How do I get an Access Token for FreshBooks?

You can find your Access Token in your FreshBooks application settings or by creating a Personal Access Token in the FreshBooks Developer Portal.

Where do I find my FreshBooks Account ID?

Your Account ID is the unique number visible in your browser's URL bar immediately after '/portal/' when you are logged into FreshBooks.

Can I see if a specific invoice has been paid?

Yes! Use the 'get_invoice_details' tool and provide the Invoice ID. The agent will return the current status, including whether it is 'Sent', 'Paid', or 'Overdue'.

Is time tracking data accessible via the agent?

Yes, the 'list_time_entries' tool allows you to retrieve all time tracking logs for your business, keeping your project productivity in view.

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

Name: FreshBooks
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 FreshBooks 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 FreshBooks "
            "(12 tools)."
        ),
    )

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

asyncio.run(main())

Fully ManagedVinkius Servers

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<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 FreshBooks MCP Server

Connect your FreshBooks account to any AI agent to automate your small business accounting, invoicing, and client management through the Model Context Protocol (MCP). FreshBooks is the leading cloud-based accounting software designed for small businesses and self-employed professionals. This MCP server enables you to manage your clients, track invoice statuses, and retrieve financial summaries directly through natural conversation.

Pydantic AI validates every FreshBooks 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.

Key Features

Client Management — List and search for clients, fetch detailed profiles, and maintain full context of your customer relationships.
Invoice Lifecycle — Track sales invoices across all states (Sent, Paid, Overdue) and retrieve detailed line-item metadata.
Expense Oversight — Monitor recorded business expenses and categorize them for better financial tracking.
Payment History — Retrieve a list of all payments received to ensure your cash flow is accurately monitored.
Project & Task Tracking — Access projects, tasks, and time entries to see how they impact your billing and productivity.
User Identity — Fetch global user profile and identity details to ensure you are working in the correct account context.
Financial Insights — Access high-level metadata for your specific FreshBooks business account instantly.

The FreshBooks 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 FreshBooks to Pydantic AI via MCP

Follow these steps to integrate the FreshBooks 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 FreshBooks with type-safe schemas

Why Use Pydantic AI with the FreshBooks MCP Server

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

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

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

FreshBooks + Pydantic AI Use Cases

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

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

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

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

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

FreshBooks MCP Tools for Pydantic AI (12)

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

get_account_info

Get business info

get_client_details

Get client metadata

get_invoice_details

Get invoice metadata

get_my_identity

Get user identity

list_active_projects

List projects

list_clients

List clients

list_expense_categories

List categories

list_expenses

List tracked expenses

list_invoices

List sales invoices

list_payments

List invoice payments

list_project_tasks

List tasks

list_time_entries

List time logs

Example Prompts for FreshBooks in Pydantic AI

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

"List my 5 most recent clients in FreshBooks."

"Show me the status of my last 3 invoices."

"Get my time tracking entries for this week."

Troubleshooting FreshBooks MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

FreshBooks + Pydantic AI FAQ

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