About Dataiku MCP
Dataiku MCP is an MCP server for operating Dataiku DSS through its REST APIs. It covers projects, flow analysis, datasets, recipes, jobs, scenarios, and related resources, but is no longer actively maintained; development has moved to Dataiku DSS SDK.
Key features
- 01Normalized project flow maps
- 02Project and dataset operations
- 03Recipe and job management
- 04Scenario and folder operations
- 05Structured errors with retry hints
Use cases
- 01Inspect a project's flow and dependencies
- 02Preview or manage datasets and recipes
- 03Run jobs and check their status
MCP support
Exposes tools for Dataiku DSS projects, datasets, recipes, jobs, scenarios, folders, variables, connections, and code environments to MCP clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
npx -y dataiku-mcpDATAIKU_URLDataiku DSS instance URL (for example, https://my-dss.app.dataiku.io).DATAIKU_API_KEYSecretDataiku API key.DATAIKU_PROJECT_KEYSecretOptional default Dataiku project key.Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.
Tools
9Saved tool list · updated 2w ago
This tool takes no parameters.
Details
From the project READMEImportant
Sunset — use
clssck/dataiku-sdkinsteadDataiku MCP Server is no longer actively maintained. Development has moved to the Dataiku DSS SDK — a schema-first TypeScript SDK and
dssCLI 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
dssCLI 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).
Cursor one-click install includes placeholder environment values. Update
DATAIKU_URL,DATAIKU_API_KEY, and optionallyDATAIKU_PROJECT_KEYafter 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,unknownwith retry hints.
Tool Coverage
project:list,get,metadata,flow,mapdataset:list,get,schema,preview,metadata,download,create,update,deleterecipe:list,get,create,update,delete,downloadjob:list,get,log,build,buildAndWait,wait,abortscenario:list,run,status,get,create,update,deletemanaged_folder:list,get,contents,download,upload,delete_filevariable:get,setconnection:infercode_env:list,get
Prerequisites
- Node.js 20+
- npm
- Dataiku DSS URL + API key
Quick Start
npm ci
npm run build
Run as a local CLI after build:
node dist/index.js
Use directly from npm (after publish):
npx -y dataiku-mcp
Local Build And Testing
Recommended local workflow from repo root:
# 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:
# 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:
cp .env.example .env
# then edit .env
Run directly in dev:
npm start
Example scripts and sample outputs are kept under examples/ to avoid root-level clutter.
Environment Variables
DATAIKU_URL: DSS base URLDATAIKU_API_KEY: DSS API keyDATAIKU_PROJECT_KEY(optional): default project keyDATAIKU_REQUEST_TIMEOUT_MS(optional): per-attempt request timeout in milliseconds (default:30000)DATAIKU_RETRY_MAX_ATTEMPTS(optional): max attempts for retry-enabled requests (GETonly, default:4, cap:10)DATAIKU_DEBUG_LATENCY(optional): set to1/trueto include per-tool timing diagnostics instructuredContent.debug.latency(off by default)
MCP Client Setup Guide
Use this server command in clients (npm package):
{
"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:
{
"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:
{
"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
- Open Claude Desktop ->
Settings->Developer->Edit Config. - Add this under
mcpServersinclaude_desktop_config.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:
{
"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)
- Open Cline -> MCP Servers -> Configure MCP Servers.
- Add this server block in
cline_mcp_settings.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 | majorversion: optional exact version (overridesbump)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:
- Install dependencies, run checks/tests, and build.
- Bump package version and create git tag.
- Push commit + tag to
main. - Publish to npm with GitHub OIDC trusted publishing (if
publish=true). - Create a GitHub Release with generated notes.
Trusted publishing setup (npm):
- Open
https://www.npmjs.com/package/dataiku-mcp->Settings->Trusted Publisher. - Choose
GitHub Actions. - Set:
- Organization or user:
clssck - Repository:
Dataiku_MCP - Workflow filename:
release.yml
- Organization or user:
- 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:
mcpNameinpackage.json
Server namespace:
io.github.clssck/dataiku-mcp
Publish paths:
- Manual: run
Publish to MCP Registryin GitHub Actions. - Automatic: run the npm release workflow with
publish=true(it triggers MCP Registry publish).
Validation notes:
server.json.namemust matchpackage.json.mcpName.server.json.packages[].identifier+versionmust reference a real npm publish.
Recommended Verification Prompt
After adding the server in a client, run:
projectwith{ "action": "map", "projectKey": "YOUR_PROJECT_KEY" }(defaults tomaxNodes=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.mapreturns a compact text summary; full normalized graph is instructuredContent.map.- Arrays in normalized map output are deterministically sorted to reduce diff churn.
job.waitandjob.buildAndWaitincludestructuredContent.normalizedStatewith one ofterminalSuccess | terminalFailure | timeout | nonTerminalwhile preserving raw DSSstate.- With
DATAIKU_DEBUG_LATENCY=1, responses include per-tool and per-API-call latency metrics understructuredContent.debug.latency. - List-style responses are token-bounded by default; use
limit/offset(and action-specific caps likemaxNodes,maxEdges,maxKeys,maxPackages) to page or expand results when needed. dataset.getandjob.getare summary-first by default; passincludeDefinition=trueto include full DSS JSON instructuredContent.definition.
Sources
- MCP local server connection docs: https://modelcontextprotocol.io/docs/develop/connect-local-servers
- Cursor MCP docs: https://cursor.com/docs/context/mcp
- Cline MCP docs: https://docs.cline.bot/mcp/configuring-mcp-servers
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