Superset MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 |
|---|---|
| query-supersetC | 执行 Superset 数据查询 |
| list-databasesB | 获取所有可用的数据库列表 |
| list-tablesC | 获取指定数据库的表列表 |
| list-fieldsC | 获取指定表的字段列表 |
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 4 tools
Each tool has a clearly distinct purpose with no overlap: list-databases enumerates databases, list-tables shows tables within a database, list-fields details fields within a table, and query-superset executes queries. The hierarchical progression from databases to tables to fields to queries eliminates any ambiguity.
All tools follow a consistent verb_noun pattern using kebab-case (list-databases, list-fields, list-tables, query-superset). The verbs 'list' and 'query' are appropriately descriptive and applied consistently across the set, making the naming highly predictable.
With 4 tools, the count is reasonable for a Superset data exploration server, covering core operations like listing resources and querying. It feels slightly lean but not incomplete, as it supports basic workflows without unnecessary bloat. A few more tools (e.g., for metadata or schema operations) could enhance it, but it's well-scoped.
The tools provide a logical flow for data exploration: list databases, then tables, then fields, and finally query. Minor gaps exist, such as no explicit tools for creating or managing resources (e.g., dashboards or charts), but the core query and discovery operations are covered, allowing agents to navigate and query data effectively.