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Danelf API

초급

이것은Crypto Trading, AI RAG분야의자동화 워크플로우로, 5개의 노드를 포함합니다.주로 HttpRequestTool, McpTrigger 등의 노드를 사용하며. Danelfin의 AI 분석 API를 사용하여 실시간 주식 분석 및 순위를 가져옵니다.

사전 요구사항
  • 대상 API의 인증 정보가 필요할 수 있음
워크플로우 미리보기
노드 연결 관계를 시각적으로 표시하며, 확대/축소 및 이동을 지원합니다
워크플로우 내보내기
다음 JSON 구성을 복사하여 n8n에 가져오면 이 워크플로우를 사용할 수 있습니다
{
  "id": "e7UIuZcjbSmC6ZO0",
  "meta": {
    "instanceId": "e7ccf4281d5afb175c79c02db95b45f15d5b53862cb6bc357c5e5bc26567f35c",
    "templateCredsSetupCompleted": true
  },
  "name": "danelf api",
  "tags": [],
  "nodes": [
    {
      "id": "b95edee5-b803-43b0-9c52-3ee4be139ecf",
      "name": "Danelfin mcp",
      "type": "@n8n/n8n-nodes-langchain.mcpTrigger",
      "position": [
        32,
        -128
      ],
      "webhookId": "6997e22b-7e96-47f1-ad91-a0784451f2a1",
      "parameters": {
        "path": "danelfin-api",
        "authentication": "headerAuth"
      },
      "credentials": {
        "httpHeaderAuth": {
          "id": "WtAyYH2L9Z9enZqX",
          "name": "danelfin"
        }
      },
      "typeVersion": 2
    },
    {
      "id": "e6b5b592-255f-4a09-8eff-5ca631774096",
      "name": "ranking",
      "type": "n8n-nodes-base.httpRequestTool",
      "position": [
        -64,
        64
      ],
      "parameters": {
        "url": "https://apirest.danelfin.com/ranking",
        "options": {},
        "sendQuery": true,
        "authentication": "genericCredentialType",
        "genericAuthType": "httpHeaderAuth",
        "queryParameters": {
          "parameters": [
            {
              "name": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters0_Name', ``, 'string') }}",
              "value": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters0_Value', ``, 'string') }}"
            },
            {
              "name": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters1_Name', ``, 'string') }}",
              "value": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters1_Value', ``, 'string') }}"
            }
          ]
        },
        "toolDescription": "ranking endpoint"
      },
      "credentials": {
        "httpHeaderAuth": {
          "id": "WtAyYH2L9Z9enZqX",
          "name": "danelfin"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "4c2938e8-1d7a-48e0-9439-107502c4fa8b",
      "name": "sectors",
      "type": "n8n-nodes-base.httpRequestTool",
      "position": [
        128,
        128
      ],
      "parameters": {
        "url": "https://apirest.danelfin.com/sectors",
        "options": {},
        "sendQuery": true,
        "authentication": "genericCredentialType",
        "genericAuthType": "httpHeaderAuth",
        "queryParameters": {
          "parameters": [
            {
              "name": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters0_Name', ``, 'string') }}",
              "value": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters0_Value', ``, 'string') }}"
            },
            {
              "name": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters1_Name', ``, 'string') }}",
              "value": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters1_Value', ``, 'string') }}"
            },
            {
              "name": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters2_Name', ``, 'string') }}",
              "value": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters2_Value', ``, 'string') }}"
            }
          ]
        },
        "toolDescription": "sectors endpoint"
      },
      "credentials": {
        "httpHeaderAuth": {
          "id": "WtAyYH2L9Z9enZqX",
          "name": "danelfin"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "eef0d0ce-263f-4ad1-bdc3-3b46d099a734",
      "name": "industries",
      "type": "n8n-nodes-base.httpRequestTool",
      "position": [
        320,
        112
      ],
      "parameters": {
        "url": "https://apirest.danelfin.com/industries",
        "options": {},
        "sendQuery": true,
        "authentication": "genericCredentialType",
        "genericAuthType": "httpHeaderAuth",
        "queryParameters": {
          "parameters": [
            {
              "name": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters0_Name', ``, 'string') }}",
              "value": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters0_Value', ``, 'string') }}"
            },
            {
              "name": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters1_Name', ``, 'string') }}",
              "value": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters1_Value', ``, 'string') }}"
            }
          ]
        },
        "toolDescription": "industries endpoint"
      },
      "credentials": {
        "httpHeaderAuth": {
          "id": "WtAyYH2L9Z9enZqX",
          "name": "danelfin"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "67a61837-e7a3-4702-aa75-6400fb16dfcf",
      "name": "메모",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -1024,
        -592
      ],
      "parameters": {
