Can the agent calculate how many hours were logged on a specific project?

Yes. If you ask your agent 'How many hours were logged for project Alpha recently?', the agent will invoke `list_time_entries` and filter the returned data by that specific project, summing up the billable minutes natively.

Is it possible to track unpaid invoices directly from the chat?

Absolutely. Just prompt the AI: 'List my recent sales invoices and flag any that haven't been paid'. The agent will make an API call to `list_invoices` and analyze the 'payment status' attributes for you.

Can I retrieve contact information before a meeting?

Yes. You can use the agent to prepare yourself. Prompt: 'Search our contacts for Acme Corp and get me their full profile'. The agent relies on `list_contacts` and `get_contact` to pull in emails, phone numbers, and relational tags.

Scoro MCP Server for Pydantic AI 12 tools — connect in under 2 minutes

Name: Scoro
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 12 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Scoro through 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 Scoro "
            "(12 tools)."
        ),
    )

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

asyncio.run(main())

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 Scoro MCP Server

Connect your Scoro workspace to any AI agent to interact with your business operations securely. Avoid context-switching between your agency's CRM, PM software, and billing dashboards.

Pydantic AI validates every Scoro tool response against typed schemas, catching data inconsistencies at build time. Connect 12 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

Project & Task Tracking — Query your entire project portfolio, check on ongoing task statuses, and extract time entries logged by the team
CRM & Contacts — Retrieve details, metadata, and history for any client or vendor in your database
Financial Health — List sales invoices, pending quotes, and registered business expenses to track profitability without running manual reports
Team Management — Consult your user roster, pull recent activity audit logs, and browse team calendar events directly within your chat environment

The Scoro MCP Server exposes 12 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 Scoro to Pydantic AI via MCP

Follow these steps to integrate the Scoro 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 12 tools from Scoro with type-safe schemas

Why Use Pydantic AI with the Scoro MCP Server

Pydantic AI provides unique advantages when paired with Scoro 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 Scoro integration code

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

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

Scoro + Pydantic AI Use Cases

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

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

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

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

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

Scoro MCP Tools for Pydantic AI (12)

These 12 tools become available when you connect Scoro to Pydantic AI via MCP:

get_contact

Retrieves details for a specific contact

list_activities

Lists recent activities and audit logs

list_calendar_events

Lists all events on the Scoro calendar

list_contacts

Lists all contacts (companies and people) in Scoro

list_expenses

Lists all business expenses

list_invoices

Lists all sales invoices

list_products

Lists all products and services in the catalog

list_projects

Lists all projects in Scoro

list_quotes

Lists all sales quotes

list_tasks

Lists all tasks

list_time_entries

Lists time entries logged by the team

list_users

Lists all users in the Scoro organization

Example Prompts for Scoro in Pydantic AI

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

"What are the most recent activities logged in my Scoro workspace?"

"List all active marketing projects and their statuses."

"Show me our total revenue from the latest invoices."

Troubleshooting Scoro MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Scoro + Pydantic AI FAQ

Common questions about integrating Scoro 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 Scoro MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.