Lakelogic Mcp

io.github.LakeLogic由 GitHub 账号 LakeLogic 发布v0.1.4更新于 Oct 29, 2026

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

已验证STDIO仅桌面开发者工具数据与分析

概览

AI 生成的概览

本地 MCP 服务器,让 AI 助手用 LakeLogic 校验、检查、解释并试运行 Open Lakehouse Contracts。

可以做什么
  • 按 OLC 模型校验契约,列出每个错误的位置与问题
  • 对契约做 lint 检查,给出治理问题及对应修复建议
  • 解释 lint 规则,并查询契约各部分应如何编写
  • 将契约导出为 Open Data Contract Standard 文档
  • 按契约生成合成测试数据,其中包含故意违反规则的行
  • 用 Polars 或 DuckDB 在本地文件上运行契约,报告通过行数、失败行数及失败原因
适用场景
适合在项目中维护数据契约、希望助手检查契约、解释 lint 结果、生成样例数据并给出真实通过/失败结果而非臆测 YAML 的场景。
运行要求
以 PyPI 包 lakelogic-mcp 通过 stdio 在本地运行,PATH 中需有 uv。需在存放契约的项目中启动助手,或传入根目录参数。无需 LakeLogic 账号、API 密钥或环境变量。
安装前请注意
工具路径及 lint 读取的 domain/system 文件必须位于项目文件夹内,但契约自身引用的文件会按原样读取。若契约配置了通知或运行日志投递,运行契约时可能被发送。工具结果(包括样本行、可能引用数据的失败原因以及契约本身)会进入 AI 提供商的上下文;sample: 0 只移除行,机密数据请使用生成数据测试。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Lakelogic Mcp,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

[LakeLogic MCP: check and test data contracts with your AI assistant. A local MCP server for validating, linting and test-running OLC contracts. Your AI assistant talks to the LakeLogic MCP local server, which uses LakeLogic Core with Polars or DuckDB for contract checks (validate, lint, explain) and test runs (sample data, results, failure reasons). No LakeLogic account required.]

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

ToolAnswers
validate_contractDoes it match the OLC model? Each error's location and problem
lint_contractDoes it pass the lint checks? Governance findings, each with its fix
explain_ruleWhy does a lint rule exist? What it checks, why it matters, a failing and a fixed contract
contract_referenceHow is one part of a contract written? (anatomy, quality, materialization, …)
export_odcsThe contract as an Open Data Contract Standard document
generate_test_dataSynthetic data shaped by the contract, with a share of rows that deliberately break its rules
run_contractHow 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:

text
/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:

json
{  "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.

来源:README.md,提交 ea85927

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

4
  1. v0.1.4最新Oct 29, 2026
  2. v0.1.3Oct 24, 2026
  3. v0.1.2Oct 18, 2026
  4. v0.1.1Oct 15, 2026

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