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Gaggiuino MCP Server

by AndrewKlement
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Python
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ガッジウーノ-MCP

Gaggiuino MCPサーバー これは、Gaggia Classic用のオープンソースエスプレッソマシンコントローラーであるGaggiuino用に構築された軽量なモデルコンテキストプロトコル（MCP）サーバーです。Gaggiuinoシステムからのデータをリアルタイムで表示または分析したいAIクライアントを簡単に統合できるように設計されています。

これは私がこのプロジェクトについて書いた記事ですhttps://medium.com/@a.klement.w/dialing-in-espresso-using-mcp-server-0207819fe93a

接続されたクライアントに次のことを許可します:

  • 現在のマシンの状態を取得する

  • 最新のショットIDにアクセスする

  • 指定されたIDのショットデータを取得する

Related MCP server: meticulous-mcp

特徴

📊 ショットテレメトリへのリアルタイムアクセス

🌐 ローカルネットワークアクセス用に設計

使い方

Claudeデスクトップの使用

{
  "mcpServers": {
      "gaggiuino": {
          "command": "uv",
          "args": [
              "--directory",
              "/ABSOLUTE/PATH/TO/PARENT/FOLDER/gaggiuino-mcp",
              "run",
              "gaggiuino.py"
          ]
      }
  }
}

利用可能なツールセット

ツールセット

説明

getLatestShotId

最新のエスプレッソショットIDを取得する

getShotData

IDのエスプレッソショットデータを取得します。引数: id: ショットID

getStatus

エスプレッソマシンのステータスを取得する

例

ユーザー：

最新のエスプレッソショットデータを分析する

クロード：

最新のエスプレッソショットデータを取得して分析します。まずエスプレッソマシンの状態を確認し、最新のショット情報を取得します。getStatus 最新のエスプレッソショットのIDを取得します: getStatusショットgetLatestShotId 188のデータを取得します: getShotData取得したデータに基づいて、最新のエスプレッソショット（ID #188）を分析します。分析結果は以下の通りです。

マシンの状態とショットの概要：マシンは現在アイドル状態（57.2°C、圧力-0.1 bar）です。分析されたショットは、2025年4月19日（タイムスタンプに基づく）に行われ、合計継続時間は26.5秒（0.1秒間隔で265データポイント）でした。

プロファイル情報 使用したのは「Leva 9 LR v0.5」プロファイルです。これは、40gの出力を目標とした減圧多相プロファイルです。このプロファイルは

  1. 7 ml/sの流量制御前注入

  2. 3.5 ml/sの流量までステップダウン

  3. 3 barの圧力制限で1.5 ml/sの流量で前抽出

  4. 2秒かけて9barまで圧力上昇

  5. 徐々に圧力が低下する一連のステップ（8.8→6.0 bar）

ショット分析前注入および抽出段階

  • 事前注入 (0-5 秒): パックを飽和させるために、最小の圧力 (0.3-0.6 bar) で高流量 (6-7 ml/秒) から開始します。

  • 最初の圧力上昇 (5 ～ 10 秒): 圧力が徐々に約 2.5 bar まで上昇し、流量が約 1.5 ml/s まで減少しました。

  • 圧力プロファイルフェーズ (10 ～ 15 秒): 圧力は 3 bar 前後に維持され、流量は ~0.8 ml/s に減少します。

  • 圧力ランプ (15 ～ 20 秒): プログラムされたプロファイルに従って、約 5 秒間で圧力が 3 bar から 8.9 bar に増加しました。

  • 圧力低下フェーズ (20 ～ 26.5 秒): プロファイルの手順に従って、圧力が約 8.5 bar から 6.4 bar まで徐々に低下しました。

主要な測定

  • 最終収量: 38g (最終ショット重量に基づく)

  • 抽出比率: 不明（コーヒーの量は提供されていない）

  • 温度安定性: 良好 - 抽出中は92.8～94.1℃に維持

  • 最初の滴: 約11～12秒後に出現（注入前の約75%）

  • ピークフローレート：7.2 ml/s（開始時）

  • ピーク圧力: 8.9 bar (約20秒後)

抽出ダイナミクス

  1. 流量: 最初は高く (7 ml/s)、プログラムどおりに前注入中に 3.5 ml/s、次に 1.5 ml/s に下げ、抽出中に約 2.8 ml/s で安定しました。

  2. 給水量: 汲み上げられた水の総量は 87.7 ml で、カップには 38g 入っており、パック内にかなりの水分が残っていることが示唆されます。

  3. 圧力プロファイル: 圧力曲線は、注入前から抽出まで優れた進行を示し、圧力が下降するまでスムーズに移行します。

パフォーマンス評価 これは、プログラムされたプロファイルによく準拠した、技術的によく実行されたショットのようです。

  • 温度制御：93～94℃付近で優れた安定性

  • 圧力曲線: プログラムされたプロファイルに沿ってスムーズな遷移を実現します

  • 抽出フロー：主抽出フェーズで一貫している

  • 重量出力: 38g を達成 (40g 目標に近い)

このショットのどの側面についてもより具体的なアドバイスを提供して欲しいですか、あるいはより詳しく分析して欲しい特定のパラメータはありますか?

