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Assembled MCP Server for Pydantic AI 7 tools — connect in under 2 minutes

Built by Vinkius GDPR 7 Tools SDK

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

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 Assembled "
            "(7 tools)."
        ),
    )

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

asyncio.run(main())
Assembled
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
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 Assembled MCP Server

The Assembled MCP Server provides your AI agent with direct access to your workforce management (WFM) data. Optimize your support operations by monitoring agent availability, auditing schedules, and analyzing contact volume forecasts using natural language.

Pydantic AI validates every Assembled tool response against typed schemas, catching data inconsistencies at build time. Connect 7 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.

Key Capabilities

  • Agent & State Tracking — List all users and monitor real-time agent states to see who is online, on break, or in a meeting.
  • Team & Queue Management — Audit your support organization structure by listing teams and individual support queues.
  • Schedule Oversight — Retrieve detailed agent schedules for any time range to ensure proper coverage.
  • Forecasting Insights — Access contact volume forecasts to prepare for upcoming support demand.
  • Operational Auditing — Quickly verify account connections and organizational metadata without manual reports.
  • Secure API Access — Uses your Assembled API Key for safe and authenticated communication with your WFM data.

The Assembled MCP Server exposes 7 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 Assembled to Pydantic AI via MCP

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

01

Install Pydantic AI

Run pip install pydantic-ai

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the agent

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

04

Explore tools

The agent discovers 7 tools from Assembled with type-safe schemas

Why Use Pydantic AI with the Assembled MCP Server

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

01

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

02

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

03

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

04

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

Assembled + Pydantic AI Use Cases

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

01

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

02

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

03

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

04

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

Assembled MCP Tools for Pydantic AI (7)

These 7 tools become available when you connect Assembled to Pydantic AI via MCP:

01

get_account_check

Verify Assembled account connection

02

list_agent_states

List real-time agent states

03

list_forecasts

List contact volume forecasts

04

list_queues

List all support queues

05

list_schedules

List agent schedules for a time range

06

list_teams

List all teams

07

list_users

List all users in Assembled

Example Prompts for Assembled in Pydantic AI

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

01

"List all agents currently online in Assembled."

02

"Show me the schedule for 'Support Team Alpha' for today."

03

"What is the contact volume forecast for next Monday?"

Troubleshooting Assembled MCP Server with Pydantic AI

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

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Assembled + Pydantic AI FAQ

Common questions about integrating Assembled MCP Server with Pydantic AI.

01

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.
02

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.
03

Can I switch LLM providers without changing MCP code?

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

Connect Assembled to Pydantic AI

Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.