Data Activation Companies Server

Overview

The Data Activation Companies Server specializes in analyzing identified company/account data. It provides comprehensive insights into company engagement, intent signals, buying stages, and firmographic information.

Server Details

Server Name: data-activation-companies-server
Version: 0.0.1
Endpoint: /mcp/data-activation-companies
Authentication: Organization-level required

Purpose

Analyze identified companies and accounts, track their engagement patterns, intent signals, buying stages, and firmographic attributes to identify opportunities and understand account behavior.

Available Tools

1. companies-schema-tool

Purpose: Get field mappings for the Companies index

When to use: Before constructing queries to understand available fields

Returns: Elasticsearch mapping with field names, types, and descriptions

2. companies-compute-tool

Purpose: Execute Elasticsearch queries against the Companies index

Input: Elasticsearch query JSON Returns: Query results with matching companies and aggregations

3. terminology-tool

Purpose: Translate abbreviations and business terms

4. alert-filters-tool

Purpose: Retrieve alert filter configurations

5. settings-signal-trends-tool

Purpose: Retrieve signal trend settings

6. settings-buying-stages-scoring-tool

Purpose: Retrieve buying stage scoring rules

7. chart-format-tool

Purpose: Generate Chart.js configurations for visualizing data

8. company-links-tool

Purpose: Generate clickable links to company profiles

Key Fields

Identity Fields

Uuid - Unique company identifier
Name - Company name
Domain - Company domain
Website - Company website URL

Scoring Fields

Icp - ICP (Ideal Customer Profile) score (0-100)
Intent - Intent score (0-100)
Intent Signals - Array of intent signals detected
Intent Trends - Intent trend direction (rising, stable, declining)

Buying Stage Fields

Buying Stage - Current buying stage (Awareness, Consideration, Decision, Purchase)
Lifecycle Stage - Lifecycle stage
Awareness Date - When account entered Awareness stage
Consideration Date - When account entered Consideration stage
Decision Date - When account entered Decision stage
Purchase Date - When account entered Purchase stage

Engagement Fields

Page Views - Total page views
Unique Pages - Number of unique pages visited
Total Active Time - Total time spent on site (seconds)
Visitors Count - Number of identified visitors
Urls - Array of URLs visited
Last Touch Date - Most recent engagement date
First Touch Date - First engagement date

Firmographic Fields

Industry - Company industry
Sub Industry - Sub-industry classification
Employees - Employee count
Employees Range - Employee range category
Annual Revenue - Annual revenue (if available)
City - Company city
State - Company state/province
Country - Company country

Technology Fields

Tech - Array of technologies used
Tech Categories - Technology categories

Identification Fields

Identified People - Number of identified people
Identified People Emails - Array of identified email addresses

Attribution Fields

First Touch Channel - First touch channel
First Touch UTM Source - First touch UTM source
First Touch UTM Medium - First touch UTM medium
First Touch UTM Campaign - First touch UTM campaign

CRM Fields

CRM Owner - CRM owner name
CRM Owner Email - CRM owner email

Common Use Cases

1. High-ICP Accounts with Strong Intent

{
  "query": {
    "bool": {
      "filter": [
        {"range": {"Icp": {"gte": 70}}},
        {"range": {"Intent": {"gte": 60}}}
      ]
    }
  },
  "_source": ["Uuid", "Name", "Domain", "Icp", "Intent", "Buying Stage", "Industry"],
  "sort": [
    {"Intent": "desc"},
    {"Icp": "desc"}
  ],
  "size": 50
}

2. Accounts by Buying Stage

{
  "size": 0,
  "aggs": {
    "by_stage": {
      "terms": {"field": "Buying Stage.keyword", "size": 10},
      "aggs": {
        "avg_icp": {"avg": {"field": "Icp"}},
        "avg_intent": {"avg": {"field": "Intent"}},
        "total_accounts": {"value_count": {"field": "Uuid.keyword"}}
      }
    }
  }
}

3. Recently Engaged Accounts

{
  "query": {
    "bool": {
      "filter": [
        {"range": {"Last Touch Date": {"gte": "now-7d/d"}}},
        {"range": {"Page Views": {"gte": 3}}}
      ]
    }
  },
  "_source": ["Uuid", "Name", "Domain", "Last Touch Date", "Page Views", "Unique Pages", "Urls"],
  "sort": [{"Last Touch Date": "desc"}],
  "size": 100
}