Available Tools

3 tools
getLatestShotIdB

Get latest espresso shot id.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states what the tool does but doesn't add context on traits like whether it's read-only, requires authentication, has rate limits, or what the return format might be. This leaves significant gaps for an agent to understand how to invoke it correctly.

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 description is a single, clear sentence with zero waste, front-loading the essential information. It's appropriately sized for a simple tool with no parameters, making it highly efficient and easy to parse.

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

Completeness2/5

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

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., the format of the shot ID or any error cases), which is crucial for an agent to use it effectively. For a tool with no structured output documentation, more context is needed.

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 has 0 parameters, and schema description coverage is 100%, so there's no need for parameter details in the description. The baseline for this scenario is 4, as the description doesn't need to compensate for any parameter gaps, and it efficiently avoids unnecessary information.

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?

The description clearly states the verb ('Get') and resource ('latest espresso shot id'), making the purpose specific and understandable. However, it doesn't differentiate from sibling tools like 'getShotData' or 'getStatus', which might retrieve related information, so it doesn't reach the highest score.

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?

No guidance is provided on when to use this tool versus alternatives like 'getShotData' or 'getStatus'. The description implies it's for retrieving the latest shot ID, but there's no explicit context, exclusions, or comparisons to help an agent choose appropriately.

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

getShotDataC

Get espresso shot data for an id.

Args:
    id: Shot id
ParametersJSON Schema
NameRequiredDescriptionDefault
idYes

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions 'Get' which implies a read operation, but doesn't disclose behavioral traits such as error handling, data format, permissions needed, or rate limits. This is a significant gap for a tool with no annotation coverage.

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

Conciseness4/5

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

The description is brief and front-loaded with the main purpose, followed by a parameter explanation. It avoids unnecessary words, but the structure could be improved by integrating the parameter info more seamlessly or adding context in a single coherent sentence.

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

Completeness2/5

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

Given no annotations, no output schema, and low schema coverage, the description is incomplete. It lacks details on return values, error cases, or how it interacts with sibling tools. For a tool with one parameter but undefined behavior, this is inadequate.

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

Parameters3/5

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

The schema description coverage is 0%, but the description adds meaning by specifying that 'id' is a 'Shot id'. This clarifies the parameter's purpose beyond the schema's basic type. However, it doesn't detail format, constraints, or examples, so it only partially compensates for the low coverage.

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?

The description clearly states the action ('Get espresso shot data') and the resource ('for an id'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'getLatestShotId' or 'getStatus', which might retrieve related data, so it doesn't reach the highest score.

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?

No guidance is provided on when to use this tool versus alternatives like 'getLatestShotId' or 'getStatus'. The description only states what it does, without context on prerequisites, scenarios, or exclusions, leaving the agent to infer usage.

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

getStatusB

Get espresso machine status.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Get') but doesn't clarify what 'status' entails (e.g., operational state, error codes, maintenance info), response format, or any side effects like rate limits or authentication needs. This leaves significant gaps for a tool with no structured safety hints.

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 description is extremely concise—a single sentence with no wasted words. It front-loads the core purpose ('Get espresso machine status') effectively, making it easy to parse quickly.

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

Completeness2/5

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

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the 'status' return value includes (e.g., JSON structure, possible states), which is critical for an agent to use the tool correctly. For a tool with no structured output, more context is needed.

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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate here, and it implies no inputs are required, aligning with the schema. A baseline of 4 is given since no parameters exist.

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?

The description clearly states the verb ('Get') and resource ('espresso machine status'), making the purpose specific and understandable. It doesn't explicitly distinguish from sibling tools like 'getLatestShotId' or 'getShotData', but the resource focus is clear enough for basic differentiation.

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 provides no guidance on when to use this tool versus alternatives like 'getLatestShotId' or 'getShotData'. It lacks context about prerequisites, timing, or exclusions, leaving the agent to infer usage based on tool names alone.

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.

  1. 3 tool updatesv1.0.0
    • First observedgetLatestShotId
    • First observedgetShotData
    • First observedgetStatus
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

B3.1/5.0

Scored across 3 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: getLatestShotId retrieves the most recent shot identifier, getShotData fetches detailed data for a specific shot ID, and getStatus provides machine status information. There is no overlap or ambiguity between these functions.

Naming Consistency5/5

All three tools follow a consistent verb_noun pattern with camelCase naming (getLatestShotId, getShotData, getStatus). The naming is predictable and uniform throughout the set.

Tool Count2/5

With only 3 tools, the set feels thin for an espresso machine control server. There are obvious gaps in functionality, such as tools to start/stop shots, adjust settings, or manage profiles, which limits the server's utility for comprehensive machine interaction.

Completeness2/5

The tool surface is severely incomplete for an espresso machine domain. It only provides read-only operations (getLatestShotId, getShotData, getStatus) with no ability to control the machine (e.g., start_shot, set_temperature), update configurations, or manage other critical aspects like brewing profiles or maintenance.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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