How to Use the Merge (Unified Integration API) MCP in Pydantic AI

Validate HRIS, ATS, and CRM payloads at runtime using Pydantic AI and our hosted MCP Server.

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Connect Merge (Unified Integration API) MCP to Pydantic AI

Create your Vinkius account to connect Merge (Unified Integration API) to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Merge (Unified Integration API) with Pydantic AI

Ask AI about this MCP

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Perplexity

Enforce strict schemas on employee and applicant data.

The `list_employees` tool returns structured personnel data that your agent validates against Pydantic models. This MCP Server ensures you never parse malformed salary, role, or department fields. Similarly, `list_candidates` guarantees that applicant tracking data matches your internal Python classes. If an ATS platform returns unexpected null values, the framework catches the error immediately before it corrupts your database.

Validate CRM Accounts and Contacts

The `list_accounts` tool retrieves CRM integration profiles and maps them to strict Python types. This prevents your agent from executing workflows based on partial or corrupted customer records. Your agent uses `list_contacts` to safely extract external email addresses and phone numbers. The runtime validation guarantees that every contact field complies with your application's data integrity rules.

Track help desk issues and connection states securely.

The `list_tickets` tool fetches active customer support cases across all your integrated help desks. Your agent can group these tickets by priority, status, or assignee with absolute type safety. To keep an eye on connection health, `get_account_details` exposes active integration limits. This lets your system verify that downstream credentials are valid before initiating heavy data syncs.

Setup guide

Set up Merge (Unified Integration API) MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "merge-unified-integration-api-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Merge (Unified Integration API) tools.",
)

result = await agent.run("List recent Merge (Unified Integration API) transactions")
print(result.output)

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Common questions about Merge (Unified Integration API) MCP in Pydantic AI

The framework automatically generates Pydantic models from the server's OpenAPI-style schemas. This ensures that tools like `list_employees` and `list_tickets` return typed data that matches your expectations.

The agent raises a validation error immediately. This loud-failure model prevents your application from writing corrupted HRIS or CRM records to your production database.

Yes, the framework is model-agnostic. You can connect your local LLM to the MCPToolset and let it execute tools like `list_candidates` and `list_companies` without relying on cloud APIs.

It supports SSE and Streamable HTTP transports. You run the server externally, and the Python client establishes a persistent connection to stream tool calls.

All employee details, candidate lists, and support tickets route through an ephemeral V8 sandbox. Vinkius maintains a zero-trust architecture, meaning no data is cached or stored outside of active memory.

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