4. Accounts by Industry with High ICP

{
  "query": {
    "range": {"Icp": {"gte": 70}}
  },
  "size": 0,
  "aggs": {
    "by_industry": {
      "terms": {
        "field": "Industry.keyword",
        "size": 20,
        "order": {"avg_icp": "desc"}
      },
      "aggs": {
        "avg_icp": {"avg": {"field": "Icp"}},
        "avg_intent": {"avg": {"field": "Intent"}},
        "account_count": {"value_count": {"field": "Uuid.keyword"}}
      }
    }
  }
}

5. Accounts Using Specific Technology

{
  "query": {
    "bool": {
      "filter": [
        {"wildcard": {"Tech": "*salesforce*"}},
        {"range": {"Icp": {"gte": 60}}}
      ]
    }
  },
  "_source": ["Uuid", "Name", "Domain", "Tech", "Tech Categories", "Icp"],
  "size": 50
}

6. Accounts Viewing Specific Pages

{
  "query": {
    "bool": {
      "should": [
        {"wildcard": {"Urls": "*pricing*"}},
        {"wildcard": {"Urls": "*demo*"}},
        {"wildcard": {"Urls": "*contact*"}}
      ],
      "minimum_should_match": 1,
      "filter": [
        {"range": {"Icp": {"gte": 70}}}
      ]
    }
  },
  "_source": ["Uuid", "Name", "Domain", "Urls", "Last Touch Date", "Icp"],
  "size": 100
}

7. Accounts with Multiple Identified People

{
  "query": {
    "bool": {
      "filter": [
        {"range": {"Identified People": {"gte": 3}}},
        {"range": {"Icp": {"gte": 70}}}
      ]
    }
  },
  "_source": ["Uuid", "Name", "Domain", "Identified People", "Identified People Emails", "Icp"],
  "sort": [{"Identified People": "desc"}],
  "size": 50
}

8. Accounts by Company Size

{
  "query": {
    "bool": {
      "filter": [
        {"range": {"Employees": {"gte": 100, "lte": 1000}}},
        {"range": {"Icp": {"gte": 60}}}
      ]
    }
  },
  "size": 0,
  "aggs": {
    "by_size_range": {
      "terms": {"field": "Employees Range.keyword", "size": 10},
      "aggs": {
        "avg_icp": {"avg": {"field": "Icp"}},
        "avg_intent": {"avg": {"field": "Intent"}}
      }
    }
  }
}

9. Accounts with Rising Intent

{
  "query": {
    "bool": {
      "filter": [
        {"term": {"Intent Trends.keyword": "rising"}},
        {"range": {"Intent": {"gte": 50}}}
      ]
    }
  },
  "_source": ["Uuid", "Name", "Domain", "Intent", "Intent Trends", "Intent Signals", "Icp"],
  "sort": [{"Intent": "desc"}],
  "size": 50
}

10. Geographic Distribution

{
  "query": {
    "bool": {
      "filter": [
        {"term": {"Country.keyword": "United States"}},
        {"range": {"Icp": {"gte": 70}}}
      ]
    }
  },
  "size": 0,
  "aggs": {
    "by_state": {
      "terms": {"field": "State.keyword", "size": 20},
      "aggs": {
        "account_count": {"value_count": {"field": "Uuid.keyword"}},
        "avg_icp": {"avg": {"field": "Icp"}}
      }
    }
  }
}

11. Accounts by First Touch Channel

{
  "query": {
    "range": {"First Touch Date": {"gte": "now-90d/d"}}
  },
  "size": 0,
  "aggs": {
    "by_channel": {
      "terms": {"field": "First Touch Channel.keyword", "size": 15},
      "aggs": {
        "account_count": {"value_count": {"field": "Uuid.keyword"}},
        "avg_icp": {"avg": {"field": "Icp"}},
        "high_intent_count": {
          "filter": {"range": {"Intent": {"gte": 70}}}
        }
      }
    }
  }
}

12. Stage Progression Analysis

{
  "query": {
    "bool": {
      "filter": [
        {"exists": {"field": "Decision Date"}},
        {"range": {"Decision Date": {"gte": "now-30d/d"}}}
      ]
    }
  },
  "_source": [
    "Uuid", "Name", "Domain",
    "First Touch Date", "Awareness Date", "Consideration Date", "Decision Date",
    "Icp", "Intent"
  ],
  "sort": [{"Decision Date": "desc"}],
  "size": 50
}

Best Practices

1. Always Check Schema First

Call companies-schema-tool before querying to ensure correct field names.

