Sales Prioritization Server

Surface the accounts in Purchase and Decision buying stages: the ones your sales team should be calling right now.

Overview

The Sales Prioritization Server specializes in identifying high-priority accounts that are ready for sales engagement. It focuses exclusively on companies in the Purchase or Decision buying stages - the hottest accounts for your sales team.

Server Details

Server Name: sales-prioritization-server
Version: 0.0.1
Endpoint: /mcp/sales-prioritization
Authentication: Organization-level required

Purpose

Identify and analyze accounts that are sales-ready, helping sales teams prioritize their outreach to companies showing strong buying intent and engagement signals.

Available Tools

1. sales-prio-buying-stages-schema-tool

Purpose: Get field mappings for the SalesPrioBuyingStages index

When to use: Before constructing any query to understand available fields

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

2. sales-prio-buying-stages-compute-tool

Purpose: Execute Elasticsearch queries against sales-ready accounts

Input: Elasticsearch query JSON Returns: Query results with matching accounts

Note: All queries automatically filter for Buying Stage = "Purchase" OR "Decision"

3. chart-format-tool

Purpose: Generate Chart.js configurations for visualizing sales data

4. company-links-tool

Purpose: Generate clickable links to company profiles

Input:

{
  "companies": [
    { "uuid": "abc-123", "label": "Acme Corp" },
    { "uuid": "def-456", "label": "TechCo Inc" }
  ]
}

Returns: Array of clickable links to company detail pages

Key Concepts

Buying Stages

The server automatically filters for these high-priority stages:

Purchase: Companies actively looking to buy (highest priority)
Decision: Companies in final decision-making phase (high priority)

You do NOT need to add buying stage filters to your queries - this is handled automatically.

ICP Score

ICP (Ideal Customer Profile) score ranges from 0-100:

90-100: Perfect fit for your ICP
70-89: Strong fit
50-69: Moderate fit
Below 50: Weak fit

Intent Score

Intent score indicates buying intent strength:

High (70-100): Strong buying signals
Medium (40-69): Moderate interest
Low (0-39): Early research phase

Common Use Cases

1. Top 20 High-ICP Accounts Ready for Sales

Workflow:

Call sales-prio-buying-stages-schema-tool to verify fields
Call sales-prio-buying-stages-compute-tool:

{
  "query": {
    "range": { "Icp": { "gte": 70 } }
  },
  "_source": [
    "Uuid",
    "Name",
    "Domain",
    "Icp",
    "Intent",
    "Buying Stage",
    "Industry"
  ],
  "sort": [{ "Icp": "desc" }],
  "size": 20
}

Call company-links-tool to generate clickable links

2. High-Intent Accounts by Industry

{
  "query": {
    "range": { "Intent": { "gte": 70 } }
  },
  "size": 0,
  "aggs": {
    "by_industry": {
      "terms": {
        "field": "Industry.keyword",
        "size": 10,
        "order": { "avg_intent": "desc" }
      },
      "aggs": {
        "avg_intent": { "avg": { "field": "Intent" } },
        "avg_icp": { "avg": { "field": "Icp" } },
        "account_count": { "value_count": { "field": "Uuid.keyword" } }
      }
    }
  }
}

3. Accounts with Specific Technology Stack

{
  "query": {
    "bool": {
      "filter": [
        { "range": { "Icp": { "gte": 70 } } },
        { "wildcard": { "Tech": "*salesforce*" } }
      ]
    }
  },
  "_source": ["Uuid", "Name", "Domain", "Tech", "Icp", "Intent"],
  "size": 50
}

4. Large Enterprise Accounts (by Employee Count)

{
  "query": {
    "bool": {
      "filter": [
        { "range": { "Employees": { "gte": 1000 } } },
        { "range": { "Icp": { "gte": 60 } } }
      ]
    }
  },
  "_source": [
    "Uuid",
    "Name",
    "Domain",
    "Employees",
    "Annual Revenue",
    "Icp",
    "Intent"
  ],
  "sort": [{ "Employees": "desc" }],
  "size": 30
}

5. Accounts by Geographic Region

{
  "query": {
    "bool": {
      "filter": [
        { "term": { "Country.keyword": "United States" } },
        { "terms": { "State.keyword": ["California", "New York", "Texas"] } }
      ]
    }
  },
  "size": 0,
  "aggs": {
    "by_state": {
      "terms": { "field": "State.keyword", "size": 10 },
      "aggs": {
        "avg_icp": { "avg": { "field": "Icp" } },
        "high_intent_count": {
          "filter": { "range": { "Intent": { "gte": 70 } } }
        }
      }
    }
  }
}

