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Hermes Search MCP Server

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Hermes 검색 MCP 서버 🔍

🔌 Cline, Cursor, Claude Desktop 및 기타 MCP 클라이언트와 호환됩니다!

MCP(Model Context Protocol)는 AI 시스템이 다양한 데이터 소스 및 도구와 원활하게 상호 작용할 수 있도록 하는 개방형 표준으로, 안전한 양방향 연결을 용이하게 합니다.

Hermes Search MCP 서버는 다음을 제공합니다.

  • 구조화/비구조화 데이터에 대한 전체 텍스트 및 의미 검색 기능

  • Azure Cognitive Search의 문서 인덱싱 및 관리

  • 사용자 정의 가능한 매개변수를 통한 효율적인 검색 작업

  • TypeScript를 사용한 유형 안전 작업

필수 조건 🔧

시작하기 전에 다음 사항을 확인하세요.

  • Azure Cognitive Search 서비스 및 자격 증명

  • 클로드 데스크탑 또는 커서

  • Node.js(v20 이상)

  • Git 설치됨(Git 설치 방법을 사용하는 경우에만 필요)

Related MCP server: Azure AI Search MCP Server

Hermes Search MCP 서버 설치 ⚡

NPX로 실행

지엑스피1

Smithery를 통해 설치

Smithery를 통해 Claude Desktop에 Hermes Search MCP Server를 자동으로 설치하려면:

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

MCP 클라이언트 구성 ⚙️

Cline 구성 🤖

Cline에 Hermes Search MCP 서버를 설정하는 가장 쉬운 방법은 마켓플레이스를 통해 한 번의 클릭으로 설정하는 것입니다.

  1. VS Code에서 Cline 열기

  2. 사이드바에서 Cline 아이콘을 클릭하세요

  3. "MCP 서버" 탭(4개 사각형)으로 이동합니다.

  4. "Hermes Search"를 검색하고 "설치"를 클릭하세요.

  5. 메시지가 표시되면 Azure Cognitive Search 자격 증명을 입력하세요.

또는 Cline에서 Hermes Search MCP 서버를 수동으로 설정할 수 있습니다.

  1. Cline MCP 설정 파일을 엽니다.

# 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 검색 서버 구성을 파일에 추가합니다.

{
  "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. 파일을 저장하고 Cline이 이미 실행 중이면 다시 시작합니다.

커서 구성 🖥️

참고 : 커서 버전 0.45.6 이상이 필요합니다.

커서에서 Hermes Search MCP 서버를 설정하려면:

  1. 커서 설정 열기

  2. 기능 > MCP 서버로 이동

  3. "+ 새 MCP 서버 추가" 버튼을 클릭하세요

  4. 다음 정보를 입력하세요:

    • 이름 : 서버의 별명을 입력하세요(예: "hermes-search-mcp")

    • 유형 : 유형으로 "명령"을 선택하세요

    • 명령어 : 서버를 실행하기 위한 명령어를 입력하세요: GXP5

    중요 : 환경 변수를 Azure Cognitive Search 자격 증명으로 바꾸세요.

Claude Desktop 앱 구성하기 🖥️

macOS의 경우:

# 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"

Windows의 경우:

code %APPDATA%\Claude\claude_desktop_config.json

Hermes 검색 서버 구성을 추가합니다.

{
  "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 데스크톱 앱에서의 사용법 🎯

설치가 완료되고 Claude 데스크톱 앱 구성이 완료되면 Claude 데스크톱 앱을 완전히 닫았다가 다시 열어야 hermes-search-mcp 서버를 확인할 수 있습니다. 앱 왼쪽 하단에 사용 가능한 MCP 도구를 나타내는 검색 아이콘이 표시됩니다.

Hermes 검색 예시

  1. 문서 검색 :

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

  1. 인덱스 내용 :

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

  1. 인덱스 삭제 :

Delete the current Azure Cognitive Search index.

문제 해결 🛠️

일반적인 문제

  1. 서버를 찾을 수 없습니다

    • npm --version 실행하여 npm 설치를 확인하세요.

    • Claude Desktop 구성 구문 확인

    • node --version 실행하여 Node.js가 제대로 설치되었는지 확인하세요.

  2. Azure Search 자격 증명 문제

    • Azure Cognitive Search 자격 증명이 유효한지 확인하세요.

    • 구성에서 자격 증명이 올바르게 설정되었는지 확인하세요.

    • 자격 증명 주위에 공백이나 따옴표가 없는지 확인하세요.

  3. 인덱스 액세스 문제

    • Azure Cognitive Search 서비스에 인덱스가 있는지 확인하세요.

    • 인덱스 권한 확인

    • API 키에 적절한 액세스 권한이 있는지 확인하세요.

감사의 말 ✨

  • MCP 사양을 위한 모델 컨텍스트 프로토콜

  • 클로드 데스크탑을 위한 인류학

  • 인지 검색을 위한 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

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