Dataiku MCP

平台与服务

by clssck

面向 Dataiku DSS 项目、flow 与 operations APIs 的 MCP 服务器,便于 AI 调用与管理。

什么是 Dataiku MCP

面向 Dataiku DSS 项目、flow 与 operations APIs 的 MCP 服务器,便于 AI 调用与管理。

README

[!IMPORTANT]

Sunset — use clssck/dataiku-sdk instead

Dataiku MCP Server is no longer actively maintained. Development has moved to the Dataiku DSS SDK — a schema-first TypeScript SDK and dss CLI that is more actively maintained and covers far more of the DSS API:

  • Broader coverage — 30+ DSS resources vs this server's narrow tool set.
  • A scriptable dss CLI with a machine-readable command contract for agents.
  • One-command agent skill install for Claude, Codex, Cursor, Pi, and OMP.

Migrate here → https://github.com/clssck/dataiku-sdk


Dataiku MCP Server

MCP server for Dataiku DSS REST APIs, focused on flow analysis and reliable day-to-day operations (projects, datasets, recipes, jobs, scenarios, folders, variables, connections, and code environments).

Install MCP Server

Cursor one-click install includes placeholder environment values. Update DATAIKU_URL, DATAIKU_API_KEY, and optionally DATAIKU_PROJECT_KEY after adding the server.

What You Get

  • Deterministic normalized flow maps (project.map) with recipe subtypes and connectivity.
  • Summary-first outputs with explicit raw/detail toggles where needed.
  • Broad test coverage (unit + live integration + optional destructive integration suite).
  • Strong error taxonomy in responses: not_found, forbidden, validation, transient, unknown with retry hints.

Tool Coverage

  • project: list, get, metadata, flow, map
  • dataset: list, get, schema, preview, metadata, download, create, update, delete
  • recipe: list, get, create, update, delete, download
  • job: list, get, log, build, buildAndWait, wait, abort
  • scenario: list, run, status, get, create, update, delete
  • managed_folder: list, get, contents, download, upload, delete_file
  • variable: get, set
  • connection: infer
  • code_env: list, get

Prerequisites

  • Node.js 20+
  • npm
  • Dataiku DSS URL + API key

Quick Start

bash
npm ci
npm run build

Run as a local CLI after build:

bash
node dist/index.js

Use directly from npm (after publish):

bash
npx -y dataiku-mcp

Local Build And Testing

Recommended local workflow from repo root:

bash
# install deps
npm ci

# static checks
npm run check

# unit tests
npm test

# build distribution
npm run build

# run MCP server locally (dev)
npm start

Optional live DSS integration tests:

bash
# requires DATAIKU_URL, DATAIKU_API_KEY, DATAIKU_PROJECT_KEY in .env
npm run test:integration

# includes destructive actions (create/update/delete)
DATAIKU_MCP_DESTRUCTIVE_TESTS=1 npm run test:integration

Repository Layout

  • src/: MCP server and tool implementations.
  • tests/: unit + integration test suites.
  • examples/: demos, fixtures, artifacts, and ad-hoc local scripts.
  • bin/: package executable entrypoint.
  • dist/: compiled output (generated).

Create a local env file:

bash
cp .env.example .env
# then edit .env

Run directly in dev:

bash
npm start

Example scripts and sample outputs are kept under examples/ to avoid root-level clutter.

Environment Variables

  • DATAIKU_URL: DSS base URL
  • DATAIKU_API_KEY: DSS API key
  • DATAIKU_PROJECT_KEY (optional): default project key
  • DATAIKU_REQUEST_TIMEOUT_MS (optional): per-attempt request timeout in milliseconds (default: 30000)
  • DATAIKU_RETRY_MAX_ATTEMPTS (optional): max attempts for retry-enabled requests (GET only, default: 4, cap: 10)
  • DATAIKU_DEBUG_LATENCY (optional): set to 1/true to include per-tool timing diagnostics in structuredContent.debug.latency (off by default)

MCP Client Setup Guide

Use this server command in clients (npm package):

json
{
  "command": "npx",
  "args": ["-y", "dataiku-mcp"],
  "env": {
    "DATAIKU_URL": "https://your-dss-instance.app.dataiku.io",
    "DATAIKU_API_KEY": "your_api_key",
    "DATAIKU_PROJECT_KEY": "YOUR_PROJECT_KEY"
  }
}

Windows note: if your MCP client launches commands without a shell, use npx.cmd:

json
{
  "command": "npx.cmd",
  "args": ["-y", "dataiku-mcp"],
  "env": {
    "DATAIKU_URL": "https://your-dss-instance.app.dataiku.io",
    "DATAIKU_API_KEY": "your_api_key",
    "DATAIKU_PROJECT_KEY": "YOUR_PROJECT_KEY"
  }
}

You can also run TypeScript directly during development:

json
{
  "command": "npx",
  "args": ["tsx", "/absolute/path/to/Dataiku_MCP/src/index.ts"],
  "env": {
    "DATAIKU_URL": "https://your-dss-instance.app.dataiku.io",
    "DATAIKU_API_KEY": "your_api_key",
    "DATAIKU_PROJECT_KEY": "YOUR_PROJECT_KEY"
  }
}