6. Recently Engaged Accounts

{
  "query": {
    "bool": {
      "filter": [
        { "range": { "Last Touch Date": { "gte": "now-7d/d" } } },
        { "range": { "Page Views": { "gte": 5 } } }
      ]
    }
  },
  "_source": [
    "Uuid",
    "Name",
    "Domain",
    "Last Touch Date",
    "Page Views",
    "Unique Pages",
    "Intent"
  ],
  "sort": [{ "Last Touch Date": "desc" }],
  "size": 50
}

7. 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",
    "Icp",
    "Intent",
    "Last Touch Date"
  ],
  "size": 50
}

Best Practices

1. Always Check Schema First

Call sales-prio-buying-stages-schema-tool before querying to ensure correct field names.

2. Don't Filter by Buying Stage

The server automatically filters for Purchase and Decision stages. Adding your own buying stage filter is redundant.

3. Include Key Fields in _source

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

4. Use ICP and Intent for Prioritization

Combine ICP score and Intent score to identify the best accounts:

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

5. Leverage Engagement Metrics

Use fields like Page Views, Unique Pages, Total Active Time, and Last Touch Date to identify actively engaged accounts.

6. Generate Clickable Links

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

Query Patterns

Combining Multiple Filters

{
  "query": {
    "bool": {
      "filter": [
        { "range": { "Icp": { "gte": 70 } } },
        { "range": { "Intent": { "gte": 60 } } },
        { "term": { "Industry.keyword": "Technology" } },
        { "range": { "Employees": { "gte": 100, "lte": 5000 } } }
      ]
    }
  }
}

Text Search with Wildcards

{
  "query": {
    "bool": {
      "should": [
        { "wildcard": { "Name": "*enterprise*" } },
        { "wildcard": { "Domain": "*enterprise*" } }
      ],
      "minimum_should_match": 1
    }
  }
}

Sorting by Multiple Fields

{
  "sort": [
    { "Intent": "desc" },
    { "Icp": "desc" },
    { "Last Touch Date": "desc" }
  ]
}

Aggregations for Insights

{
  "size": 0,
  "aggs": {
    "icp_distribution": {
      "histogram": {
        "field": "Icp",
        "interval": 10
      }
    },
    "top_industries": {
      "terms": {
        "field": "Industry.keyword",
        "size": 10
      }
    },
    "avg_metrics": {
      "stats": {
        "field": "Intent"
      }
    }
  }
}

Workflow Example

Goal: Find top 10 technology companies with high ICP and recent engagement

Step 1: Check schema

Call: sales-prio-buying-stages-schema-tool

Step 2: Query accounts

{
  "query": {
    "bool": {
      "filter": [
        { "term": { "Industry.keyword": "Technology" } },
        { "range": { "Icp": { "gte": 75 } } },
        { "range": { "Last Touch Date": { "gte": "now-14d/d" } } },
        { "range": { "Page Views": { "gte": 3 } } }
      ]
    }
  },
  "_source": [
    "Uuid",
    "Name",
    "Domain",
    "Icp",
    "Intent",
    "Page Views",
    "Last Touch Date"
  ],
  "sort": [{ "Intent": "desc" }, { "Icp": "desc" }],
  "size": 10
}

Step 3: Generate links

{
  "companies": [
    { "uuid": "result-uuid-1", "label": "Company Name 1" },
    { "uuid": "result-uuid-2", "label": "Company Name 2" }
  ]
}

Step 4: Present results with insights

Show company names as clickable links
Highlight key metrics (ICP, Intent, engagement)
Provide actionable recommendations for sales team

Overview​

Server Details​

Purpose​

Available Tools​

1. sales-prio-buying-stages-schema-tool​

2. sales-prio-buying-stages-compute-tool​

3. chart-format-tool​

4. company-links-tool​

Key Concepts​

Buying Stages​

ICP Score​

Intent Score​

Common Use Cases​

1. Top 20 High-ICP Accounts Ready for Sales​

2. High-Intent Accounts by Industry​

3. Accounts with Specific Technology Stack​

4. Large Enterprise Accounts (by Employee Count)​

5. Accounts by Geographic Region​

6. Recently Engaged Accounts​

7. Accounts Viewing Specific Pages​

Best Practices​

1. Always Check Schema First​

2. Don't Filter by Buying Stage​

3. Include Key Fields in _source​

4. Use ICP and Intent for Prioritization​

5. Leverage Engagement Metrics​

6. Generate Clickable Links​

Query Patterns​

Combining Multiple Filters​

Text Search with Wildcards​

Sorting by Multiple Fields​

Aggregations for Insights​

Workflow Example​