Drip MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Drip through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 Drip "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Drip?"
)
print(result.data)
asyncio.run(main())
* 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 Drip MCP Server
Connect your Drip account to any AI agent and take full control of your e-commerce CRM and marketing automation through natural conversation.
Pydantic AI validates every Drip tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through 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
- Subscriber Management — List and search for subscribers to retrieve emails, tags, custom fields, lead scores, and lifecycle stages natively
- Provisioning & Tagging — Create or update subscriber profiles and apply or remove tags strictly to drive your automation and segmentation logic
- Workflow Orchestration — List all automation workflows and trigger absolute response routing to start subscribers onto an executing node loop
- Campaign Auditing — Retrieve explicit arrays detailing specific email series campaigns, including statuses and subscriber counts
- Event Tracking — Inject raw telemetry logs to record custom events (like 'Purchased' or 'Visited') generating hard tracking bindings for your automation
- Categorical Tagging — Identify precise active tag arrays spanning your account to manage your organizational segmentation boundaries
- Activity Monitoring — Analyze specific localized profiles decoding activity history to understand customer behavior limitlessly
The Drip MCP Server exposes 10 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 Drip to Pydantic AI via MCP
Follow these steps to integrate the Drip 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 10 tools from Drip with type-safe schemas
Why Use Pydantic AI with the Drip MCP Server
Pydantic AI provides unique advantages when paired with Drip 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 Drip integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Drip connection logic from agent behavior for testable, maintainable code
Drip + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Drip MCP Server delivers measurable value.
Type-safe data pipelines: query Drip with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Drip tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Drip and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Drip responses and write comprehensive agent tests
Drip MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Drip to Pydantic AI via MCP:
create_subscriber
Modifies `/v2/{account_id}/subscribers` resolving exact tags mapping. Create or update a Drip subscriber
get_subscriber
Returns full profile, tags, custom fields, lead score, and activity history. Get a Drip subscriber by email or ID
list_campaigns
Returns campaign IDs, names, statuses, and subscriber counts. List Drip email series campaigns
list_subscribers
Returns emails, tags, custom fields, and lifecycle stage. List Drip subscribers. Drip is an e-commerce CRM/email platform
list_tags
List all tags in your Drip account
list_workflows
Returns workflow IDs, names, and statuses (active/paused/draft). List Drip automation workflows
record_event
Events trigger automations. Record a custom event for a Drip subscriber
remove_tag
Drops the raw data tag relationship bypassing the standard UI triggers. Remove a tag from a Drip subscriber
start_workflow
Starts a subscriber onto an executing node loop. Start a subscriber on a Drip automation workflow
tag_subscriber
Tags drive automation and segmentation. Apply a tag to a Drip subscriber
Example Prompts for Drip in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Drip immediately.
"Search for subscriber info for: hello@example.com"
"Add tag 'Vip-Customer' to user: user@drip.com"
"List all active automation workflows"
Troubleshooting Drip MCP Server with Pydantic AI
Common issues when connecting Drip to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiDrip + Pydantic AI FAQ
Common questions about integrating Drip MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
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?
Can I switch LLM providers without changing MCP code?
Connect Drip with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Drip to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.