redash-mcp

redash-mcp

Model Context Protocol (MCP) server for Redash - manage queries, dashboards, and visualizations through AI assistants like Claude.

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README

redash-mcp

Model Context Protocol (MCP) server for Redash - manage queries, dashboards, and visualizations through AI assistants like Claude.

Features

  • 7 tools, 30 actions - compressed for minimal context usage
  • Full query management (list, search, create, update, archive, delete, run, adhoc, export, schedule)
  • Dashboard management (list, get, create, publish, delete)
  • Widget management with positioning (add, move, delete)
  • Alert management (list, get, create, update, delete)
  • Visualization creation (pie, line, bar, counter charts)
  • Data source listing

Installation

pip install redash-mcp

Or with uvx:

uvx redash-mcp

Configuration

Environment Variables

Variable Required Description
REDASH_URL Yes Your Redash instance URL (e.g., https://redash.example.com)
REDASH_API_KEY Yes Your Redash API key
REDASH_TIMEOUT No Request timeout in seconds (default: 30)

Claude Code

Add to ~/.claude.json (user-level config):

{
  "mcpServers": {
    "redash": {
      "type": "stdio",
      "command": "uvx",
      "args": ["redash-mcp"],
      "env": {
        "REDASH_URL": "https://your-redash-instance.com",
        "REDASH_API_KEY": "your-api-key"
      }
    }
  }
}

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "redash": {
      "command": "uvx",
      "args": ["redash-mcp"],
      "env": {
        "REDASH_URL": "https://your-redash-instance.com",
        "REDASH_API_KEY": "your-api-key"
      }
    }
  }
}

Or if installed via pip:

{
  "mcpServers": {
    "redash": {
      "command": "redash-mcp",
      "env": {
        "REDASH_URL": "https://your-redash-instance.com",
        "REDASH_API_KEY": "your-api-key"
      }
    }
  }
}

Tools

redash_data_sources

List all available data sources.

redash_query

Manage Redash queries.

Action Parameters Description
list page List all queries (paginated)
search q Search queries by name
get id Get query details
create name, query, data_source_id Create new query
update id, query?, name? Update existing query
archive id Archive (soft-delete) query
delete id Permanently delete query
run id, timeout? Execute query and wait for results
adhoc query, data_source_id Execute SQL without saving
export id, path Export query results to file (.csv or .json)
schedule id, interval, until? Schedule query execution (interval in seconds)

redash_dashboard

Manage Redash dashboards.

Action Parameters Description
list page List all dashboards
get id Get dashboard with widgets
create name Create new dashboard
publish id Publish dashboard (remove draft)
delete id Delete dashboard

redash_widget

Manage dashboard widgets.

Action Parameters Description
add dashboard_id, viz_id, col?, row?, sizeX?, sizeY? Add visualization with optional position
move id, col?, row?, sizeX?, sizeY? Reposition/resize a widget
delete id Remove widget from dashboard

redash_alert

Manage query alerts.

Action Parameters Description
list List all alerts
get id Get alert details
create query_id, name, column, op, value, rearm? Create alert on query result
update id, name?, rearm? Update alert settings
delete id Delete alert

redash_viz

Create visualizations.

Type Parameters Description
pie query_id, name, x, y Pie chart
line query_id, name, x, y, datetime? Line chart
bar query_id, name, x, y, stacked? Bar chart
counter query_id, name, x, suffix? Counter/KPI

Note: For multiple Y columns, pass comma-separated values: y="count,total,avg"

Examples

Create a dashboard with visualizations

1. redash_data_sources() → get data_source_id
2. redash_query(action="create", name="Daily Stats", query="SELECT ...", data_source_id=1)
3. redash_viz(type="line", query_id=123, name="Trend", x="date", y="count")
4. redash_dashboard(action="create", name="My Dashboard")
5. redash_widget(action="add", dashboard_id=456, viz_id=789)
6. redash_dashboard(action="publish", id=456)

Run ad-hoc query

redash_query(action="adhoc", query="SELECT COUNT(*) FROM users", data_source_id=1)

Export query results

redash_query(action="export", id=123, path="/tmp/results.csv")
redash_query(action="export", id=123, path="/tmp/results.json")

Search and update query

redash_query(action="search", q="daily")
redash_query(action="update", id=123, query="SELECT ... WHERE date > NOW() - INTERVAL '7 days'")

Python Library Usage

You can also use redash-mcp as a Python library:

import os
os.environ["REDASH_URL"] = "https://your-redash.com"
os.environ["REDASH_API_KEY"] = "your-key"

from redash_mcp import (
    list_queries, create_query, run_query,
    create_dashboard, publish_dashboard,
    line, bar, pie, counter,
    add_widget
)

# Create query
q = create_query("My Query", "SELECT * FROM events", data_source_id=1)

# Create visualization
viz = line(q["id"], "Events Trend", x="date", y=["count"])

# Create dashboard and add widget
d = create_dashboard("My Dashboard")
add_widget(d["id"], viz["id"])
publish_dashboard(d["id"])

Why redash-mcp?

  • Context efficient - Only 7 tools (~500 tokens) with 30 actions
  • Full-featured - Queries, dashboards, widgets, and visualizations
  • Production ready - Proper error handling and timeouts
  • Dual use - Works as MCP server and Python library

License

MIT

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