Skip to main content
Glama
enesjakozh
Cognitive-Stack

Hermes Search MCP Server

by Cognitive-Stack
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Hermes Search MCP サーバー 🔍

🔌 Cline、Cursor、Claude Desktop、その他の MCP クライアントと互換性があります。

モデル コンテキスト プロトコル (MCP) は、AI システムがさまざまなデータ ソースやツールとシームレスに対話し、安全な双方向接続を実現できるようにするオープン スタンダードです。

Hermes Search MCP サーバーは以下を提供します。

  • 構造化/非構造化データに対する全文検索およびセマンティック検索機能

  • Azure Cognitive Search におけるドキュメントのインデックス作成と管理

  • カスタマイズ可能なパラメータによる効率的な検索操作

  • TypeScriptによる型安全な操作

前提条件🔧

始める前に、次のものを用意してください。

  • Azure Cognitive Search サービスと資格情報

  • クロードデスクトップまたはカーソル

  • Node.js (v20以上)

  • Git がインストールされている (Git インストール方法を使用する場合のみ必要)

Related MCP server: Azure AI Search MCP Server

Hermes Search MCP サーバーのインストール ⚡

NPXで実行

npx -y hermes-search-mcp@latest

Smithery経由でインストール

Smithery 経由で Claude Desktop 用の Hermes Search MCP Server を自動的にインストールするには:

npx -y @smithery/cli install @hermes-search/mcp --client claude

MCP クライアントの設定 ⚙️

Cline の設定 🤖

Cline で Hermes Search MCP サーバーをセットアップする最も簡単な方法は、マーケットプレイスから 1 回のクリックでセットアップすることです。

  1. VS CodeでClineを開く

  2. サイドバーのClineアイコンをクリックします

  3. 「MCPサーバー」タブ（4つの四角）に移動します

  4. 「Hermes Search」を検索し、「インストール」をクリックします

  5. プロンプトが表示されたら、Azure Cognitive Search の資格情報を入力します。

あるいは、Cline で Hermes Search MCP サーバーを手動で設定することもできます。

  1. Cline MCP 設定ファイルを開きます。

# For macOS:
code ~/Library/Application\ Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json

# For Windows:
code %APPDATA%\Code\User\globalStorage\saoudrizwan.claude-dev\settings\cline_mcp_settings.json

  1. Hermes Search サーバーの構成をファイルに追加します。

{
  "mcpServers": {
    "hermes-search-mcp": {
      "command": "npx",
      "args": ["-y", "hermes-search-mcp@latest"],
      "env": {
        "AZURE_SEARCH_ENDPOINT": "your-search-endpoint",
        "AZURE_SEARCH_API_KEY": "your-api-key",
        "AZURE_SEARCH_INDEX_NAME": "your-index-name"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}

  1. ファイルを保存し、Cline がすでに実行されている場合は再起動します。

カーソルの設定 🖥️

注: カーソルバージョン0.45.6以上が必要です

Cursor で Hermes Search MCP サーバーを設定するには:

  1. カーソル設定を開く

  2. 機能 > MCP サーバーに移動します

  3. 「+新しいMCPサーバーを追加」ボタンをクリックします。

  4. 以下の情報を入力してください。

    • 名前: サーバーのニックネームを入力します（例：「hermes-search-mcp」）

    • タイプ: タイプとして「コマンド」を選択

    • コマンド: サーバーを実行するコマンドを入力してください: GXP5

    重要: 環境変数をAzure Cognitive Searchの資格情報に置き換えてください

Claude デスクトップ アプリの設定 🖥️

macOSの場合:

# Create the config file if it doesn't exist
touch "$HOME/Library/Application Support/Claude/claude_desktop_config.json"

# Opens the config file in TextEdit
open -e "$HOME/Library/Application Support/Claude/claude_desktop_config.json"

Windowsの場合:

code %APPDATA%\Claude\claude_desktop_config.json

Hermes Search サーバーの構成を追加します。

{
  "mcpServers": {
    "hermes-search-mcp": {
      "command": "npx",
      "args": ["-y", "hermes-search-mcp@latest"],
      "env": {
        "AZURE_SEARCH_ENDPOINT": "your-search-endpoint",
        "AZURE_SEARCH_API_KEY": "your-api-key",
        "AZURE_SEARCH_INDEX_NAME": "your-index-name"
      }
    }
  }
}

Claude デスクトップアプリでの使用 🎯

インストールが完了し、Claudeデスクトップアプリの設定が完了したら、Claudeデスクトップアプリを完全に閉じて再度開くと、hermes-search-mcpサーバーが表示されます。アプリの左下に検索アイコンが表示され、利用可能なMCPツールが表示されます。

エルメスの検索例

  1. ドキュメントを検索:

Search for documents containing "machine learning" in the Azure Cognitive Search index, returning the top 10 results.

