Sport Health MCP
Sport Health MCP
ローカルファーストのHuawei Health解析MCP Server。ユーザーは一度だけ
HUAWEI_HEALTH_* 個人データ書き出しパッケージを提供すればよく、Agentは運動パフォーマンス、
運動中の生理指標、運動前後の健康コンテキストを読み取り、必要に応じて履歴の天気と
大気質を補完できます。
本プロジェクトは運動の振り返りを目的としており、医療診断や治療のアドバイスを提供するものではありません。
現在の機能
Huawei個人データ書き出しディレクトリとコアJSONファイルを識別します。
Huawei非標準JSON数値キーをフォールトトレラントに解析します。
運動サマリー、GPSトラック、心拍数、歩頻、速度、標高、トレーニング負荷を解析します。
運動前日、当日、翌日の心拍数、安静時心拍数、HRV、ストレス、血中酸素、睡眠段階を集計します。
Open-Meteo履歴天気・大気質APIを呼び出し、レスポンスをローカルにキャッシュします。
MCP経由でページングデータツールとレポート証拠パックを提供します。
Related MCP server: mcp-takeout-googlefit
インストール
Python 3.11以降を推奨し、プロジェクトディレクトリに仮想環境を作成します:
python -m venv .venv
.\.venv\Scripts\Activate.ps1
python -m pip install -e ".[dev]"Huawei書き出しパッケージはパッケージ化もコミットもされません。.gitignore はデフォルトで
すべての HUAWEI_HEALTH_* ディレクトリを無視します。
ローカル確認
プロジェクトディレクトリに HUAWEI_HEALTH_* フォルダが1つだけある場合、自動的に識別されます:
sport-health-inspect inspect
sport-health-inspect list明示的に指定することもできます:
sport-health-inspect --export-dir "D:\HealthData\HUAWEI_HEALTH_xxx" listMCP Serverの起動
ローカルAgentには stdio を推奨します:
$env:SPORT_HEALTH_EXPORT_DIR="D:\HealthData\HUAWEI_HEALTH_xxx"
sport-health-mcpMCPクライアント設定の基本形式は次のとおりです。実際のフィールド名はクライアントに依存します:
{
"mcpServers": {
"sport-health": {
"command": "C:\\sport-health-mcp\\.venv\\Scripts\\sport-health-mcp.exe",
"env": {
"SPORT_HEALTH_EXPORT_DIR": "D:\\HealthData\\HUAWEI_HEALTH_xxx"
}
}
}
}MCPクライアントへの登録
MCP stdio をサポートするクライアントに前述の command と env 設定を追加し、保存後にクライアントを再起動します。
クライアントごとに設定ファイルの場所や外側のフィールド名が異なる場合があります。対応するクライアントのドキュメントに従ってください。
異なるAgentでの使用
同じPC:MCP
stdioをサポートする各Agentは同じServerを起動できますが、そのAgentの 設定形式に従って一度登録する必要があります。他のユーザーのPC:本プロジェクトをインストールし、自分の
HUAWEI_HEALTH_*データパッケージを書き出し、 設定内のコマンドとデータディレクトリを自分の絶対パスに置き換えます。ウェブ版またはクラウドAgent:ユーザーのPC上にあるローカル
stdioプロセスにはアクセスできません。このようなクライアントを サポートするには、認証付きのStreamable HTTPデプロイを別途提供し、暗号化アップロード、ユーザー分離、 データ削除、プライバシーコンプライアンスの仕組みを設計する必要があります。
プロジェクトは作者のHuaweiデータパッケージを共有しません。MCP Serverは汎用プログラムであり、 各ユーザーのデータは引き続きそのユーザーのローカルに保存されます。
MCPツール
inspect_huawei_export: データパッケージの整合性をチェックします。list_activities: 運動を一覧表示します。get_activity_summary: 1回の運動サマリーを照会します。get_activity_track: GPS軌跡をぺーしてお問い合わせます。get_activity_samples: 心拍数、歩数、速度、高度のサンプルをページングで照会します。get_health_context: 運動前後の複数日の健康コンテキストを照会します。get_activity_environment: 履歴環境データを取得してキャッシュします。get_report_evidence_pack: Agentがレポートを作成するための決定的な証拠パックを生成します。get_report_contract: 固定のレポート章構成、ページトーク数を取得します。
Agentはまず list_activities を呼び出し、activity_id を選択した後、優先的に
get_report_evidence_pack を呼び出し、返された report_contract に厳密に従ってレポートを出力することを推奨します。固定フォーマットは
コア判断、パフォーマンス分析、体の反応、トレーニング提案のみを保持し、デバイスアプリがすでに表示している完全な指標の繰り返しは避けます。
元のカーブやトラジェクトを表示する必要がある場合にのみ、ページングされた詳細ツールを呼び出します。
テスト
テストフレームワークをインストールしなくても、標準ライブラリでテストを実行できます:
$env:PYTHONPATH="src"
python -m unittest discover -s tests -vテストはコードで生成された合成運動記録のみを使用し、個人の書き出しデータには依存せず、含みません。
プライバシー境界
元の健康データはデフォルトでローカルでのみ読み取りされます。
環境補強ツールのみがネットワークにアクセスし、ルート中心点合わせて日付と時間範囲のみを送信します。
MCPツールは読み取り専用で、Huawei書き出し情報ファイルを修正しません。
ログや問題レポートを外部共有する前に、座標・時刻・デバイス識別子・健康指標を削除する必要があります。
ソースコードを公開する前に、作業ディレクトリ全体を直接彼は圧縮しないでください。版本控制のように导出するか、 ビルド成果物を公開し、無視されている個人データディレクトリを一緒にパッケージングしないようにします。
ライセンス
本プロジェクトは MITライセンス を採用しています。セキュリティ問題を提出する前に SECURITY.md をお読みください。公開のIssueに本物の健康データ、GPSトラック、 環境キャッシュ、またはローカルパスを含むログをアップロードしないでください。
第三方服务信息サービスの商标
環境データは Open-Meteo より提供され、データには CC BY 4.0 が適用されます。表示時には情報源とライセンスを明記する必要があります。
Open-Meteoの無料APIは非商用利用に限られ、呼び出し頻度の契約を受けます。商用利用の場合は商用インターフェースを利用するか、 公式ライセンスに従って自社で配備してください。詳細は Open-Meteo Terms を参照してください。
本プロジェクトは独立した社区コミュニティです。当時、华为の華為との間には所属・同意・承認関係はありません。 関連する製品名と商標は各権利者に帰属します。
Available Tools
9 toolsget_activity_environmentB
Fetch cached historical weather and air-quality context from Open-Meteo.
| Name | Required | Description | Default |
|---|---|---|---|
