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Prometheus MCP Server

by pab1it0

Prometheus MCP サーバー

Prometheus 用のモデル コンテキスト プロトコル(MCP) サーバー。

これにより、標準化された MCP インターフェースを介して Prometheus メトリックとクエリにアクセスできるようになり、AI アシスタントが PromQL クエリを実行してメトリック データを分析できるようになります。

特徴

  • [x] Prometheusに対してPromQLクエリを実行する

  • [x] 指標の発見と探索

    • [x] 利用可能なメトリックの一覧

    • [x] 特定のメトリックのメタデータを取得する

    • [x] 即時クエリ結果を表示

    • [x] 異なるステップ間隔で範囲クエリの結果を表示する

  • [x] 認証サポート

    • [x] 環境変数からの基本認証

    • [x] 環境変数からのベアラートークン認証

  • [x] Dockerコンテナ化のサポート

  • [x] AIアシスタントのためのインタラクティブツールを提供する

ツールリストは設定可能なので、MCPクライアントで利用できるようにするツールを選択できます。特定の機能を使用しない場合や、コンテキストウィンドウをあまり占有したくない場合に便利です。

Related MCP server: Prometheus MCP Server

使用法

  1. この MCP サーバーを実行する環境から Prometheus サーバーにアクセスできることを確認します。

  2. .envファイルまたはシステム環境変数を使用して、Prometheus サーバーの環境変数を構成します。

# Required: Prometheus configuration
PROMETHEUS_URL=http://your-prometheus-server:9090

# Optional: Authentication credentials (if needed)
# Choose one of the following authentication methods if required:

# For basic auth
PROMETHEUS_USERNAME=your_username
PROMETHEUS_PASSWORD=your_password

# For bearer token auth
PROMETHEUS_TOKEN=your_token

# Optional: For multi-tenant setups like Cortex, Mimir or Thanos
ORG_ID=your_organization_id
  1. サーバー設定をクライアント設定ファイルに追加します。例えば、Claude Desktopの場合は以下のようになります。

{
  "mcpServers": {
    "prometheus": {
      "command": "uv",
      "args": [
        "--directory",
        "<full path to prometheus-mcp-server directory>",
        "run",
        "src/prometheus_mcp_server/main.py"
      ],
      "env": {
        "PROMETHEUS_URL": "http://your-prometheus-server:9090",
        "PROMETHEUS_USERNAME": "your_username",
        "PROMETHEUS_PASSWORD": "your_password"
      }
    }
  }
}

注意: Claude Desktop でError: spawn uv ENOENT表示される場合は、 uvへのフル パスを指定するか、構成で環境変数NO_UV=1を設定する必要があります。

Dockerの使用

このプロジェクトには、簡単な展開と分離を実現する Docker サポートが含まれています。

ビルド済みのDockerイメージ

このプロジェクトを使用する最も簡単な方法は、GitHub Container Registry から事前に構築されたイメージを使用することです。

docker pull ghcr.io/pab1it0/prometheus-mcp-server:latest

タグを使用して特定のバージョンを使用することもできます。

docker pull ghcr.io/pab1it0/prometheus-mcp-server:1.0.0

ローカルでDockerイメージを構築する

自分でイメージを構築する場合:

docker build -t prometheus-mcp-server .

Dockerで実行する

Docker を使用してサーバーを実行するにはいくつかの方法があります。

事前にビルドされたイメージで docker run を使用する:

docker run -it --rm \
  -e PROMETHEUS_URL=http://your-prometheus-server:9090 \
  -e PROMETHEUS_USERNAME=your_username \
  -e PROMETHEUS_PASSWORD=your_password \
  ghcr.io/pab1it0/prometheus-mcp-server:latest

ローカルでビルドされたイメージで docker run を使用する:

docker run -it --rm \
  -e PROMETHEUS_URL=http://your-prometheus-server:9090 \
  -e PROMETHEUS_USERNAME=your_username \
  -e PROMETHEUS_PASSWORD=your_password \
  prometheus-mcp-server

docker-compose を使用する:

Prometheus の資格情報を使用して.envファイルを作成し、次を実行します。

docker-compose up

Claude Desktop で Docker を実行する

Claude Desktop でコンテナ化されたサーバーを使用するには、環境変数を使用して Docker を使用するように構成を更新します。

{
  "mcpServers": {
    "prometheus": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "-e", "PROMETHEUS_URL",
        "-e", "PROMETHEUS_USERNAME",
        "-e", "PROMETHEUS_PASSWORD",
        "ghcr.io/pab1it0/prometheus-mcp-server:latest"
      ],
      "env": {
        "PROMETHEUS_URL": "http://your-prometheus-server:9090",
        "PROMETHEUS_USERNAME": "your_username",
        "PROMETHEUS_PASSWORD": "your_password"
      }
    }
  }
}

この構成では、変数名のみを指定した-eフラグを使用し、 envオブジェクトに実際の値を指定して、Claude Desktop から Docker コンテナーに環境変数を渡します。

Docker実装に関する注意:Docker設定は、Claudeで正常に動作することが実証されているchess-mcpプロジェクトの構造に合わせて更新されました。新しい実装では、マルチステージビルドプロセスを採用し、シェルスクリプトを介さずにエントリポイントスクリプトを直接実行します。このアプローチにより、MCP通信におけるstdin/stdoutの適切な処理が保証されます。

発達

貢献を歓迎します!ご提案や改善点がありましたら、問題を報告するか、プルリクエストを送信してください。

このプロジェクトは依存関係の管理にuvを使用しています。お使いのプラットフォームの手順に従ってuvをインストールしてください。

curl -LsSf https://astral.sh/uv/install.sh | sh

次に、次のコマンドで仮想環境を作成し、依存関係をインストールします。

uv venv
source .venv/bin/activate  # On Unix/macOS
.venv\Scripts\activate     # On Windows
uv pip install -e .

プロジェクト構造

プロジェクトはsrcディレクトリ構造で構成されています:

prometheus-mcp-server/
├── src/
│   └── prometheus_mcp_server/
│       ├── __init__.py      # Package initialization
│       ├── server.py        # MCP server implementation
│       ├── main.py          # Main application logic
├── Dockerfile               # Docker configuration
├── docker-compose.yml       # Docker Compose configuration
├── .dockerignore            # Docker ignore file
├── pyproject.toml           # Project configuration
└── README.md                # This file

テスト

このプロジェクトには、機能性を保証し、回帰を防ぐのに役立つ包括的なテスト スイートが含まれています。

pytest でテストを実行します。

# Install development dependencies
uv pip install -e ".[dev]"

# Run the tests
pytest

# Run with coverage report
pytest --cov=src --cov-report=term-missing

テストは次のように分類されます:

  • 構成検証テスト

  • サーバー機能テスト

  • エラー処理テスト

  • 主なアプリケーションテスト

新しい機能を追加する場合は、対応するテストも追加してください。

ツール

道具

カテゴリ

説明

execute_query

クエリ

Prometheusに対してPromQLインスタントクエリを実行する

execute_range_query

クエリ

開始時刻、終了時刻、ステップ間隔を指定してPromQL範囲クエリを実行する

list_metrics

発見

Prometheusで利用可能なすべてのメトリックを一覧表示する

get_metric_metadata

発見

特定のメトリックのメタデータを取得する

get_targets

発見

すべてのスクレイプターゲットに関する情報を取得する

ライセンス

マサチューセッツ工科大学


Available Tools

6 tools
execute_queryExecute PromQL QueryC
Read-onlyIdempotent

Execute a PromQL instant query against Prometheus

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYes
timeNo

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

C2.7/5.0
Behavior2/5

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

Annotations already provide readOnlyHint, destructiveHint, idempotentHint, and openWorldHint. The description adds no behavioral context beyond what is in the schema and annotations.

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

Conciseness3/5

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

The description is a single sentence, which is concise but overly terse. It could be improved with more structure while remaining short.

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?

With 0% schema coverage and no description of parameters, the tool is incomplete for an agent. The output schema exists, but the description does not mention it or the nature of the return value.

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

Parameters1/5

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

Schema description coverage is 0%, yet the description does not explain the parameters. It fails to clarify that 'query' is the PromQL expression and 'time' is optional evaluation time.

