natural_query

Processes natural language queries to retrieve structured data about leads, contacts, and opportunities from Ambivo MCP Server, enabling efficient data extraction in table, natural, or both formats.

Instructions

Execute natural language queries against Ambivo entity data. This tool processes natural language queries and returns structured data about leads, contacts, opportunities, and other entities.

Input Schema

Name	Required	Description	Default
`query`	Yes	Natural language query describing what data you want to retrieve. Examples: 'Show me leads created this week', 'Find contacts with gmail addresses', 'List opportunities worth more than $10,000'
`response_format`	No	Format of the response: 'table' for structured data, 'natural' for natural language description, 'both' for both formats	both

Input Schema (JSON Schema)

{
  "properties": {
    "query": {
      "description": "Natural language query describing what data you want to retrieve. Examples: 'Show me leads created this week', 'Find contacts with gmail addresses', 'List opportunities worth more than $10,000'",
      "type": "string"
    },
    "response_format": {
      "default": "both",
      "description": "Format of the response: 'table' for structured data, 'natural' for natural language description, 'both' for both formats",
      "enum": [
        "table",
        "natural",
        "both"
      ],
      "type": "string"
    }
  },
  "required": [
    "query"
  ],
  "type": "object"
}

Ambivo MCP Server

natural_query

Instructions

Input Schema

Input Schema (JSON Schema)

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MCP directory API