Column MCP Server for Pydantic AI 12 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Column 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 Column "
"(12 tools)."
),
)
result = await agent.run(
"What tools are available in Column?"
)
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 Column MCP Server
The Column MCP Server effectively bypasses standard FinTech wrappers and ties your artificial intelligence directly to one of the only nationally chartered US banks built originally around raw Developer APIs.
Pydantic AI validates every Column tool response against typed schemas, catching data inconsistencies at build time. Connect 12 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
- Automated Clearing — Use
column_create_ach_transferto reliably settle recurring vendor payouts directly out of your native balance without relying on external UI web panels. - Establish Corporate Entities — Hook your conversational bots to construct KYC/KYB verified operational clusters
column_create_entityready to map against newly minted bank account numbers (column_create_bank_account). - Physical Check Writing — Astonishing API feature: send literal paper checks natively out to US addresses. Formulate text like "Mail a $40 check to John's address in Texas for maintenance" and the
column_create_checkprints and bounds the ledger payload directly.
The Column 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 Column to Pydantic AI via MCP
Follow these steps to integrate the Column 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 Column with type-safe schemas
Why Use Pydantic AI with the Column MCP Server
Pydantic AI provides unique advantages when paired with Column 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 Column integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Column connection logic from agent behavior for testable, maintainable code
Column + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Column MCP Server delivers measurable value.
Type-safe data pipelines: query Column with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Column tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Column and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Column responses and write comprehensive agent tests
Column MCP Tools for Pydantic AI (12)
These 12 tools become available when you connect Column to Pydantic AI via MCP:
column_create_ach_transfer
Fire an ACH to an external routing/account number
column_create_bank_account
Establish a DDA (Demand Deposit Account)
column_create_check
Very useful for legacy vendor systems. Generate and mail a paper check
column_create_entity
In production, this goes through compliance screening. Register a business or person KYC target inside Column
column_create_wire_transfer
Fire an immediate Wire transfer
column_get_balance
Audit settled funds inside a Bank Account
column_get_bank_account
Fetch specific DDA details (Routing info)
column_get_statement
Retrieve the generated bank statement artifacts
column_list_entities
View all active KYC profiles under the charter
column_list_transfers
Sweep historical ACH payment operations
column_list_webhooks
View all registered listening streams
column_simulate_ach
Trigger Sandbox inbound money movement
Example Prompts for Column in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Column immediately.
"Scan our balance history within my Operational account ID. See exactly how much pure funds are settled and available for dispatch."
"Print out a $1,500 manual paper check paid out to 'Green Construction LLC'. Mail it to '55 Broad St, Chicago IL 60601'."
"Initialize a Same-Day direct ACH batch targeting our landlord accounting info. Execute a $5,000 push towards Counterparty Router 02844 under entity RentalCorp."
Troubleshooting Column MCP Server with Pydantic AI
Common issues when connecting Column to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiColumn + Pydantic AI FAQ
Common questions about integrating Column 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 Column 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 Column to Pydantic AI
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.