datanika-mcp

Datanika MCP Server

mcp-name: io.datanika/datanika-mcp

MCP server for Datanika — browse connections, preview data, compile and validate dbt transformations, monitor runs, and manage pipelines from Claude Desktop.

Read-only by default. Pass --allow-write to enable creating resources and triggering pipeline runs.

Install

# From PyPI (recommended)
uvx datanika-mcp --help

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

Claude Desktop Configuration

Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS, %APPDATA%\Claude\claude_desktop_config.json on Windows):

Read-only (recommended)

{
  "mcpServers": {
    "datanika": {
      "command": "uvx",
      "args": [
        "--from", "git+https://github.com/datanika-io/datanika-core#subdirectory=datanika-mcp",
        "datanika-mcp",
        "--url", "https://app.datanika.io",
        "--api-key", "YOUR_API_KEY"
      ]
    }
  }
}

With write access

{
  "mcpServers": {
    "datanika": {
      "command": "uvx",
      "args": [
        "--from", "git+https://github.com/datanika-io/datanika-core#subdirectory=datanika-mcp",
        "datanika-mcp",
        "--url", "https://app.datanika.io",
        "--api-key", "YOUR_API_KEY",
        "--allow-write"
      ]
    }
  }
}

Environment variables

You can also configure via environment variables:

{
  "mcpServers": {
    "datanika": {
      "command": "uvx",
      "args": [
        "--from", "git+https://github.com/datanika-io/datanika-core#subdirectory=datanika-mcp",
        "datanika-mcp"
      ],
      "env": {
        "DATANIKA_URL": "https://app.datanika.io",
        "DATANIKA_API_KEY": "YOUR_API_KEY",
        "DATANIKA_ALLOW_WRITE": "true"
      }
    }
  }
}

Available Tools

Always available (read-only)

Tool	Description
get_agent_tiers	Get the 5-tier agent capability stack
get_connection_types	List supported connection types with config schemas
list_connections	List all connections in the org
get_connection	Get connection details by ID
introspect_connection	List schemas/tables of a source connection
preview_connection	Preview first N rows of a table
query_connection	Execute a read-only SQL query
compile_transformation	Compile a dbt transformation (no execution)
preview_transformation	Compile + execute, return preview rows
list_uploads	List all uploads
list_pipelines	List all pipelines
list_transformations	List all transformations
list_runs	List runs with optional filters
get_run	Get run details by ID
get_run_logs	Get run logs
list_catalog	List catalog entries (source tables + dbt models)
get_catalog_entry	Get catalog entry details

Requires --allow-write

Tool	Description
create_connection	Create a new data connection
create_upload	Create a new upload (extract + load)
create_pipeline	Create a new pipeline (dbt orchestration)
create_transformation	Create a new dbt SQL transformation
bulk_import	Bulk-create resources from JSON v2 format
trigger_upload	Trigger an upload run
trigger_pipeline	Trigger a pipeline run
trigger_transformation	Trigger a transformation run

Self-hosted

Point --url at your instance. Use the backend port (8000) — 3000 is the Reflex frontend and serves no /api/v1:

datanika-mcp --url http://localhost:8000 --api-key etf_your_key

Releasing (maintainers)

datanika-mcp publishes to PyPI via GitHub Actions Trusted Publishing (OIDC — no stored API token). To cut a release (from master):

1. Bump version in pyproject.toml.

2. Tag and push — the tag version must match pyproject.toml:

   git tag mcp-v0.2.0
   git push origin mcp-v0.2.0
   

3. The Release datanika-mcp to PyPI workflow builds the sdist + wheel and publishes. Verify: uvx datanika-mcp --help resolves from PyPI.

First-release setup: a one-time PyPI trusted-publisher must be configured (project datanika-mcp, repo datanika-io/datanika-core, workflow release-mcp.yml, environment pypi) before the first tag will publish. See the infra human-locker.

License

AGPL-3.0 — same as the core Datanika platform.