2. Use Wildcard for Text Search

Unless exact match is explicitly requested:

{"wildcard": {"Name": "*acme*"}}

3. Combine ICP and Intent for Prioritization

{
  "query": {
    "bool": {
      "filter": [
        {"range": {"Icp": {"gte": 70}}},
        {"range": {"Intent": {"gte": 60}}}
      ]
    }
  }
}

4. Include Key Fields in _source

Always include: Uuid, Name, Domain for generating company links.

5. Use .keyword for Exact Matches

For text fields that need exact matching:

{"term": {"Industry.keyword": "Technology"}}

6. Leverage Engagement Metrics

Combine scoring with engagement for better insights:

{
  "query": {
    "bool": {
      "filter": [
        {"range": {"Icp": {"gte": 70}}},
        {"range": {"Page Views": {"gte": 5}}},
        {"range": {"Last Touch Date": {"gte": "now-14d/d"}}}
      ]
    }
  }
}

7. Apply Date Filters

For time-sensitive queries, always filter by date fields:

{"range": {"Last Touch Date": {"gte": "now-30d/d"}}}

8. Generate Clickable Links

After retrieving accounts, call company-links-tool to provide easy access.

Query Patterns

Strong Buying Signals

Interpret as: Intent high OR Intent Signals exists OR Intent Trends rising

{
  "query": {
    "bool": {
      "should": [
        {"range": {"Intent": {"gte": 70}}},
        {"exists": {"field": "Intent Signals"}},
        {"term": {"Intent Trends.keyword": "rising"}}
      ],
      "minimum_should_match": 1
    }
  }
}

Multiple Filters Combined

{
  "query": {
    "bool": {
      "filter": [
        {"range": {"Icp": {"gte": 70}}},
        {"term": {"Buying Stage.keyword": "Decision"}},
        {"term": {"Industry.keyword": "Technology"}},
        {"range": {"Employees": {"gte": 100}}},
        {"range": {"Last Touch Date": {"gte": "now-7d/d"}}}
      ]
    }
  }
}

Aggregations for Insights

{
  "size": 0,
  "aggs": {
    "icp_distribution": {
      "histogram": {"field": "Icp", "interval": 10}
    },
    "intent_distribution": {
      "histogram": {"field": "Intent", "interval": 10}
    },
    "stage_breakdown": {
      "terms": {"field": "Buying Stage.keyword"}
    }
  }
}

Overview​

Server Details​

Purpose​

Available Tools​

1. companies-schema-tool​

2. companies-compute-tool​

3. terminology-tool​

4. alert-filters-tool​

5. settings-signal-trends-tool​

6. settings-buying-stages-scoring-tool​

7. chart-format-tool​

8. company-links-tool​

Key Fields​

Identity Fields​

Scoring Fields​

Buying Stage Fields​

Engagement Fields​

Firmographic Fields​

Technology Fields​

Identification Fields​

Attribution Fields​

CRM Fields​

Common Use Cases​

1. High-ICP Accounts with Strong Intent​

2. Accounts by Buying Stage​

3. Recently Engaged Accounts​

4. Accounts by Industry with High ICP​

5. Accounts Using Specific Technology​

6. Accounts Viewing Specific Pages​

7. Accounts with Multiple Identified People​

8. Accounts by Company Size​

9. Accounts with Rising Intent​

10. Geographic Distribution​

11. Accounts by First Touch Channel​

12. Stage Progression Analysis​

Best Practices​

1. Always Check Schema First​

2. Use Wildcard for Text Search​

3. Combine ICP and Intent for Prioritization​

4. Include Key Fields in _source​

5. Use .keyword for Exact Matches​

6. Leverage Engagement Metrics​

7. Apply Date Filters​

8. Generate Clickable Links​

Query Patterns​

Strong Buying Signals​

Multiple Filters Combined​

Aggregations for Insights​