Explorium MCP - Slack-Bot

Fortgeschritten

Dies ist ein Support Chatbot, AI Chatbot-Bereich Automatisierungsworkflow mit 13 Nodes. Hauptsächlich werden If, Set, Code, Slack, HttpRequest und andere Nodes verwendet. Slack-Business-Intelligence-Assistent mit Explorium MCP und Claude AI

Voraussetzungen
  • Slack Bot Token oder Webhook URL
  • Möglicherweise sind Ziel-API-Anmeldedaten erforderlich
  • Anthropic API Key
Workflow-Vorschau
Visualisierung der Node-Verbindungen, mit Zoom und Pan
Workflow exportieren
Kopieren Sie die folgende JSON-Konfiguration und importieren Sie sie in n8n
{
  "id": "nKluKJXe6qIz7tnR",
  "meta": {
    "instanceId": "0a70652f43c1b29dd16c35b61a38fd31c8004f58bc7e723bf43262a797407c77",
    "templateCredsSetupCompleted": true
  },
  "name": "Explorium MCP - Slack Bot",
  "tags": [],
  "nodes": [
    {
      "id": "2cdc96cf-c1b6-4177-ba58-6feae2c38bb5",
      "name": "Notizzettel",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        5472,
        -256
      ],
      "parameters": {
        "width": 640,
        "height": 880,
        "content": "## 1. Create Slack App\n\n### Create App\n1. Go to api.slack.com/apps\n2. Click **Create New App** → **From scratch**\n3. Give it name (e.g., \"Explorium Agent\") and select workspace\n\n### Bot Permissions (OAuth & Permissions)\nAdd these **Bot Token Scopes**:\n```\napp_mentions:read\nchannels:history\nchannels:read\nchat:write\nemoji:read\ngroups:history\ngroups:read\nim:history\nim:read\nmpim:history\nmpim:read\nreactions:read\nusers:read\n```\n\n### Enable Events\n1. **Event Subscriptions** → Enable\n2. Add **Request URL** (from n8n Slack Trigger node)\n3. Subscribe to **bot events**:\n   - app_mention\n   - message.channels\n   - message.groups\n   - message.im\n   - message.mpim\n   - reaction_added\n\n### Install App\n1. **Install App** → **Install to Workspace**\n2. Copy **Bot User OAuth Token** (xoxb-...)\n"
      },
      "typeVersion": 1
    },
    {
      "id": "cbb39059-80ea-45b3-8cf3-65b39b7aed52",
      "name": "Notizzettel1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        6160,
        -256
      ],
      "parameters": {
        "width": 640,
        "height": 608,
        "content": "## 2. Configure n8n\n\n### Import & Setup\n1. Import this JSON template\n2. **Slack Trigger** node:\n   - Add Slack credential with Bot Token\n   - Copy webhook URL\n   - Paste in Slack Event Subscriptions Request URL\n\n3. **Anthropic Chat Model** node:\n   - Add Anthropic API credential\n   - Model: claude-haiku-4-5-20251001\n\n(You can replace it with other chat models)\n\n4. **MCP Client** node:\n   - Endpoint: https://mcp.explorium.ai/mcp\n   - Header Auth: Add Explorium API key\n\n\n## Usage Examples\n```\n@Bot find tech companies in SF with 50-200 employees\n@Bot show Microsoft's technology stack\n@Bot get CMO contacts at healthcare companies\n```"
      },
      "typeVersion": 1
    },
    {
      "id": "fdf690d4-4175-47a8-8a55-9b9051a5d9af",
      "name": "Notizzettel2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        5472,
        -560
      ],
      "parameters": {
        "width": 2912,
        "height": 256,
        "content": "# Explorium Agent for Slack\n\nAI-powered Slack bot for business intelligence queries using Explorium API through MCP.\n\n## Prerequisites\n- Slack workspace with admin access\n- Anthropic API key (You can replace with other LLM Chat)\n- Explorium API Key\n"
      },
      "typeVersion": 1
    },
    {
      "id": "68135d6e-9061-4e6b-a4fc-b0bacadff82c",
      "name": "Slack Trigger",
      "type": "n8n-nodes-base.slackTrigger",
      "position": [
        6848,
        -160
      ],
      "webhookId": "5d3fa63f-ef0a-48f1-9550-d95e527fba61",
      "parameters": {
        "options": {
          "resolveIds": true
        },
        "trigger": [
          "app_mention"
        ],
        "watchWorkspace": true
      },
      "credentials": {},
      "typeVersion": 1
    },
    {
      "id": "82327159-f01d-433f-bd6a-6a66489eb568",
      "name": "Prüfe ob Thread",
      "type": "n8n-nodes-base.if",
      "position": [
        7072,
        -160
      ],
      "parameters": {
        "options": {},
        "conditions": {
          "options": {
            "combineOperation": "any"
          },
          "conditions": [
            {
              "id": "condition1",
              "operator": {
                "type": "string",
                "operation": "notEmpty"
              },
              "leftValue": "={{ $json.thread_ts }}",
              "rightValue": ""
            }
          ]
        }
      },
      "typeVersion": 2
    },
    {
      "id": "fa24f726-de97-46a5-91e9-da0ace8b2ef5",
      "name": "Hole Thread-Nachrichten",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        7296,
        -256
      ],
      "parameters": {
        "url": "https://slack.com/api/conversations.replies",
