Lakelogic Mcp

io.github.LakeLogic由 GitHub 帳號 LakeLogic 發布v0.1.4更新於 Oct 29, 2026

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

已驗證STDIO僅桌面開發者工具資料與分析

概覽

AI 產生的概覽

本機 MCP 伺服器,讓 AI 助理用 LakeLogic 驗證、檢查、解釋並試跑 Open Lakehouse Contracts。

可以做什麼
  • 依 OLC 模型驗證契約,列出每個錯誤的位置與問題
  • 對契約執行 lint 檢查,列出治理問題並附上修正建議
  • 解釋 lint 規則,並查詢契約各部分的撰寫方式
  • 將契約匯出為 Open Data Contract Standard 文件
  • 依契約產生合成測試資料,其中包含刻意違反規則的資料列
  • 以 Polars 或 DuckDB 在本機檔案上執行契約,回報通過列數、失敗列數與失敗原因
適用情境
適合在專案中維護資料契約、希望助理檢查契約、解釋 lint 結果、產生範例資料,並取得實際通過/失敗結果而非憑空生成的 YAML 的情境。
執行需求
以 PyPI 套件 lakelogic-mcp 透過 stdio 在本機執行,PATH 中需有 uv。需在存放契約的專案中啟動助理,或傳入根目錄參數。不需要 LakeLogic 帳號、API 金鑰或環境變數。
安裝前請注意
工具路徑及 lint 讀取的 domain/system 檔案必須位於專案資料夾內,但契約本身引用的檔案會依原樣讀取。若契約設定了通知或執行日誌投遞,執行契約時可能會送出。工具結果(包含樣本資料列、可能引用資料的失敗原因以及契約本身)會進入 AI 供應商的上下文;sample: 0 只移除資料列,機密資料請改用產生的資料測試。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Lakelogic Mcp,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

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.

來源:README.md,提交 ea85927

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

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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