Can the AI alter invoices or update CRM statuses remotely?

No, it cannot. The agent is explicitly configured to possess pure Read-Only access capability via API V2 GET methodology endpoints (Such as `list_companies` and `get_invoices`). Your operational data remains completely immutable regardless of what you prompt.

Can I query a specific estimate document generated for a client?

Yes. While the integration allows sweeping over lists using `list_estimates`, the LLM can interpret the raw data to give you the summary of any pending quotes directly tied to associated internal pipelines effortlessly.

Does it track sales activities like recent calls?

Yes—by prompting your LLM with the underlying `list_activities` directive, you immediately gain access to the chronological logs outlining calls, meetings, generic events, and tasks created by your native Sales Development Representatives (SDRs).

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

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

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

asyncio.run(main())

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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 Sellsy MCP Server

Connect the Sellsy CRM API to your AI workflow to unlock conversational oversight over your entire French-designed commercial hub. By providing exactly Read-Only access, your agent can securely map ongoing deals, review invoice payment statuses, and fetch complete dossiers on existing catalog items and contacts.

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

Client & Prospecting Analysis — Use natural language to search companies, retrieve full metadata via company_id, and pull associated granular contacts directly into the conversational context
Sales Pipeline Auditing — Ask the agent to list all active 'opportunities' and drill down into a specific Deal ID to review its exact stage and monetary potential
Billing Integrity — Prompt your LLM to sweep your current draft, sent, and overdue invoices, including exact estimates given out recently to big leads
CRM Activity Surveillance — Seamlessly extract chronological activity feeds (meetings, calls, tasks) to compile end-of-week reporting automatically

The Sellsy 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 Sellsy to Pydantic AI via MCP

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

Why Use Pydantic AI with the Sellsy MCP Server

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

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

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

Sellsy + Pydantic AI Use Cases

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

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

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

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

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

Sellsy MCP Tools for Pydantic AI (12)

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

get_company

Get detailed information about a specific company

get_contact

Get detailed information about a specific contact

get_deal

Get full details of a specific deal (amount, status, pipeline step, company)

get_invoice

Get full details of a specific invoice (amount, status, due date)

list_activities

List recent CRM activities (calls, emails, meetings, tasks)

list_companies

List all companies (clients, prospects) in the CRM

list_contacts

List all contacts in the CRM

list_deals

List all deals (opportunities) in the sales pipeline

list_estimates

List all estimates (quotes) sent to prospects

list_invoices

List all invoices (draft, sent, paid, overdue)

list_items

List all products and services in the catalog

search_companies

Search companies by name or keyword

Example Prompts for Sellsy in Pydantic AI

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

"Identify pending Deals on Sellsy CRM and extract their projected monetary values."

"Pull the contact information and status for the primary user of 'Company XYZ'."

"Summarize the overarching status of my Sellsy invoices list."

Troubleshooting Sellsy MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Sellsy + Pydantic AI FAQ

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