        "width": 848,
        "height": 1808,
        "content": "## Danelfin MCP Server\n\n## About Danelfin\n\nDanelfin is an AI-powered stock analytics platform that helps investors find the best stocks and optimize their portfolios with explainable AI insights to make smarter, data-driven investment decisions. The platform uses AI-driven stock analytics to optimize investment strategies.\n\nDanelfin uses Explainable Artificial Intelligence to help everyone make smart and data-driven investment decisions. The platform provides API solutions for developers, analysts, and fintech firms wanting to integrate predictive stock data into their own applications.\n\n## Key Features\n\n- **AI Stock Picker**: Advanced algorithms to identify high-potential stocks\n- **Portfolio Optimization**: Data-driven portfolio management and optimization tools\n- **Explainable AI**: Transparent AI insights that show reasoning behind recommendations\n- **Predictive Analytics**: AI Scores and forecasting capabilities\n- **Multi-Asset Coverage**: Analysis of stocks and ETFs across various markets\n\n## MCP Server Endpoints\n\nThis Danelfin MCP (Model Context Protocol) server exposes three main endpoints that provide comprehensive market analysis capabilities:\n\n### 🏆 `/ranking` Endpoint\n**GET: https://apirest.dan...**\n\nThe ranking endpoint provides AI-powered stock rankings and ratings. This tool allows users to:\n- Access ranked lists of stocks based on AI-generated scores\n- Retrieve performance rankings across different timeframes\n- Get comparative analysis of stock performance\n- Access predictive AI scores for investment decision-making\n\n### 🏭 `/sectors` Endpoint  \n**GET: https://apirest.dan...**\n\nThe sectors endpoint provides analysis for US market stocks including AI ratings, prices, stock charts, technical, fundamental, and sentiment analysis organized by market sectors. Features include:\n- Sector-wise market analysis and performance metrics\n- AI ratings and price data for sector classifications\n- Technical and fundamental analysis by sector\n- Sentiment analysis across different market sectors\n- Comparative sector performance insights\n\n### 🏢 `/industries` Endpoint\n**GET: https://apirest.dan...**\n\nThe industries endpoint offers granular industry-level analysis within market sectors:\n- Industry-specific stock analysis and ratings  \n- Performance metrics at the industry classification level\n- AI-powered insights for specific industry verticals\n- Comparative industry analysis within sectors\n- Industry trend analysis and forecasting\n\n## Integration Benefits\n\nThis MCP server enables seamless integration of Danelfin's AI-powered stock analysis capabilities into applications and workflows. Users can:\n\n- **Access Real-time Data**: Get up-to-date stock rankings, sector performance, and industry analysis\n- **Leverage AI Insights**: Utilize explainable AI recommendations for investment decisions\n- **Streamline Research**: Automate stock research workflows with comprehensive market data\n- **Enhance Decision-Making**: Make data-driven investment choices with predictive analytics\n- **Scale Analysis**: Process large-scale market analysis across multiple dimensions\n\n## Use Cases\n\n- **Investment Research**: Comprehensive stock analysis and ranking for portfolio managers\n- **Algorithmic Trading**: Integration of AI scores into trading algorithms and strategies  \n- **Financial Advisory**: Enhanced client advisory services with AI-powered insights\n- **Risk Management**: Sector and industry analysis for portfolio risk assessment\n- **Market Analysis**: Real-time market intelligence for institutional investors\n\nThe Danelfin MCP server bridges the gap between advanced AI stock analytics and practical investment applications, providing developers and financial professionals with powerful tools for data-driven market analysis."
      },
      "typeVersion": 1
    }
  ],
  "active": true,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "92572d67-f8e8-4eb1-bfeb-5177f64b7d09",
  "connections": {
    "e6b5b592-255f-4a09-8eff-5ca631774096": {
      "ai_tool": [
        [
          {
            "node": "b95edee5-b803-43b0-9c52-3ee4be139ecf",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "4c2938e8-1d7a-48e0-9439-107502c4fa8b": {
      "ai_tool": [
        [
          {
            "node": "b95edee5-b803-43b0-9c52-3ee4be139ecf",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "eef0d0ce-263f-4ad1-bdc3-3b46d099a734": {
      "ai_tool": [
        [
          {
            "node": "b95edee5-b803-43b0-9c52-3ee4be139ecf",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    }
  }
}
자주 묻는 질문

이 워크플로우를 어떻게 사용하나요?

위의 JSON 구성 코드를 복사하여 n8n 인스턴스에서 새 워크플로우를 생성하고 "JSON에서 가져오기"를 선택한 후, 구성을 붙여넣고 필요에 따라 인증 설정을 수정하세요.

이 워크플로우는 어떤 시나리오에 적합한가요?

초급 - 암호화폐 거래, AI RAG

유료인가요?

이 워크플로우는 완전히 무료이며 직접 가져와 사용할 수 있습니다. 다만, 워크플로우에서 사용하는 타사 서비스(예: OpenAI API)는 사용자 직접 비용을 지불해야 할 수 있습니다.

워크플로우 정보
난이도
초급
노드 수5
카테고리2
노드 유형3
난이도 설명

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