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 clearly states the action ('Execute') and the resource ('PromQL instant query against Prometheus'). It distinguishes from the sibling tool 'execute_range_query' which handles range queries.

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 'execute_range_query'. There is no mention of typical use cases or exclusions.

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

execute_range_queryExecute PromQL Range QueryB
Read-onlyIdempotent

Execute a PromQL range query with start time, end time, and step interval

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYes
startYes
endYes
stepYes

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds that it uses PromQL with time parameters, but does not disclose potential failures, pagination, or rate limits. For a tool with rich annotations, the description adds modest extra context.

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, front-loaded sentence with no extraneous words. It efficiently communicates the core action and key parameters.

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?

For a 4-parameter tool with an output schema and comprehensive annotations, the description provides adequate context. It names the parameters and states the tool's purpose. Minor gaps include lack of format details and error behavior, but overall it is mostly complete.

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?

With 0% schema description coverage, the description partially compensates by naming the parameters (start time, end time, step interval). However, it does not specify expected formats (e.g., Unix timestamps or RFC3339) or explain the query parameter beyond 'PromQL range query', leaving ambiguity.

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 tool executes a PromQL range query with start time, end time, and step interval. However, it does not distinguish this from the sibling tool 'execute_query', which likely handles instant queries, missing an opportunity for 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?

No usage guidance is provided. The description does not specify when to use this tool over alternatives (e.g., for time-range versus instant queries), nor does it mention prerequisites or conditions.

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

get_metric_metadataGet Metric MetadataA
Read-onlyIdempotent

Get metadata (type, help, unit) for metrics. Returns all metric metadata when no metric name is provided. Use filter_pattern to search metric names and descriptions.

ParametersJSON Schema
NameRequiredDescriptionDefault
metricNo
filter_patternNo
limitNo
offsetNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint, openWorldHint. The description adds that it returns all metadata when no metric is given and how to use filter_pattern. No contradictions.

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 efficient sentences with no redundancy. The first defines purpose, the second provides usage guidance. Every sentence adds value.

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 output schema present, description covers primary functionality. However, it omits explanation of pagination parameters (limit, offset), which could be important for large result sets. Otherwise complete.

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?

Schema description coverage is 0%, so description must compensate. It explains metric (optional, returns all if null) and filter_pattern (search). But it does not cover limit/offset, leaving pagination behavior unclear. Adequate but not fully compensating.

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 clearly states the tool retrieves metadata (type, help, unit) for metrics. It specifies behavior when no metric name is provided (returns all) and mentions filter_pattern for searching. This distinguishes it from siblings like list_metrics and execute_query.

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?

Provides explicit guidance on using filter_pattern to search. However, it does not mention when not to use the tool or alternatives, but the context is clear enough for an agent to decide.

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

get_targetsGet Scrape TargetsA
Read-onlyIdempotent

Get information about all scrape targets

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A4/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true and destructiveHint=false, so the description reinforces that it is a read operation. It adds that it returns information about all scrape targets, but does not detail what information is included. The output schema likely covers the return format.

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 sentence of 8 words, front-loaded with the key action and resource. Every word is meaningful with no redundancy.

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?

For a tool with no parameters and an existing output schema, the description is reasonably complete. It states the purpose and scope (all targets). A minor gap is the lack of mention of potential pagination or limits, but the output schema likely handles that.

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 zero parameters, and schema description coverage is trivially 100%. The description does not need to add parameter details. The baseline for 0 parameters is 4, and no additional information is necessary.

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 clearly states the verb 'Get' and the resource 'scrape targets', indicating it retrieves information on all scrape targets. It distinguishes from sibling tools like execute_query or get_metric_metadata which perform different operations.

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, such as when to use list_metrics or get_metric_metadata. It lacks explicit context or exclusions for sibling tools.

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

health_checkHealth CheckA
Read-onlyIdempotent

Health check endpoint for container monitoring and status verification

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint, and openWorldHint. The description adds context about container monitoring and status verification, which aligns with annotations and provides additional behavioral clarity.

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?

Single sentence, front-loaded with key information, no wasted words. Highly concise and well-structured.

