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Bleez MCP Server for Pydantic AIGive Pydantic AI instant access to 8 tools to Create Accounting Entry, Create Invoice, Get Account Info, and more

Built by Vinkius GDPR 8 Tools SDK

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

Ask AI about this App Connector for Pydantic AI

The Bleez app connector for Pydantic AI is a standout in the Document Management category — giving your AI agent 8 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

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 Bleez "
            "(8 tools)."
        ),
    )

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

asyncio.run(main())
Bleez
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* 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 Bleez MCP Server

Connect your Bleez account to any AI agent and take full control of your French accounting workflows and digital document management through natural conversation.

Pydantic AI validates every Bleez tool response against typed schemas, catching data inconsistencies at build time. Connect 8 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

  • Ledger Orchestration — List and manage accounting journal entries programmatically, retrieving detailed historical ledger data in real-time
  • Invoice Lifecycle Management — Create and track sales and purchase invoices programmatically to maintain a perfectly coordinated billing pipeline
  • Document Ingestion — Programmatically upload digital documents (PDF/Images) to the 'Factures à traiter' module for high-fidelity automated processing
  • Contact Discovery — Access complete directories of customer and supplier profiles to coordinate your organizational relationship ecosystem
  • Folder Visibility — Retrieve organization-level metadata and folder settings directly through your agent for instant financial reporting

The Bleez 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.

All 8 Bleez tools available for Pydantic AI

When Pydantic AI connects to Bleez through Vinkius, your AI agent gets direct access to every tool listed below — spanning ledger-management, invoicing, accounting-automation, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

create_accounting_entry

Provide date, label, and account lines. Create a new accounting entry

create_invoice

Provide contact ID and amount. Create a new invoice

get_account_info

Get current account settings

list_accounting_entries

List all accounting journal entries

list_customers

List all customers

list_invoices

List all invoices

list_suppliers

List all suppliers

upload_document

Upload a digital document for processing

Connect Bleez to Pydantic AI via MCP

Follow these steps to wire Bleez into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

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 8 tools from Bleez with type-safe schemas

Why Use Pydantic AI with the Bleez MCP Server

Pydantic AI provides unique advantages when paired with Bleez 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 Bleez 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 Bleez connection logic from agent behavior for testable, maintainable code

Bleez + Pydantic AI Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for Bleez in Pydantic AI

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

01

"List all active customers in my Bleez folder."

02

"Upload the file 'invoice_123.pdf' to Bleez for processing."

03

"Show the last 5 accounting entries recorded this month."

Troubleshooting Bleez MCP Server with Pydantic AI

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

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Bleez + Pydantic AI FAQ

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