MCP.
Faut-il une clé API pour io.github.LakeLogic/lakelogic-mcp ?
Son entrée au registre n'indique aucune clé ni secret obligatoire. Certaines fonctions peuvent tout de même demander un compte auprès du service auquel il se connecte.
io.github.LakeLogic/lakelogic-mcp est-il open source ?
Oui. Son code est sur GitHub sous licence Apache-2.0.
Qui maintient io.github.LakeLogic/lakelogic-mcp ?
Il est publié par LakeLogic. AI.tn le référence sans le maintenir ni le recommander.
Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.