        "options": {},
        "sendQuery": true,
        "authentication": "predefinedCredentialType",
        "queryParameters": {
          "parameters": [
            {
              "name": "channel",
              "value": "={{ $json.channel }}"
            },
            {
              "name": "ts",
              "value": "={{ $json.thread_ts }}"
            }
          ]
        },
        "nodeCredentialType": "slackApi"
      },
      "credentials": {},
      "typeVersion": 4.2
    },
    {
      "id": "4ab45f74-0e4d-4686-af3c-3b6865adb3d5",
      "name": "Formatiere Thread-Kontext",
      "type": "n8n-nodes-base.code",
      "position": [
        7520,
        -256
      ],
      "parameters": {
        "jsCode": "// Get the original trigger data from the first item\nconst triggerData = $('Slack Trigger').first().json;\n\n// Get thread messages from Slack API response\nconst slackResponse = $input.first().json;\nconst messagesList = slackResponse.messages || [];\n\n// Build thread context from all messages\nlet threadContext = '';\nif (messagesList.length > 1) {\n  threadContext = messagesList\n    .map((msg, idx) => {\n      const text = msg.text || '';\n      const user = msg.user || 'Unknown';\n      const isBot = msg.bot_id ? ' (bot)' : '';\n      return `Message ${idx + 1} from ${user}${isBot}: ${text}`;\n    })\n    .join('\\n');\n}\n\n// Get current message text\nconst currentText = triggerData.text || (triggerData.blocks && triggerData.blocks[0] && triggerData.blocks[0].elements && triggerData.blocks[0].elements[0] && triggerData.blocks[0].elements[0].elements && triggerData.blocks[0].elements[0].elements[1] ? triggerData.blocks[0].elements[0].elements[1].text : '');\n\n// Combine context with current message\nconst finalText = messagesList.length > 1 \n  ? `Thread Context:\\n${threadContext}\\n\\nCurrent Message: ${currentText}`\n  : currentText;\n\nreturn {\n  channel: triggerData.channel || '',\n  ts: triggerData.ts || '',\n  thread_ts: triggerData.thread_ts || '',\n  type: triggerData.type || '',\n  text: finalText,\n  original_text: currentText,\n  is_bot: triggerData.bot_id ? true : false,\n  user: triggerData.user || '',\n  is_thread_continuation: triggerData.thread_ts ? true : false,\n  session_id: triggerData.thread_ts || triggerData.ts,\n  reaction: triggerData.reaction || '',\n  item_ts: triggerData.item ? triggerData.item.ts : '',\n  is_emoji: triggerData.blocks && triggerData.blocks[0] && triggerData.blocks[0].elements && triggerData.blocks[0].elements[0] && triggerData.blocks[0].elements[0].elements && triggerData.blocks[0].elements[0].elements[0] && triggerData.blocks[0].elements[0].elements[0].type === 'emoji' ? true : false,\n  has_thread_context: messagesList.length > 1\n};"
      },
      "typeVersion": 2
    },
    {
      "id": "32e8b75b-844f-4cb7-9f1d-a1e9621a7b6c",
      "name": "Formatiere ohne Thread",
      "type": "n8n-nodes-base.set",
      "position": [
        7520,
        -64
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "2c1ec1ad-72f2-4bcd-bfef-dc12f49de48b",
              "name": "channel",
              "type": "string",
              "value": "={{ $json.channel || '' }}"
            },
            {
              "id": "af7e1d94-946c-4257-824e-a5d91a2b007a",
              "name": "ts",
              "type": "string",
              "value": "={{ $json.ts || '' }}"
            },
            {
              "id": "28583957-bddd-4bd2-b937-79b7554a7a65",
              "name": "thread_ts",
              "type": "string",
              "value": "={{ $json.thread_ts || '' }}"
            },
            {
              "id": "53179618-0ca1-43a2-a416-af8a39f792e0",
              "name": "type",
              "type": "string",
              "value": "={{ $json.type || '' }}"
            },
            {
              "id": "fbe15475-5924-41fa-a7b1-6017ae766a23",
              "name": "text",
              "type": "string",
              "value": "={{ $json.text || ($json.blocks && $json.blocks[0] && $json.blocks[0].elements && $json.blocks[0].elements[0] && $json.blocks[0].elements[0].elements && $json.blocks[0].elements[0].elements[1] ? $json.blocks[0].elements[0].elements[1].text : '') }}"
            },
            {
              "id": "49376ca5-079b-4993-9f15-6847734d9c5d",
              "name": "is_bot",
              "type": "boolean",
              "value": "={{ $json.bot_id ? true : false }}"
            },
            {
              "id": "b0ae1eed-7adf-49d2-b19d-0a1efdb5f435",
              "name": "user",
              "type": "string",
              "value": "={{ $json.user || '' }}"
            },
            {
              "id": "13fab869-b570-444d-903b-11d4b4f0ebe6",
              "name": "is_thread_continuation",
              "type": "boolean",
              "value": "={{ $json.thread_ts ? true : false }}"
            },
            {