| activity_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral disclosure burden. It does usefully disclose that data is cached and historical, which implies it may be stale or not fetched live, but it does not describe cache-miss behavior, freshness limits, or whether any network call occurs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words, and the core purpose is front-loaded. It is compact and easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple enough that the description is mostly adequate, but it omits any contextual bridge to the sibling tools and leaves the sole parameter unexplained. The presence of an output schema reduces the need to explain the return value, yet this still feels minimal rather than complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not mention activity_id at all, and schema description coverage is 0%. The parameter name is reasonably interpretable, but the description adds no semantic guidance beyond the schema and does not compensate for the missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb and resource: 'Fetch cached historical weather and air-quality context from Open-Meteo.' It is specific enough to be understood as distinct from sibling tools like get_health_context, though it does not explicitly call out that distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance about when to use this tool instead of alternatives. Given siblings like get_health_context and get_activity_summary, an agent receives no signal about which one fits a given need.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_activity_samplesA
Get paginated heart_rate, cadence, speed, altitude, or pace samples.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| metric | No | ||
| offset | No | ||
| activity_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the transparency burden. It usefully states that results are paginated, which indicates offset/limit-driven behavior, and 'Get' signals read-only usage. However, it does not disclose what happens when the optional 'metric' parameter is null, nor does it mention ordering, boundaries, or rate-limit behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no jargon or required words. 'Get paginated' is front-loaded, and the metric list is compact. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so the response shape is not a concern. Yet the description still omits important invocation context: there is no statement about what null metric means, how pagination limits/offsets work, or any model limits on limit. This is likely to be usable in many cases but leaves crucial optionality unstated.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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. It does add semantic value for the metric parameter by listing possible sample types, but it does not explain the default null behavior, how limit/offset interact for pagination, or whether metric values are case/index-sensitive. The parameter list is therefore partially clarified but not fully covered.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description is specific and immediate: it uses the verb 'Get' with a clear resource ('paginated ... samples') and lists the exact metric types supported. This makes the purpose unmistakable and differentiates it from sibling tools like get_activity_summary and get_activity_track.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool—when you need paginated raw activity samples—but it never explicitly says when to prefer it over alternatives such as get_activity_summary or get_activity_track. The agent must infer routing from the tool name and sibling names rather than from direct guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_activity_summaryC
Get normalized summary metrics for one activity.
