Daftra MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Daftra through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 Daftra "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Daftra?"
)
print(result.data)
asyncio.run(main())
* 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 Daftra MCP Server
Integrate Daftra, the comprehensive cloud-based ERP and accounting software, directly into your AI workflow. Manage your clients, monitor invoices and estimates, and track business expenses using natural language.
Pydantic AI validates every Daftra tool response against typed schemas, catching data inconsistencies at build time. Connect 10 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
- Client Management — List, search, and retrieve full profiles and interaction history for your clients.
- Billing Oversight — Monitor sales invoices and price estimates to stay on top of your revenue.
- Expense Tracking — Track and retrieve recorded business expenses across your organization.
- Inventory & Services — List products and services in your inventory directly via chat.
The Daftra MCP Server exposes 10 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 Daftra to Pydantic AI via MCP
Follow these steps to integrate the Daftra 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 10 tools from Daftra with type-safe schemas
Why Use Pydantic AI with the Daftra MCP Server
Pydantic AI provides unique advantages when paired with Daftra 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 Daftra integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Daftra connection logic from agent behavior for testable, maintainable code
Daftra + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Daftra MCP Server delivers measurable value.
Type-safe data pipelines: query Daftra with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Daftra tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Daftra and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Daftra responses and write comprehensive agent tests
Daftra MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Daftra to Pydantic AI via MCP:
create_client
Resolves the newly generated client ID. Mutates the client and contact database state. Add a new client to the ERP database
get_client_details
Resolves detailed contact info and outstanding balances. Touches the granular CRM boundary. Get full profile and history for a specific client
get_invoice_details
Resolves line items, tax details, and payment history. Interacts with the detailed billing boundary. Get full details for a specific sales invoice
get_site_metadata
Resolves site identifiers and organizational settings. Interacts with the system configuration boundary. Retrieve general settings and metadata for your Daftra site
list_clients
Resolves client IDs, business names, and contact emails. Interacts with the client management boundary. List all clients in your Daftra account
list_estimates
Resolves estimate IDs, dates, and amounts. Interacts with the sales pipeline and quoting boundary. List all price estimates and quotes
list_expenses
Resolves expense IDs, categories, and amounts. Touches the accounting and expense tracking boundary. List all recorded business expenses
list_inventory_products
Resolves product IDs, names, and pricing. Interacts with the inventory management boundary. List all products and services in the inventory
list_invoices
Resolves invoice IDs, numbers, totals, and payment statuses. Touches the financial and sales boundary. List all sales invoices
search_clients_by_name
Resolves matching client profiles. Touches the search and discovery boundary. Search for a client by name keyword
Example Prompts for Daftra in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Daftra immediately.
"List all unpaid invoices from this month."
"Search for client 'John Smith' and show his contact details."
"List all business expenses recorded in the last 7 days."
Troubleshooting Daftra MCP Server with Pydantic AI
Common issues when connecting Daftra to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiDaftra + Pydantic AI FAQ
Common questions about integrating Daftra MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
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?
Can I switch LLM providers without changing MCP code?
Connect Daftra with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Daftra to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.