              "id": "a148580e-6fe3-4689-be2f-7996c54f6118",
              "name": "session_id",
              "type": "string",
              "value": "={{ $json.thread_ts || $json.ts }}"
            },
            {
              "id": "311146c6-e6cf-492e-a4a9-09066e927879",
              "name": "reaction",
              "type": "string",
              "value": "={{ $json.reaction || '' }}"
            },
            {
              "id": "1b358df2-7062-4c7b-be7d-28bc69611322",
              "name": "item_ts",
              "type": "string",
              "value": "={{ $json.item ? $json.item.ts : '' }}"
            },
            {
              "id": "1e9d1f5a-4e0a-4ed8-8e23-660fe8b6a950",
              "name": "is_emoji",
              "type": "boolean",
              "value": "={{ $json.blocks && $json.blocks[0] && $json.blocks[0].elements && $json.blocks[0].elements[0] && $json.blocks[0].elements[0].elements && $json.blocks[0].elements[0].elements[0] && $json.blocks[0].elements[0].elements[0].type === 'emoji' ? true : false }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "cc74fb30-c9ba-4837-8af3-15fc79c91c0b",
      "name": "Explorium Agent",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        7800,
        -160
      ],
      "parameters": {
        "text": "={{ $json.text }}",
        "options": {
          "systemMessage": "=You are **Explorium Business Intelligence Agent**, created by Explorium.  \n\nAdvanced Explorium API agent with comprehensive business intelligence data through MCP.\n\n## Core Capabilities\n\n### Company Intelligence\n• Discovery: Search by industry, size, revenue, location, technology, growth metrics\n• Firmographics: Profiles, employee counts, revenue, industry classifications  \n• Technographics: Technology stacks, software usage, digital infrastructure\n• Financial Data: Revenue trends, funding rounds, investor information, financial metrics for public companies\n• Company Ratings: Employee satisfaction, company culture, work-life balance, management quality\n• Competitive Analysis: Market positioning, competitive landscape, strategic insights\n• Strategic Intelligence: Strategic focus areas, value propositions, target markets from SEC filings\n• Business Challenges: Risk analysis, security breaches, competitive pressures from public disclosures\n• Events: Funding, product launches, partnerships, office changes, business developments\n• Workforce Analytics: Department composition, hiring trends, organizational structure\n• Social Intelligence: LinkedIn posts, website changes, digital presence\n• Website Intelligence: Keyword searches, content analysis, website changes tracking\n• Market Statistics: Aggregated industry insights, geographic distribution, revenue analysis\n\n### Prospect Intelligence  \n• Discovery: Find executives, decision-makers by role, company, industry, experience\n• Contact Enrichment: Professional/personal emails, phone numbers, verification\n• Profiles: Work history, education, skills, career progression\n• Role Intelligence: Current positions, job levels, departments, reporting structure\n• Social Activity: LinkedIn posts, engagement metrics, professional content\n• Career Events: Job changes, promotions, role transitions, anniversaries\n\n### Analytics & Communication\n• Market Research: Industry trends, competitive positioning, landscape analysis\n• Investment Intelligence: Funding rounds, investor networks, financial milestones\n• Growth Tracking: Company expansion, headcount changes, business evolution\n• Personalized Outreach: Targeted messaging using real-time business intelligence\n• Trigger-Based Communication: Messages based on events, role changes, milestones\n• Smart Autocomplete: Intelligent suggestions for industries, technologies, job titles, locations\n• Web Search: General web search capabilities for additional context and research\n\n## Response Guidelines\n\n### Workflow\n1. **Discovery**: Search companies/prospects using filters\n2. **Intelligence**: Enrich with detailed data\n3. **Analysis**: Analyze trends, patterns, competitive insights  \n4. **Action**: Generate personalized messages, recommendations, strategic insights\n\n### Communication\n• Always mention using **\"Explorium API\"** (never internal function names)\n• **Keep responses concise and focused** - provide essential information without unnecessary elaboration\n• State total matches found and suggest relevant enrichments\n• When responding to thread conversations, consider the full context provided\n• Format your responses for slack, the output will be post in slack so it should looks good and well formated there. use the slack guidelines below and not md format (for example for headline use *Some Header* and not **Some Header**):\n\nSlack Guidelines:\n*bold text* - makes text bold\n_italic text_ - makes text italic\n~strikethrough~ - strikes through text\n`code` - inline code formatting\n```code block``` - multi-line code block\n\n- Use asterisk + space for bullet points\n- Like this\n\n1. Numbered lists\n2. Work like this\n\n<https://example.com|Link text> - creates a clickable link\n<@U123ABC> - mentions a user (using their user ID)\n<#C123ABC|channel-name> - links to a channel\n\n> Quoted text\n> Continues on next line\n\n--- \n\nCreates a horizontal line\n```\n\n### Error Handling\n• Tool errors/no data: respond **\"An error occurred.