Custify 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 Custify 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 Custify "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Custify?"
)
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 Custify MCP Server
Integrate Custify, the comprehensive customer success platform, directly into your AI workflow. Monitor customer health, track churn risks, and manage your success tasks and notes using natural language.
Pydantic AI validates every Custify 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
- Customer Oversight — List and retrieve detailed profiles, health scores, and churn probabilities for all customers.
- Company Monitoring — Access company-level metrics and success data to manage B2B relationships effectively.
- Success Task Management — List and track open tasks and internal CRM notes for your accounts.
- KPI Discovery — Explore key performance indicators and metrics defined in your Custify account.
The Custify 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 Custify to Pydantic AI via MCP
Follow these steps to integrate the Custify 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 Custify with type-safe schemas
Why Use Pydantic AI with the Custify MCP Server
Pydantic AI provides unique advantages when paired with Custify 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 Custify integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Custify connection logic from agent behavior for testable, maintainable code
Custify + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Custify MCP Server delivers measurable value.
Type-safe data pipelines: query Custify with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Custify tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Custify and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Custify responses and write comprehensive agent tests
Custify MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Custify to Pydantic AI via MCP:
create_customer_profile
Resolves the newly generated customer ID and validation status. Mutates the customer database state. Create a new customer profile in Custify
get_company_details
Resolves organizational attributes and health metrics. Touches the core company repository. Get detailed settings and metrics for a specific company
get_customer_details
Resolves health scores, recent activity, and segment membership. Interacts with the behavioral analytics boundary. Get full profile and health metrics for a specific customer
list_companies
Resolves company IDs, domain information, and association metrics. Touches the account-level organization boundary. List all companies in Custify
list_customer_kpis
Resolves metric definitions and threshold values. Interacts with the performance monitoring boundary. List key performance indicators defined in the account
list_customer_notes
Resolves note content and authorship metadata. Touches the internal communications boundary. List internal CRM notes for a specific customer
list_customer_success_tasks
Resolves task priority, status, and assigned owners. Interacts with the workflow automation boundary. List open and completed customer success tasks
list_customers
Resolves properties such as customer ID, name, email, and lifecycle stage. Interacts with the customer success management boundary. List all customers in Custify
list_people
Resolves contact details and account associations. Touches the relationship management boundary. List all people associated with accounts
search_customers_by_keyword
Resolves matching customer profiles based on name or email. Touches the search and indexing boundary. Search for customers by name or email
Example Prompts for Custify in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Custify immediately.
"List all customers with a health score below 50."
"Show me the success tasks for company 'Alpha Corp'."
"Search for customer 'john.doe@example.com'."
Troubleshooting Custify MCP Server with Pydantic AI
Common issues when connecting Custify to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiCustify + Pydantic AI FAQ
Common questions about integrating Custify 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 Custify 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 Custify to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.