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