\"**\n• Invalid queries: guide toward valid parameters\n• Off-topic requests: redirect to business intelligence use cases\n\n## Off-Topic Handling\nFor non-business intelligence requests:\n\n> I'm the Explorium Business Intelligence Agent, designed to demonstrate our comprehensive company and prospect intelligence platform.  \n>   \n> **Example capabilities:**  \n> • Find SaaS firms in New York with 50‑200 employees  \n> • Show Microsoft's technology stack  \n> • Get marketing‑director contacts at healthcare companies  \n> • Compare funding rounds of fintech startups\n>   \n> What business intelligence would you like to explore?\n\n## Technical Notes\n• Use autocomplete for industries, technologies, job titles, company categories before filtering\n• Combine multiple criteria for precise targeting and comprehensive results\n• Prioritize recent data and real-time insights over historical data\n• Maintain conversation context for follow-up enrichments and related queries\n• Use web search for general information, news, and context not available in business intelligence data\n• Leverage aggregated statistics tools for market-level insights and trends\n• Provide alternative search strategies when initial queries fail\n• When using fetch_prospects or fetch_businesses tools limit the results (size and page_size) to 5 results\n• Thread context is automatically provided when responding to messages in a thread",
          "returnIntermediateSteps": false
        },
        "promptType": "define"
      },
      "typeVersion": 2.1
    },
    {
      "id": "533e4626-aeb0-42e1-a55c-452229bdcfcc",
      "name": "Anthropic Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
      "position": [
        7744,
        64
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "claude-haiku-4-5-20251001",
          "cachedResultName": "Claude Haiku 4.5"
        },
        "options": {}
      },
      "credentials": {},
      "typeVersion": 1.3
    },
    {
      "id": "2504c14b-2d58-467d-ac40-d4a1317b8a7a",
      "name": "Simple Memory",
      "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
      "position": [
        7872,
        64
      ],
      "parameters": {
        "sessionKey": "={{ $json.session_id }}",
        "sessionIdType": "customKey",
        "contextWindowLength": 20
      },
      "typeVersion": 1.3
    },
    {
      "id": "95bcd5f2-ffd7-4925-95ae-7fc5f9e32937",
      "name": "Explorium MCP",
      "type": "@n8n/n8n-nodes-langchain.mcpClientTool",
      "position": [
        8000,
        64
      ],
      "parameters": {
        "options": {},
        "endpointUrl": "https://mcp.explorium.ai/mcp",
        "authentication": "headerAuth"
      },
      "credentials": {},
      "typeVersion": 1.2
    },
    {
      "id": "cb0f9fbf-1150-4a70-be4d-2d459376e52c",
      "name": "Sende eine Nachricht",
      "type": "n8n-nodes-base.slack",
      "position": [
        8208,
        -160
      ],
      "webhookId": "a840217b-6faa-474a-9cc5-21bcbb9c8db8",
      "parameters": {
        "text": "={{ $json.output }}",
        "select": "channel",
        "channelId": {
          "__rl": true,
          "mode": "id",
          "value": "={{ $item(\"0\").$node[\"Slack Trigger\"].json[\"channel\"] }}"
        },
        "otherOptions": {
          "thread_ts": {
            "replyValues": {
              "thread_ts": "={{ $item(\"0\").$node[\"Slack Trigger\"].json[\"thread_ts\"] || $item(\"0\").$node[\"Slack Trigger\"].json[\"ts\"] }}"
            }
          },
          "includeLinkToWorkflow": false
        }
      },
      "credentials": {},
      "typeVersion": 2.3
    }
  ],
  "active": true,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "34a61d7c-9ded-4af2-b24d-b462106cfe11",
  "connections": {
    "95bcd5f2-ffd7-4925-95ae-7fc5f9e32937": {
      "ai_tool": [
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            "index": 0
          }
        ]
      ]
    },
    "2504c14b-2d58-467d-ac40-d4a1317b8a7a": {
      "ai_memory": [
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            "type": "ai_memory",
            "index": 0
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    "533e4626-aeb0-42e1-a55c-452229bdcfcc": {
      "ai_languageModel": [
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            "type": "ai_languageModel",
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}
Häufig gestellte Fragen

