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flet-mcp-server

flet-mcp-server

by Nwokike
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

read_flet_source

Read-only

Fetch the actual installed Flet source code with numbered lines, optionally extracting a specific symbol, to resolve conflicts when docs and training data disagree.

Instructions

Read the actual installed source of a flet module (numbered lines). This is the ground truth when docs and training data disagree.

Args: module: Dotted module or path relative to the flet package, e.g. 'controls/material/button.py', 'flet.controls.page', 'controls/types'. symbol: Optional class or function to extract instead of the whole file (e.g. 'Button', 'Page', 'Button.style' or 'app'). max_lines: Line cap when reading a whole file (default 400).

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": {
      "module": "<module>"
    },
    "name": "read_flet_source"
  }
}

Input Schema

NameRequiredDescriptionDefault
moduleYes
symbolNo
max_linesNo

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 establish readOnlyHint=true and destructiveHint=false. The description adds useful behavioral detail beyond that: the tool returns actual installed source, includes numbered lines, and can extract a specific symbol. This gives the agent a clear idea of what to expect, without contradicting the annotations.

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 core purpose is front-loaded in the first sentence, followed by a compact Args section. Every element earns its place: purpose, trust level, and parameter explanations are all included without redundancy or unnecessary filler.

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?

Given that an output schema exists and annotations cover safety, the description provides everything needed to invoke the tool correctly. It explains module addressing, optional symbol extraction, line cap behavior, and the semantic role of the tool as source-of-truth, making it effectively complete for an agent.

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?

Schema description coverage is 0%, so the description carries the full burden of explaining parameters. It does so excellently: module is explained with dotted-path and relative-path examples, symbol is described as an optional class/function extraction with nested examples, and max_lines is documented with its default value.

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 uses a specific verb and resource: 'Read the actual installed source of a flet module'. It also sets this tool apart from documentation retrieval by explicitly stating it is 'the ground truth when docs and training data disagree', which distinguishes it from siblings like search_flet_source and get_flet_doc.

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?

The description clearly provides a usage context: use this when docs and training data disagree, because it reads installed source rather than curated summaries. It does not explicitly name sibling alternatives or state when not to use them, but the 'ground truth' framing gives good contextual guidance.

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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