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flet-mcp-server

flet-mcp-server

by Nwokike
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

inspect_flet_control

Read-only

Retrieve the exact, current API of any Flet control from installed source: properties, types, defaults, events, and deprecations. Use before writing UI code to avoid outdated control definitions.

Instructions

Get the exact, current API of any Flet control straight from the installed source: every property with its type and default (inherited ones marked), events (on_*), deprecation warnings, the class hierarchy, and the full class source with per-property docstrings. ALWAYS use this before writing Flet UI code — control APIs in training data are often outdated.

Args: control_name: Public flet class name, e.g. 'Button', 'TextField', 'CupertinoSwitch', 'Page', 'View'.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "control_name": "<control_name>"
    },
    "name": "inspect_flet_control"
  }
}

Input Schema

NameRequiredDescriptionDefault
control_nameYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.2

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already mark the tool as read-only, and the description adds meaningful behavioral detail: it reads installed source, marks inherited properties, surfaces deprecation warnings, and returns full class source. This goes beyond the annotations without contradicting them.

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?

The main purpose and output contents are front-loaded, and the usage rule is embedded naturally. The Args section is minimal and directly useful. There is no filler, tautology, or restating of the tool name.

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

Completeness5/5

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

For a single-parameter, read-only tool with an output schema, the description supplies all essential invocation context: what to pass, why to use it, and what the result will contain. Nothing critical is missing for an agent to call it correctly.

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

Parameters5/5

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

With 0% schema coverage, the description carries the full burden for parameter understanding and succeeds. The Args block defines control_name as a public Flet class name and gives five realistic examples such as 'Button', 'TextField', and 'Page', making the schema's bare 'Control Name' title far more actionable.

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 opens with a specific verb and resource: 'Get the exact, current API of any Flet control straight from the installed source.' It lists concrete outputs like properties, types, defaults, events, deprecation warnings, class hierarchy, and source, which clearly separates it from sibling source-reading and documentation tools.

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

Usage Guidelines4/5

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

It gives an explicit when-to-use instruction: 'ALWAYS use this before writing Flet UI code — control APIs in training data are often outdated.' This is strong contextual guidance, though it does not name alternatives or state when to prefer sibling tools like get_flet_doc or list_flet_api.

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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