Redash MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| REDASH_API_KEY | Yes | RedashのAPIキー | |
| REDASH_BASE_URL | Yes | RedashのURL（例: https://redash.example.com） |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| execute_query_and_waitC | Execute a SQL query and wait for the results |
| list_data_sourcesB | List all available data sources |
| get_data_sourceC | Get details about a specific data source |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: execute_query_and_wait runs queries, get_data_source retrieves details for a specific source, and list_data_sources enumerates all sources. There is no overlap or ambiguity between these operations.
All tools follow a consistent verb_noun pattern (execute_query_and_wait, get_data_source, list_data_sources) with clear, descriptive names that align well with their functions.
With only 3 tools, the server feels under-scoped for a Redash-like data querying and visualization platform. Key operations like creating/updating queries, managing dashboards, or fetching query results are missing, making the set too thin for typical agent workflows.
The tool surface is severely incomplete for a Redash server. While it covers basic data source listing and query execution, it lacks essential CRUD operations for queries, dashboards, and visualizations, as well as lifecycle management tools, which will likely cause agent failures in complex tasks.