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 zero parameters and an existing output schema (indicated by 'has output schema: true'), the description is complete enough to understand the tool's purpose and basic behavior.

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?

No parameters are defined, and schema coverage is 100%. Baseline score of 4 applies since the description does not need to compensate for missing parameter details.

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 clearly states it is a health check endpoint for container monitoring and status verification. Specific verb and resource, and it clearly distinguishes from sibling tools like execute_query and list_metrics.

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

Usage Guidelines3/5

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

The description implies usage for checking system status but does not provide explicit guidance on when to use versus alternatives or when not to use. Usage is implied by the tool's purpose and sibling context.

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

list_metricsList Available MetricsA
Read-onlyIdempotent

List all available metrics in Prometheus with optional pagination support

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNo
offsetNo
filter_patternNo
refresh_cacheNo

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the description's note about pagination adds minor behavioral context but is not necessary for safety awareness. No contradictions with 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 description is a single sentence of 10 words, directly stating the purpose and key feature. No unnecessary information.

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?

The description does not cover the purpose of filter_pattern or refresh_cache, nor how pagination behaves (defaults, total count). Given 4 undocumented parameters, the description is incomplete for a full understanding.

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

Parameters2/5

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

Schema description coverage is 0%. The description only hints at pagination (limit/offset) but does not explain filter_pattern or refresh_cache. It fails to compensate for missing schema descriptions on 4 parameters.

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 clearly states 'List all available metrics in Prometheus', specifying the exact resource and action. It distinguishes itself from sibling tools like execute_query and get_metric_metadata by focusing on enumeration of metrics.

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 mentions optional pagination, indicating when to use pagination parameters. However, it lacks explicit guidance on when to use this tool versus alternatives like get_metric_metadata for detailed metric information.

