Can I see all expense reports waiting for approval?

Yes! Use the `list_expense_reports` tool. The agent will return a list of reports along with their current status, allowing you to identify those pending action.

How do I check the receipt for a specific expense?

Use the `list_certify_receipts` tool. Your agent will fetch the available receipt data and images associated with your account's expenses.

Where do I find my x-api-key and x-api-secret?

These credentials must be generated by a Company-Level Administrator within the Certify application settings. Contact your finance or IT lead if you don't have access.

Certify (Emburse) MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: Certify (Emburse)
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 8 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Certify (Emburse) through the 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 Certify (Emburse) "
            "(8 tools)."
        ),
    )

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

asyncio.run(main())

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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 Certify (Emburse) MCP Server

Connect your Certify (Emburse Professional) account to any AI agent and orchestrate your travel and expense management through natural conversation. Streamline spend controls and financial auditing.

Pydantic AI validates every Certify (Emburse) tool response against typed schemas, catching data inconsistencies at build time. Connect 8 tools through the 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

Expense Oversight — List and retrieve individual expense lines and reports natively
Invoice Management — Monitor accounts payable invoices and invoice reports flawlessly
Receipt Auditing — Retrieve and review receipts stored in the system securely
User Administration — List employee records and organizational departments in real-time
General Ledger Sync — Access GL dimensions and dimensions for accounting synchronization flawlessly
Financial Reporting — Get a comprehensive view of employee spend and report statuses directly within your workspace

The Certify (Emburse) MCP Server exposes 8 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 Certify (Emburse) to Pydantic AI via MCP

Follow these steps to integrate the Certify (Emburse) 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 8 tools from Certify (Emburse) with type-safe schemas

Why Use Pydantic AI with the Certify (Emburse) MCP Server

Pydantic AI provides unique advantages when paired with Certify (Emburse) 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 Certify (Emburse) integration code

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

Dependency injection system cleanly separates your Certify (Emburse) connection logic from agent behavior for testable, maintainable code

Certify (Emburse) + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Certify (Emburse) MCP Server delivers measurable value.

Type-safe data pipelines: query Certify (Emburse) with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Certify (Emburse) tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Certify (Emburse) and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Certify (Emburse) responses and write comprehensive agent tests

Certify (Emburse) MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect Certify (Emburse) to Pydantic AI via MCP:

get_gl_dimensions

Retrieve General Ledger dimensions and lists

list_certify_departments

List company departments

list_certify_expenses

List individual expense lines

list_certify_invoices

List accounts payable invoices

list_certify_receipts

Retrieve receipts stored in the system

list_certify_users

List employee users in the system

list_expense_reports

List expense reports

list_invoice_reports

List reports containing multiple invoices

Example Prompts for Certify (Emburse) in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Certify (Emburse) immediately.

"Show me my recent expense reports in Certify."

"List all employees in the 'Marketing' department."

"What are the latest invoices waiting to be paid?"

Troubleshooting Certify (Emburse) MCP Server with Pydantic AI

Common issues when connecting Certify (Emburse) to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Certify (Emburse) + Pydantic AI FAQ

Common questions about integrating Certify (Emburse) 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 Certify (Emburse) MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.