  1. インデックスコンテンツ:

Index the following documents into Azure Cognitive Search: [{"id": "1", "title": "AI Overview", "content": "Artificial Intelligence is..."}]

  1. インデックスを削除:

Delete the current Azure Cognitive Search index.

トラブルシューティング 🛠️

よくある問題

  1. サーバーが見つかりません

    • npm --versionを実行して npm のインストールを確認します。

    • Claude Desktop の設定構文を確認する

    • node --versionを実行して Node.js が正しくインストールされていることを確認します。

  2. Azure Search 資格情報の問題

    • Azure Cognitive Search の資格情報が有効であることを確認します

    • 構成で資格情報が正しく設定されていることを確認します

    • 資格情報の周囲にスペースや引用符がないことを確認してください

  3. インデックスアクセスの問題

    • Azure Cognitive Search サービスにインデックスが存在することを確認する

    • インデックスの権限を確認する

    • APIキーに適切なアクセス権があることを確認する

謝辞✨

  • MCP仕様のモデルコンテキストプロトコル

  • クロード・デスクトップのAnthropic

  • コグニティブサーチのための Microsoft Azure

Available Tools

3 tools
delete-indexA

Delete the Azure Cognitive Search index

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are present, and the description lacks details about behavioral traits such as permanence, required permissions, or side effects. As a destructive operation, more transparency is needed.

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, well-structured sentence with no extraneous words. It is concise and front-loaded with the key action.

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

Completeness3/5

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

For a simple delete operation with no parameters or output schema, the description is minimally complete. However, it lacks context about effects or prerequisites, which would improve completeness.

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?

With no parameters, the baseline is 4. The description adds minimal but adequate meaning by specifying the operation type and target, which suffices given the absence of 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 the verb 'Delete' and the resource 'Azure Cognitive Search index', making the action unambiguous. It effectively distinguishes from sibling tools like index-content and search-documents.

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 (e.g., when deletion is appropriate or prerequisites). The description only states the action without context.

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

index-contentB

Index or update documents in Azure Cognitive Search

ParametersJSON Schema
NameRequiredDescriptionDefault
documentsYesArray of documents to index

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It only states 'Index or update' without explaining side effects, permissions, or whether documents are overwritten or merged. This is insufficient for a mutation tool.

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 a single sentence, front-loaded with purpose, and is not verbose. However, it sacrifices necessary details for brevity, missing usage and behavioral context.

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 simple schema (1 param, no output schema) and lack of annotations, the description is too minimal. It fails to explain document handling (e.g., partial updates, conflict resolution) or the indexing process.

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 100%, providing a baseline of 3. The description repeats the schema's 'Array of documents to index' without adding extra meaning, such as required fields or document structure.

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 ('Index or update') and the resource ('documents in Azure Cognitive Search'), with a specific verb and resource. It distinguishes from sibling tools 'delete-index' and 'search-documents' by focusing on adding/updating.

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 its siblings. There is no mention of prerequisites or alternative tools for deletion or searching, leaving the agent without context for selection.

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

search-documentsB

Search documents in Azure Cognitive Search index

ParametersJSON Schema
NameRequiredDescriptionDefault
topNoNumber of results to return (default: 5)
queryYesThe search query to execute
filterNoOData filter expression
selectNoFields to include in the results

TDQS

B3.1/5.0
Behavior2/5

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

No annotations provided, and the description does not disclose behavioral traits like pagination, relevance scoring, access requirements, or result format.

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 a single sentence, which is concise. However, it is somewhat underspecified for a search tool.

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 output schema and no annotations, the description is too minimal. It does not explain search behavior, result structure, or how parameters interact, leaving significant gaps for an AI agent.

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 100%, so baseline is 3. The description adds no additional meaning beyond the schema.

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 (Search) and resource (documents in Azure Cognitive Search index), and distinguishes from sibling tools (delete-index, index-content) which have different purposes.

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 on when to use this tool vs alternatives. No mention of prerequisites, limitations, or exclusions.

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 observeddelete-index
    • First observedindex-content
    • First observedsearch-documents
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

A3.5/5.0

Scored across 3 tools

Disambiguation5/5

Each tool targets a distinct operation: deleting an index, indexing content, and searching documents. No overlap in purpose.

Naming Consistency5/5

All tools follow a consistent verb-noun pattern with hyphens (delete-index, index-content, search-documents), making them predictable.

Tool Count4/5

Three tools is on the low side but covers the core search lifecycle (index, search, delete). Slightly under but reasonable for a focused MCP server.

Completeness3/5

Missing critical operations like creating an index or listing indexes. The server assumes an existing index, limiting its standalone usability.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

Related MCP Connectors

Related MCP Servers

Appeared in Searches