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. 6 tool updatesv1.2.2
    • Changedexecute_query3 fields changed
      • addedInput schema / additionalProperties
        Added value: +false
      • removedInput schema / properties / query / title
        Removed value: -"Query"
      • removedInput schema / properties / time / title
        Removed value: -"Time"
    • Changedexecute_range_query5 fields changed
      • addedInput schema / additionalProperties
        Added value: +false
      • removedInput schema / properties / end / title
        Removed value: -"End"
      • removedInput schema / properties / query / title
        Removed value: -"Query"
      • removedInput schema / properties / start / title
        Removed value: -"Start"
      • removedInput schema / properties / step / title
        Removed value: -"Step"
    • Changedget_metric_metadata14 fields changed
      • addedInput schema / additionalProperties
        Added value: +false
      • addedInput schema / properties / filter_pattern
        Added value: +{
        +  "anyOf": [
        +    {
        +      "type": "string"
        +    },
        +    {
        +      "type": "null"
        +    }
        +  ],
        +  "default": null
        +}
      • addedInput schema / properties / limit
        Added value: +{
        +  "anyOf": [
        +    {
        +      "type": "integer"
        +    },
        +    {
        +      "type": "null"
        +    }
        +  ],
        +  "default": null
        +}
      • addedInput schema / properties / metric / anyOf
        Added value: +[
        +  {
        +    "type": "string"
        +  },
        +  {
        +    "type": "null"
        +  }
        +]
      • addedInput schema / properties / metric / default
        Added value: +null
      • removedInput schema / properties / metric / title
        Removed value: -"Metric"
      • removedInput schema / properties / metric / type
        Removed value: -"string"
      • addedInput schema / properties / offset
        Added value: +{
        +  "default": 0,
        +  "type": "integer"
        +}
      • removedInput schema / required
        Removed value: -[
        -  "metric"
        -]
      • addedOutput schema / properties / result / anyOf
        Added value: +[
        +  {
        +    "items": {
        +      "additionalProperties": true,
        +      "type": "object"
        +    },
        +    "type": "array"
        +  },
        +  {
        +    "additionalProperties": true,
        +    "type": "object"
        +  }
        +]
      • removedOutput schema / properties / result / items
        Removed value: -{
        -  "additionalProperties": true,
        -  "type": "object"
        -}
      • removedOutput schema / properties / result / title
        Removed value: -"Result"
      • removedOutput schema / properties / result / type
        Removed value: -"array"
      • removedOutput schema / title
        Removed value: -"_WrappedResult"
    • Changedget_targets1 field changed
      • addedInput schema / additionalProperties
        Added value: +false
    • Changedhealth_check1 field changed
      • addedInput schema / additionalProperties
        Added value: +false
    • Changedlist_metrics5 fields changed
      • addedInput schema / additionalProperties
        Added value: +false
      • removedInput schema / properties / filter_pattern / title
        Removed value: -"Filter Pattern"
      • removedInput schema / properties / limit / title
        Removed value: -"Limit"
      • removedInput schema / properties / offset / title
        Removed value: -"Offset"
      • addedInput schema / properties / refresh_cache
        Added value: +{
        +  "default": false,
        +  "type": "boolean"
        +}
  2. 6 tool updatesv1.0.0
    • Changedexecute_query2 fields changed
      • removedInput schema / title
        Removed value: -"execute_queryArguments"
      • changedOutput schema / (root)
        Previous value: -nullNew value: +{
        +  "additionalProperties": true,
        +  "type": "object"
        +}
    • Changedexecute_range_query2 fields changed
      • removedInput schema / title
        Removed value: -"execute_range_queryArguments"
      • changedOutput schema / (root)
        Previous value: -nullNew value: +{
        +  "additionalProperties": true,
        +  "type": "object"
        +}
    • Changedget_metric_metadata2 fields changed
      • removedInput schema / title
        Removed value: -"get_metric_metadataArguments"
      • changedOutput schema / (root)
        Previous value: -nullNew value: +{
        +  "properties": {
        +    "result": {
        +      "items": {
        +        "additionalProperties": true,
        +        "type": "object"
        +      },
        +      "title": "Result",
        +      "type": "array"
        +    }
        +  },
        +  "required": [
        +    "result"
        +  ],
        +  "title": "_WrappedResult",
        +  "type": "object",
        +  "x-fastmcp-wrap-result": true
        +}
    • Changedget_targets2 fields changed
      • removedInput schema / title
        Removed value: -"get_targetsArguments"
      • changedOutput schema / (root)
        Previous value: -nullNew value: +{
        +  "additionalProperties": {
        +    "items": {
        +      "additionalProperties": true,
        +      "type": "object"
        +    },
        +    "type": "array"
        +  },
        +  "type": "object"
        +}
    • Addedhealth_check
    • Changedlist_metrics5 fields changed
      • addedInput schema / properties / filter_pattern
        Added value: +{
        +  "anyOf": [
        +    {
        +      "type": "string"
        +    },
        +    {
        +      "type": "null"
        +    }
        +  ],
        +  "default": null,
        +  "title": "Filter Pattern"
        +}
      • addedInput schema / properties / limit
        Added value: +{
        +  "anyOf": [
        +    {
        +      "type": "integer"
        +    },
        +    {
        +      "type": "null"
        +    }
        +  ],
        +  "default": null,
        +  "title": "Limit"
        +}
      • addedInput schema / properties / offset
        Added value: +{
        +  "default": 0,
        +  "title": "Offset",
        +  "type": "integer"
        +}
      • removedInput schema / title
        Removed value: -"list_metricsArguments"
      • changedOutput schema / (root)
        Previous value: -nullNew value: +{
        +  "additionalProperties": true,
        +  "type": "object"
        +}
  3. 5 tool updates
    • First observedexecute_query
    • First observedexecute_range_query
    • First observedget_metric_metadata
    • First observedget_targets
    • First observedlist_metrics

TDQS

A3.7/5.0

Scored across 6 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: query types (instant vs range), metadata retrieval, target info, health check, and metric listing. No overlap.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case (e.g., execute_query, get_metric_metadata). No deviations.

Tool Count5/5

Six tools cover the essential Prometheus operations without being excessive or insufficient. Well-scoped for the server's purpose.

Completeness4/5

Core CRUD-like operations for queries and metadata are present. Minor gaps like alert management or rule configuration are missing but not critical for the primary use case.

Maintenance

ActivityMaintained
ResponsivenessWithin a week

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