How do I apply a tag to a contact using the agent?

Use the `apply_tag_to_contact` tool with the specific `tag_id` and `contact_id`. This is great for manual segmentation during a conversation.

Can I see all my automation campaigns?

Yes, the `list_campaigns` tool retrieves all campaigns configured in your Keap account, allowing you to monitor active sequences.

Is it possible to query sales opportunities?

Absolutely. Use the `list_opportunities` tool to see your current sales pipeline and track potential deals.

Keap MCP Server for Pydantic AI 11 tools — connect in under 2 minutes

Name: Keap
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 11 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Keap through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Keap "
            "(11 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Keap?"
    )
    print(result.data)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Keap MCP Server

Connect your Keap (formerly Infusionsoft) account to any AI agent to optimize your CRM and sales workflows. This MCP server enables your agent to interact with contacts, tags, and automation campaigns directly from natural language interfaces.

Pydantic AI validates every Keap tool response against typed schemas, catching data inconsistencies at build time. Connect 11 tools through the Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code — full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Contact Management — List, retrieve, and create contact profiles to maintain your lead database
Marketing Automation — List and monitor active campaigns and automation sequences
Segmentation — Manage tags and apply them to contacts to trigger specific workflows
Sales Pipeline — Query opportunities and deals to track your revenue growth
Billing Visibility — Access invoices and orders to stay on top of customer transactions

The Keap MCP Server exposes 11 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Keap to Pydantic AI via MCP

Follow these steps to integrate the Keap MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 11 tools from Keap with type-safe schemas

Why Use Pydantic AI with the Keap MCP Server

Pydantic AI provides unique advantages when paired with Keap through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your Keap integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Keap connection logic from agent behavior for testable, maintainable code

Keap + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Keap MCP Server delivers measurable value.

Type-safe data pipelines: query Keap with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Keap tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Keap and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Keap responses and write comprehensive agent tests

Keap MCP Tools for Pydantic AI (11)

These 11 tools become available when you connect Keap to Pydantic AI via MCP:

apply_tag_to_contact

Apply a tag to a specific contact

create_contact

Requires at least a first name or email. Create a new contact in Keap

get_business_profile

Get Keap business profile information

get_contact

Get details for a specific contact

list_campaigns

List all marketing campaigns

list_contacts

Use this to search for leads or customers. List all contacts in Keap

list_invoices

List all invoices

list_opportunities

List sales opportunities

list_orders

List ecommerce orders

list_tags

List all available tags

list_users

List all application users

Example Prompts for Keap in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Keap immediately.

"Find a contact with email 'john@example.com' in Keap."

"Show me all my available tags in Keap."

"List my recent ecommerce orders."

Troubleshooting Keap MCP Server with Pydantic AI

Common issues when connecting Keap to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Keap + Pydantic AI FAQ

Common questions about integrating Keap MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer — your Keap MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.