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Ambivo MCP Server

Ambivo MCP Server

Official
by ambivo-corp

Ambivo Claude MCP Server

This Claude MCP (Model Context Protocol) server provides access to Ambivo API endpoints for natural language querying of entity data with Claude AI.

Features

  • Natural Language Queries: Execute natural language queries against entity data using the /entity/natural_query endpoint

  • JWT Authentication: Secure access using Bearer token authentication

  • Rate Limiting: Built-in rate limiting to prevent API abuse

  • Token Caching: Efficient token validation with caching

  • Error Handling: Comprehensive error handling with detailed error messages

  • Retry Logic: Automatic retry with exponential backoff for failed requests

Related MCP server: Dataverse MCP Server

Tools

1. set_auth_token

Set the JWT Bearer token for authentication with the Ambivo API.

Parameters:

  • token (string, required): JWT Bearer token

Usage:

{
  "token": "your-jwt-token-here"
}

2. natural_query

Execute natural language queries against Ambivo entity data.

Parameters:

  • query (string, required): Natural language query describing what data you want

  • response_format (string, optional): Response format - "table", "natural", or "both" (default: "both")

Example queries:

  • "Show me leads created this week"

  • "Find contacts with gmail addresses"

  • "List opportunities worth more than $10,000"

  • "Show me leads with attribution_source google_ads from the last 7 days"

Usage:

{
  "query": "Show me leads created this week with attribution_source google_ads",
  "response_format": "both"
}

About

This is a pure Claude-based MCP server implementation for the Ambivo API, designed to work seamlessly with Claude Desktop and other Claude-compatible MCP clients. It enables natural language interaction with your Ambivo CRM data through Claude's powerful language understanding capabilities.

Installation

pip install ambivo-mcp-server

Option 2: Install from Source

git clone https://github.com/ambivo-corp/ambivo-mcp-server.git
cd ambivo-mcp-server
pip install -e .

Running the Server

# If installed via pip
ambivo-mcp-server

# Or using Python module
python -m ambivo_mcp_server.server

Configuration

The server uses the following default configuration:

  • Base URL: https://goferapi.ambivo.com

  • Timeout: 30 seconds

  • Content Type: application/json

You can modify these settings in the AmbivoAPIClient class if needed.

Authentication

  1. First, set your authentication token using the set_auth_token tool

  2. The token will be included in all subsequent API requests as a Bearer token

  3. The token should be a valid JWT token from your Ambivo API authentication

Error Handling

The server provides comprehensive error handling:

  • Authentication errors: Clear messages when token is missing or invalid

  • HTTP errors: Detailed HTTP status codes and response messages

  • Validation errors: Parameter validation with helpful error messages

  • Network errors: Timeout and connection error handling

API Endpoints

This MCP server interfaces with these Ambivo API endpoints:

/entity/natural_query

  • Method: POST

  • Purpose: Process natural language queries for entity data retrieval

  • Authentication: Required (JWT Bearer token)

  • Content-Type: application/json

/entity/data

  • Method: POST

  • Purpose: Direct entity data access with structured parameters

  • Authentication: Required (JWT Bearer token)

  • Content-Type: application/json

Example Workflow

  1. Set Authentication:

    {
      "tool": "set_auth_token",
      "arguments": {
        "token": "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9..."
      }
    }
  2. Natural Language Query:

    {
      "tool": "natural_query", 
      "arguments": {
        "query": "Show me all leads created in the last 30 days with phone numbers",
        "response_format": "both"
      }
    }
  3. Direct Entity Query:

    {
      "tool": "entity_data",
      "arguments": {
        "entity_type": "contact",
        "filters": {"email": {"$regex": "@gmail.com$"}},
        "limit": 100,
        "sort": {"created_date": -1}
      }
    }

Development

To extend this MCP server:

  1. Add new tools: Implement additional tools in the handle_list_tools() and handle_call_tool() functions

  2. Modify API client: Extend the AmbivoAPIClient class to support additional endpoints

  3. Update configuration: Modify default settings in the configuration section

Troubleshooting

Common Issues:

  1. "Authentication required" error: Ensure you've called set_auth_token first

  2. HTTP 401/403 errors: Verify your JWT token is valid and not expired

  3. Connection timeout: Check network connectivity and API endpoint availability

  4. Invalid parameters: Review the tool schemas for required and optional parameters

Logging:

The server logs important events and errors. Check the console output for debugging information.

Available Tools

2 tools
natural_queryA

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.

Inputs: query (required), response_format.

set_auth_tokenA

Set the authentication token for API requests. This must be called before using other tools to authenticate with the Ambivo API.

Inputs: token (required).

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A3.6/5.0

    Scored across 2 tools

    Disambiguation5/5

    The two tools have completely distinct purposes: one handles authentication setup, the other executes queries. No overlap or confusion possible.

    Naming Consistency5/5

    Both tools use consistent snake_case naming, and each name clearly indicates its function ('set_auth_token' for authentication, 'natural_query' for querying).

    Tool Count2/5

    Only 2 tools for a domain that involves multiple entities (leads, contacts, opportunities). This is insufficient to cover typical operations, though the natural_query tool may encapsulate many actions.

    Completeness1/5

    The server claims to handle leads, contacts, and opportunities, but provides no CRUD tools or entity-specific operations. A single query tool is severely incomplete for data management tasks.

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