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Datanika Core

by datanika-io

Browse Datanika data, inspect dbt workflows, monitor runs, and optionally create or trigger resources through MCP.

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Install Datanika Core

Pick your client, then add it in one click or paste the config.

STDIOPython
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "datanika-io-datanika-core": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/datanika-io/datanika-core#subdirectory=datanika-mcp",
        "datanika-mcp"
      ],
      "env": {
        "DATANIKA_URL": "YOUR_VALUE_HERE",
        "DATANIKA_API_KEY": "YOUR_VALUE_HERE",
        "DATANIKA_ALLOW_WRITE": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

Automated check passed— started and listed 25 tools correctly (4d ago).

Overview

The datanika-io/datanika-core MCP server connects AI clients to Datanika’s ELT and dbt platform through a command-line MCP process. It provides read-only tools for inspecting connections, previewing data, compiling transformations, browsing pipelines, and reviewing run logs; write operations require the --allow-write flag. Use it for data-platform exploration and dbt workflow operations against hosted or self-hosted Datanika instances.

Use cases

  • Inspect source schemas and preview table data
  • Run read-only SQL against Datanika connections
  • Compile and preview dbt transformations
  • Monitor pipeline and transformation runs
  • Create or trigger resources with write access enabled

Key features

  • Read-only operation by default
  • Connection introspection and table previews
  • Read-only SQL query execution
  • dbt compilation and transformation previews
  • Pipeline, catalog, and run monitoring
  • Optional resource creation and run triggering

Tools25

What Datanika Core lets your agent do. Expand a tool for its parameters.

Verified live~3.1k tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 2d ago

Recent health check succeeded.

19/19 checks healthy over the last 79d

What it can do

From the 25 tools this server returned when we ran it.

Runs commands · 2Handles credentials · 1Makes network requests · 1Read-only tools · 23
Network at startup2 connections
Files written at startupNone

Observed 2026-10-23 in an isolated sandbox. A description of reach, not a security audit.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 10d ago via OSV.dev · datanika-mcp (PyPI)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

Last commit1mo agoMost recent push to the default branch.
Availability100%Our rolling endpoint + install checks that succeeded.
Install checkPassedOur sandbox started it and listed its tools.
Tools exposed25Callable tools this server registers over MCP.
Directory activity3 viewsConfig copies, upvotes, and views on AllMCPs.

How Datanika Core works

What datanika-io/datanika-core does

The datanika-io/datanika-core MCP server exposes Datanika’s data-platform and dbt operations to an MCP-compatible AI client. It is designed for inspecting an organization’s connections, source structures, uploaded data, transformations, pipelines, catalog entries, and execution history.

Its default mode is read-only. In that mode, an agent can retrieve connection metadata, inspect schemas and tables, preview table rows, run read-only SQL, compile dbt transformations, preview transformation results, and examine pipeline or transformation runs. Write and execution-management operations become available only when the server is started with --allow-write.

How it works

The server communicates with a Datanika instance through its API. The target instance and API credentials can be supplied as command-line options or environment variables. Hosted deployments can use https://app.datanika.io; self-hosted deployments should point to the backend API port, typically 8000, rather than the Reflex frontend port 3000.

The MCP process can be launched with uvx from the published PyPI package or directly from the repository’s datanika-mcp subdirectory. Claude Desktop can register the process as an MCP server using a command and args configuration. The same stdio process model can be used by compatible MCP clients.

Setup and configuration

Install or run the server with one of these commands:

bash
uvx datanika-mcp --help
uvx --from "git+https://github.com/datanika-io/datanika-core#subdirectory=datanika-mcp" datanika-mcp --help

A basic invocation supplies the Datanika URL and API key:

bash
datanika-mcp --url https://app.datanika.io --api-key YOUR_API_KEY

The equivalent environment variables are DATANIKA_URL, DATANIKA_API_KEY, and DATANIKA_ALLOW_WRITE. Set the write variable to true, or pass --allow-write, when the client must create resources or trigger runs. Keep the default read-only mode when agents should only inspect or validate data workflows.

Tools and capabilities

Read-only tools cover:

  • Agent capability tiers and supported connection types
  • Connection lists, connection details, schemas, and tables
  • Table-row previews and read-only SQL queries
  • dbt transformation compilation and result previews
  • Upload, pipeline, transformation, and run listings
  • Run details and logs
  • Catalog entries for source tables and dbt models

With write access enabled, the server adds tools for creating connections, uploads, pipelines, and dbt SQL transformations. It can also bulk-import resources from JSON v2 format and trigger upload, pipeline, and transformation runs.

Limitations and notes

Write operations are not available by default and should be enabled deliberately. Transformation previews compile and execute a transformation to return preview rows, while compilation alone does not execute it. For self-hosted installations, using the frontend port instead of the backend API port will not provide the required /api/v1 endpoints.

The project is licensed under AGPL-3.0, matching the core Datanika platform.

Read the full README View source on GitHub

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Frequently Asked Questions about Datanika Core

datanika-io/datanika-core is an MCP server that connects AI clients to Datanika’s ELT and dbt platform. Its main tools browse connections, preview and query data, compile or preview dbt transformations, inspect catalogs, monitor runs, and manage pipelines, with write actions enabled separately.

Install it with `uvx datanika-mcp` or run it directly from the repository with `uvx --from "git+https://github.com/datanika-io/datanika-core#subdirectory=datanika-mcp" datanika-mcp`. Supply the Datanika URL and API key when starting the process.

Add a `datanika` entry to Claude Desktop’s `mcpServers` configuration with `uvx` as the command and the server package plus `--url` and `--api-key` arguments. You can alternatively provide `DATANIKA_URL`, `DATANIKA_API_KEY`, and `DATANIKA_ALLOW_WRITE` in the entry’s `env` object.

Enable write access by passing `--allow-write` or setting `DATANIKA_ALLOW_WRITE` to `true`. This adds resource creation, bulk import, and upload, pipeline, and transformation triggering tools; without it, the server remains read-only.

Pass the self-hosted backend URL with `--url`, such as `http://localhost:8000`, together with the API key. Use the backend port that serves `/api/v1`; the default frontend port `3000` is not the API endpoint.

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