How do I find my Collection ID?

Use the `list_collections` tool to see all available data sets (e.g., People, Company) in your workspace along with their unique IDs.

Can I filter records by specific field values?

Yes, the `list_collection_records` tool accepts an optional `filter_json` parameter where you can specify your search criteria.

Is it possible to track my wallet balance?

Absolutely. Use the `list_wallet_transactions` tool to retrieve a history of all balance changes and transactions in your Zixflow account.

Zixflow MCP Server for Pydantic AI 7 tools — connect in under 2 minutes

Name: Zixflow
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 7 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Zixflow 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 Zixflow "
            "(7 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Zixflow?"
    )
    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 Zixflow MCP Server

Connect your Zixflow workspace to any AI agent to automate your sales and CRM operations. This MCP server enables your agent to interact with collections (People, Company, etc.), manage individual records, and track wallet transactions directly from natural language.

Pydantic AI validates every Zixflow tool response against typed schemas, catching data inconsistencies at build time. Connect 7 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

Collection Oversight — List all data collections configured in your workspace to understand your CRM structure
Contact Management — List, retrieve, create, and update records within any collection using detailed field mappings
Precision Filtering — Search for specific records using JSON-based filtering and sorting criteria
Cleanup Automation — Delete unnecessary records and maintain your database directly via natural language commands
Wallet Tracking — Access a history of transactions and balance changes within your Zixflow wallet

The Zixflow MCP Server exposes 7 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 Zixflow to Pydantic AI via MCP

Follow these steps to integrate the Zixflow 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 7 tools from Zixflow with type-safe schemas

Why Use Pydantic AI with the Zixflow MCP Server

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

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

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

Zixflow + Pydantic AI Use Cases

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

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

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

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

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

Zixflow MCP Tools for Pydantic AI (7)

These 7 tools become available when you connect Zixflow to Pydantic AI via MCP:

create_collection_record

g., a person or company) to a specific Zixflow collection. Create a new record in a collection

delete_collection_record

Delete a record from a collection

get_record_details

Get details for a specific record

list_collection_records

Requires a JSON body for filtering/sorting. List records within a specific collection

list_collections

List all collections (People, Company, etc.)

list_wallet_transactions

List Zixflow wallet transactions

update_collection_record

Update an existing record

Example Prompts for Zixflow in Pydantic AI

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

"List all data collections in my Zixflow workspace."

"Show details for record with ID '98765'."

"List my recent wallet transactions."

Troubleshooting Zixflow MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Zixflow + Pydantic AI FAQ

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