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by Mikebenisberchmans
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_dashboard_status

Check whether the Streamlit dashboard is running and which port it uses, so you can connect to the live view or troubleshoot startup issues.

Instructions

Returns whether the Streamlit dashboard is running and on which port.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_dashboard_status"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral burden, and it does disclose the essential trait: this is a status/read probe that returns a running flag and a port. It omits any note about authentication, side effects, or what happens when the dashboard is stopped, though for a zero-argument probe that gap is modest.

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

Conciseness5/5

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

A single front-loaded sentence with no filler; the returned information is stated immediately with zero waste.

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

Completeness4/5

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

An output schema exists, so the description needn't enumerate return values, and no parameters need explaining. The only missing piece is when to reach for this tool relative to the other dashboard tools.

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

Parameters4/5

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

The tool takes no parameters, so the baseline of 4 applies; there is no parameter semantics to document. The description correctly adds no redundant parameter commentary.

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

Purpose4/5

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

States a concrete verb and resource ('Returns whether the Streamlit dashboard is running and on which port'), which is specific enough to distinguish it from create_dashboard, stop_dashboard, and read_dashboard. It doesn't explicitly name those siblings, but the status-vs-operate distinction is inherent in the wording.

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?

The description gives no guidance on when to call this versus alternatives such as read_dashboard or create_dashboard, and no preconditions. The use case (checking readiness before another dashboard operation) is only inferable, not stated.

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

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