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mcu-debug-mcp

mcu-debug-mcp

by stillsurge
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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ecosystem_get

Retrieve identification features for a specified embedded ecosystem (e.g., Zephyr, Keil) including project artifacts, build configuration, log signatures, and common pitfalls.

Instructions

输出指定生态的识别特征：工程产物 / 构建配置 / 日志特征 / 常见坑。 name 用 ecosystem_list 给的 key（如 zephyr / keil / rust_defmt）。

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": {
      "name": "<name>"
    },
    "name": "ecosystem_get"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full disclosure burden. It does reveal the shape of the returned knowledge (artifacts, build config, log signatures, pitfalls), which is useful, but never states that this is a read-only, side-effect-free lookup or whether it depends on a prior scan. For a low-risk reference lookup with an output schema, this is adequate but thin.

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?

Two short lines, zero filler, with the purpose front-loaded and the parameter constraint immediately after. Every sentence earns its place.

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?

With an output schema present, the description need not explain return values, and it correctly focuses on the key source and identifier semantics. The only real gap is the absence of any note on read-only behavior or failure handling for an invalid ecosystem key.

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?

Schema description coverage is 0%, so the description must compensate, and it does: it explains that 'name' is the key produced by ecosystem_list and supplies three concrete example values. It stops short of stating whether an unknown key errors or returns an empty result.

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?

States a specific verb and resource ('输出指定生态的识别特征') and enumerates exactly what the output covers (工程产物 / 构建配置 / 日志特征 / 常见坑). It also differentiates itself from the sibling 'ecosystem_list' by positioning itself as the detail lookup keyed by that tool's output.

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?

Gives a clear prerequisite: obtain the 'name' key from ecosystem_list, with concrete key examples (zephyr / keil / rust_defmt). It does not state any when-not-to-use condition, but the list-then-get workflow is unambiguous.

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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