Skip to main content
Glama
tlubben

Superset MCP Server

by tlubben

superset_create_chart

Create a chart in Apache Superset by specifying the dataset, visualization type, and parameter JSON. Configure metrics, grouping, and time range to produce the desired data visualization.

Instructions

Create a new chart. params must be a JSON string: object with keys like metrics, groupby, order_desc, row_limit, time_range, etc. depending on viz_type (e.g. table, big_number, line, bar, pie).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes
viz_typeYes
dataset_idYes
slice_nameYes
descriptionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden of behavioral disclosure, but it only provides parameter format details. It does not mention side effects, permissions, whether the chart is immediately visible, or what happens on success. The description is silent on any behavioral traits beyond the act of creating.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences long, front-loaded with the core purpose, and adds a necessary detail about the params format. There is no fluff, but it could be better structured with clearer examples or a link to documentation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having an output schema and moderate complexity, the description is too thin. It fails to explain which viz_type values are accepted, how to construct valid params, or any behavioral expectations. The agent is left with too many open questions to reliably use this tool without external knowledge.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds meaningful context for the params parameter by explaining it must be a JSON string with keys like metrics, groupby, and depending on viz_type. This goes beyond the bare schema. However, it does not clarify the semantics of dataset_id, viz_type, or slice_name, and with 0% schema coverage, more compensation is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Create a new chart' with a specific verb and resource, distinguishing it from sibling tools like update_chart, delete_chart, and add_chart_to_dashboard. It also mentions the key differentiator of needing a JSON params string depending on viz_type, which aligns with chart creation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given on when to use this tool versus alternatives, such as update_chart for existing charts or add_chart_to_dashboard for embedding. There are no prerequisites or exclusions mentioned. The description only states the basic purpose, leaving usage context entirely to the agent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/tlubben/bio-superset-agent'

If you have feedback or need assistance with the MCP directory API, please join our Discord server