Wie verwende ich diesen Workflow?

Kopieren Sie den obigen JSON-Code, erstellen Sie einen neuen Workflow in Ihrer n8n-Instanz und wählen Sie "Aus JSON importieren". Fügen Sie die Konfiguration ein und passen Sie die Anmeldedaten nach Bedarf an.

Für welche Szenarien ist dieser Workflow geeignet?

Fortgeschritten - Support-Chatbot, KI-Chatbot

Ist es kostenpflichtig?

Dieser Workflow ist völlig kostenlos. Beachten Sie jedoch, dass Drittanbieterdienste (wie OpenAI API), die im Workflow verwendet werden, möglicherweise kostenpflichtig sind.

Workflow-Informationen
Schwierigkeitsgrad
Fortgeschritten
Anzahl der Nodes13
Kategorie2
Node-Typen11
Schwierigkeitsbeschreibung

Für erfahrene Benutzer, mittelkomplexe Workflows mit 6-15 Nodes

Autor
explorium

explorium

@explorium

Explorium empowers businesses to build high-performance GTM agents with specialized data infrastructure. Our seamless API integrations and high-quality data drive faster agent development and better results. With years of experience and robust data sets, we deliver context-aware solutions, helping AI agents achieve human-level support. Explorium is the essential data partner for teams building agent-driven technologies.

Externe Links
Auf n8n.io ansehen

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Kategorien

Kategorien: 34