| Name | Required | Description | Default |
|---|---|---|---|
| activity_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must explain behavior. The word 'normalized' hints at data transformation, but it is undefined, and there is no mention of side effects, data source, permissions, or edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one short sentence that immediately states the purpose. There no filler, redundancy, or repetition of the tool name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description omits any context about how activity_id is used, what normalized metrics are, and how this tool fits among eight siblings. This is minimal for an agent deciding whether to call this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate for the activity_id parameter. It only says 'for one activity,' which confirms the parameter identifies a single activity, but it does not explain the format, source, or how to obtain it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Describes a clear action (Get) on a specific resource (activity summary metrics) for a single activity. It differentiates from sibling tools like get_activity_track and get_activity_samples through the word 'summary', though it does not explicitly name those alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus its siblings. The description implies usage for obtaining summary metrics of one activity, but it does not state what to use for other needs or exclude alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_activity_trackA
Get a paginated GPS track with timestamps and altitude for one activity.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| offset | No | ||
| activity_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden. It does reveal that the result is paginated and scoped to one activity, which is meaningful. However, it does not describe error behavior, auth requirements, rate limits, or what happens when an activity_id is invalid.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence conveys the core resource, pagination behavior, and relevant data fields. There is no redundant information or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple and has an output schema, so the description does not need to enumerate return values. Still, it lacks usage guidance and explicit details about pagination behavior or error cases, which are left to inference.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description must help interpret parameters. 'Paginated' implies limit and offset are pagination controls, and 'one activity' matches activity_id. But the description does not explain ordering, maximum limit, or the exact units or format expected.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: 'Get a paginated GPS track with timestamps and altitude for one activity.' This is unambiguous and clearly distinguishes the tool from siblings like list_activities and get_activity_summary.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to choose this tool over alternatives such as get_activity_samples or get_activity_environment. There are no conditions, exclusions, or known alternatives mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_health_contextA
Get daily health summaries around an activity, including sleep, HRV, stress, heart rate, and SpO2.
| Name | Required | Description | Default |
|---|---|---|---|
| days_after | No | ||
| activity_id | Yes | ||
| days_before | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden for behavioral context. The verb 'get' and the word 'summaries' indicate a read-only operation and the scope of data, but the description does not disclose behavior around missing health data, the meaning of the surrounding window, or any rate/consistency expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single compact sentence that leads with the action and resource, and adds a relevant list of health metrics without unnecessary elaboration. Every word contributes to the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple three-parameter tool with an output schema available, the description covers the central intent and the health metrics reasonably well. It still leaves the exact day-range behavior and data-availability edge cases to inference, but these are not severe omissions given the schemas and defaults.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description does not explicitly explain activity_id, days_before, or days_after. However, 'around an activity' adds some meaning to the before/after window and the default values in the schema are reasonably self-explanatory, so it is more than a tautology but still not a full parameter explanation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'get' and the specific resource: 'daily health summaries around an activity', and lists the included health indicators (sleep, HRV, stress, heart rate, SpO2). This makes it distinct from several siblings like get_activity_track or get_activity_environment, though it does not explicitly name a sibling within the text.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'around an activity' provides a plausible context for when to use the tool, but no explicit when-to-use or when-not-to-use guidance is present. There is no mention of when to choose this over get_activity_summary or get_activity_samples, so the decision is left to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_report_contractA
Return the stable structure and writing rules for end-user activity reports.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full responsibility. It clearly says the tool 'returns' a structure and rules, which implies a non-mutating retrieval. However, it doesn't disclose any details about the return format, version, caching behavior, or permissions required, though this is less critical for a 0-parameter read-like tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence of 11 words, front-loaded, with no filler or repeated information. It captures the essential behavior as precisely as possible for a simple contract-retrieval tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and the presence of an output schema, the description is complete enough for a simple contract lookup. The main gap is that it doesn't frame the relation to sibling tools such as get_report_evidence_pack, but that's a usage-guidance concern rather than a core completeness failure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters with an empty schema, so the description cannot need to add anything beyond what the schema already states. The baseline of 4 for 0-parameter tools is appropriate; nothing is unfilled.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Return') with a concrete resource ('stable structure and writing rules for end-user activity reports'), which strongly communicates the tool's deliverable. It distinguishes itself from all siblings (activity data, evidence packs) by focusing on the report contract itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage context or when-to-use/when-not-to-use guidance is provided. The description doesn't mention when to use this instead of siblings like get_report_evidence_pack or get_activity_summary, so the agent must infer from the tool's name and description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_report_evidence_packA
Build deterministic facts, context, flags, and guidance for a post-activity Agent report.