Claude Desktop

  1. Open Claude Desktop -> Settings -> Developer -> Edit Config.
  2. Add this under mcpServers in claude_desktop_config.json:
json
{
  "mcpServers": {
    "dataiku": {
      "command": "npx",
      "args": ["-y", "dataiku-mcp"],
      "env": {
        "DATAIKU_URL": "https://your-dss-instance.app.dataiku.io",
        "DATAIKU_API_KEY": "your_api_key",
        "DATAIKU_PROJECT_KEY": "YOUR_PROJECT_KEY"
      }
    }
  }
}

Cursor

Cursor supports both project-scoped and global MCP config:

  • Project: .cursor/mcp.json
  • Global: ~/.cursor/mcp.json

Example:

json
{
  "mcpServers": {
    "dataiku": {
      "command": "npx",
      "args": ["-y", "dataiku-mcp"],
      "env": {
        "DATAIKU_URL": "https://your-dss-instance.app.dataiku.io",
        "DATAIKU_API_KEY": "your_api_key",
        "DATAIKU_PROJECT_KEY": "YOUR_PROJECT_KEY"
      }
    }
  }
}

Cline (VS Code extension)

  1. Open Cline -> MCP Servers -> Configure MCP Servers.
  2. Add this server block in cline_mcp_settings.json:
json
{
  "mcpServers": {
    "dataiku": {
      "command": "npx",
      "args": ["-y", "dataiku-mcp"],
      "env": {
        "DATAIKU_URL": "https://your-dss-instance.app.dataiku.io",
        "DATAIKU_API_KEY": "your_api_key",
        "DATAIKU_PROJECT_KEY": "YOUR_PROJECT_KEY"
      }
    }
  }
}

Codex / project-level MCP config

This repo already includes a project-scoped MCP file at .mcp.json. The checked-in .mcp.json uses node node_modules/tsx/dist/cli.mjs src/index.ts for cross-platform startup (including Windows); run npm ci first.

NPM Release Workflow

This repo includes a manual GitHub Actions release workflow:

  • Workflow file: .github/workflows/release.yml
  • Trigger: Actions -> Release NPM Package -> Run workflow

Inputs:

  • bump: patch | minor | major
  • version: optional exact version (overrides bump)
  • publish: whether to publish to npm

Required repository configuration:

  • GitHub variable: NPM_RELEASE_ENABLED=true
  • Optional variable: NPM_PUBLISH_ACCESS=public
  • Trusted publisher configured on npmjs.com for this package/repo/workflow

The workflow will:

  1. Install dependencies, run checks/tests, and build.
  2. Bump package version and create git tag.
  3. Push commit + tag to main.
  4. Publish to npm with GitHub OIDC trusted publishing (if publish=true).
  5. Create a GitHub Release with generated notes.

Trusted publishing setup (npm):

  1. Open https://www.npmjs.com/package/dataiku-mcp -> Settings -> Trusted Publisher.
  2. Choose GitHub Actions.
  3. Set:
    • Organization or user: clssck
    • Repository: Dataiku_MCP
    • Workflow filename: release.yml
  4. Save.

Official MCP Registry

This repo is configured for MCP Registry publishing:

  • Metadata file: server.json
  • Workflow: .github/workflows/publish-mcp-registry.yml
  • Required package field: mcpName in package.json

Server namespace:

  • io.github.clssck/dataiku-mcp

Publish paths:

  1. Manual: run Publish to MCP Registry in GitHub Actions.
  2. Automatic: run the npm release workflow with publish=true (it triggers MCP Registry publish).

Validation notes:

  • server.json.name must match package.json.mcpName.
  • server.json.packages[].identifier + version must reference a real npm publish.

Recommended Verification Prompt

After adding the server in a client, run:

  • project with { "action": "map", "projectKey": "YOUR_PROJECT_KEY" } (defaults to maxNodes=300, maxEdges=600; override as needed)

You should receive a flow summary in text and normalized nodes, edges, stats, roots, and leaves under structuredContent.map. When truncation limits are applied (default maxNodes=300, maxEdges=600), structuredContent.truncation reports before/after node+edge counts and whether truncation occurred.

Notes

  • project.map returns a compact text summary; full normalized graph is in structuredContent.map.
  • Arrays in normalized map output are deterministically sorted to reduce diff churn.
  • job.wait and job.buildAndWait include structuredContent.normalizedState with one of terminalSuccess | terminalFailure | timeout | nonTerminal while preserving raw DSS state.
  • With DATAIKU_DEBUG_LATENCY=1, responses include per-tool and per-API-call latency metrics under structuredContent.debug.latency.
  • List-style responses are token-bounded by default; use limit/offset (and action-specific caps like maxNodes, maxEdges, maxKeys, maxPackages) to page or expand results when needed.
  • dataset.get and job.get are summary-first by default; pass includeDefinition=true to include full DSS JSON in structuredContent.definition.

Sources

常见问题

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