| Name | Required | Description | Default |
|---|---|---|---|
| activity_id | Yes | ||
| include_environment | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries more behavioral weight. It adds one useful behavior detail: the result is deterministic, meaning the generated evidence pack is reproducible. However, it does not explain important behavioral aspects such as whether this is a read-only/resource-consuming operation, whether it can fail, or what 'flags' semantically imply for the agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is concise, front-loaded with the core action, and contains no filler. The tradeoff is that brevity omits some needed behavioral details, but the text that is present earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The output schema exists, so return values are not required in the description. Even so, the description lacks parameter-level guidance, clear exclusions, and deeper behavioral context. It is minimally usable but not fully complete for an agent that must decide among several related activity/report tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description was expected to compensate, and it does not explain either parameter. Still, activity_id is clearly the identifier of the target activity, and include_environment is self-descriptive enough to infer its boolean intent, giving the parameter semantics a modest baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Build' and names a concrete deliverable ('deterministic facts, context, flags, and guidance for a post-activity Agent report'), so the tool's basic purpose is clear. It does not fully distinguish itself from report-related siblings like get_activity_summary or get_report_contract, so it falls short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for a post-activity Agent report' provides a clear, explicit use context: call this after an activity when generating an Agent report. It does not name alternative siblings, exclude related tools, or state when not to use it, but it does convey a direct context rather than leaving usage entirely implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
inspect_huawei_exportA
Check the configured Huawei export and report available source-file counts.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. 'Check' and 'report' imply a read-only inspection that returns counts rather than file contents, which is helpful, but it doesn't explicitly state side effects, required configuration, or error/edge-case behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one concise front-loaded sentence. It delivers the action, resource, and result with no filler or unclear phrasing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no parameters, an output schema, and a clear read-oriented purpose, the description is mostly complete. It could be slightly stronger with explicit guidance on what 'configured' means or what the counts are used for, but an agent can likely call it correctly as-is.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters and the schema confirms this, so there is no parameter-semantic burden on the description. A score of 4 aligns with the baseline for zero-parameter tools.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Check') and a clear resource ('configured Huawei export') along with the concrete outcome ('report available source-file counts'). This distinguishes it from the sibling activity/health/report tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage context is implicitly clear: an agent should call this when it needs to verify the Huawei export and know how many source files are available. However, there is no explicit guidance on when not to use it or how it compares to the sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_activitiesA
List imported activities. Optionally filter by running, walking, cycling, fitness, or workout.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| sport_type | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral disclosure burden. The verb 'list' implies a read-only operation and the filter values add useful context, but the description does not explain default limit behavior, what a null sport_type returns, pagination, or response shape.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the primary action and resource, then adds the key filtering detail. There is no filler or redundant repetition of the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with no required parameters and an output schema, the description is largely sufficient: it says what is listed and how to filter. Some context is left implicit, such as default limit behavior and when a caller should switch to the detail getter tools, but the schema and sibling names cover part of that gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has no descriptions for its parameters, so the description adds value by enumerating the valid sport_type filter values: running, walking, cycling, fitness, or workout. However, it does not clarify the 'limit' parameter or how filtering interacts with it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the operation ('List') and resource ('imported activities'), and gives concrete filter categories. It is distinguishable from the sibling get_activity_* tools because it describes a list view rather than a specific activity detail, though it does not explicitly contrast with those tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for listing imported activities and optionally filtering them by sport type. It does not explicitly say when to use this tool versus get_activity_summary, get_activity_track, or other siblings, nor does it provide exclusion cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
9 tool updates
v0.1.0- First observed
get_activity_environment - First observed
get_activity_samples - First observed
get_activity_summary - First observed
get_activity_track - First observed
get_health_context - First observed
get_report_contract - First observed
get_report_evidence_pack - First observed
inspect_huawei_export - First observed
list_activities
TDQS
Scored across 9 tools
Each tool maps cleanly to a distinct resource or data type: Huawei source inspection, activity listing, activity summary, GPS track, samples, health context, weather environment, report evidence, and report contract. Even the health context and activity environment tools are clearly separated by source and intent.
Most tools follow a clear get_<object> pattern, such as get_activity_summary, get_activity_track, and get_report_contract. The deviations are minor: list_activities uses list instead of get, and inspect_huawei_export uses inspect, but all are still recognizable, verb-first names.
Nine tools is a well-scoped surface for an activity and report analysis server. Each tool represents a meaningful step in the workflow—from inspecting source files, listing and retrieving activity data, adding health/environment context, and producing report evidence and contract rules.
The tool set forms a complete read-only pipeline for activity reporting: find source files, list activities, fetch summary, track, samples, health context, environmental context, and then produce evidence and contract for the final agent report. There are no obvious dead ends or missing operations within this server's reporting-focused scope.
Maintenance
Related MCP Connectors
PDF, photo, email, and file comparison evidence checks with plain-language reports.
- SomviaOAuthapp.somvia
Apple Health training load, recovery, HRV and workout detail for Claude, ChatGPT and any MCP client.
Read wearables and lab health data — sleep, activity, workouts, timeseries, lab tests and orders.
Authenticated public evidence search, verification, research jobs, exports, and webhooks.
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