Collect 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 Collect 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 Collect "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Collect?"
)
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 Collect MCP Server
Connect your AI to Collect, the secure platform for gathering information and documents from clients.
Pydantic AI validates every Collect 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
- Campaign Management — List active data collection campaigns and check their completion status.
- Request Sending — Send new data requests to clients by email for KYC, onboarding, or compliance workflows.
- Status Tracking — Check the status of individual requests, view messages, and monitor completion.
The Collect 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 Collect to Pydantic AI via MCP
Follow these steps to integrate the Collect 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 Collect with type-safe schemas
Why Use Pydantic AI with the Collect MCP Server
Pydantic AI provides unique advantages when paired with Collect 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 Collect integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Collect connection logic from agent behavior for testable, maintainable code
Collect + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Collect MCP Server delivers measurable value.
Type-safe data pipelines: query Collect with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Collect tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Collect and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Collect responses and write comprehensive agent tests
Collect MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Collect to Pydantic AI via MCP:
create_request
Send a new data collection request to a recipient
get_campaign
Retrieve detailed information about a specific campaign
get_element_details
Retrieve details of a specific element (field/block) in a request
get_request
Retrieve details of a specific data request
get_team_info
Retrieve information about your team in Collect
get_user_info
Retrieve information about the currently authenticated user
list_campaigns
Retrieve a list of all data collection campaigns in Collect
list_messages
Retrieve a list of messages sent through Collect
list_requests
Retrieve all data requests for a specific campaign
send_message
Send a message to a recipient regarding a specific request
Example Prompts for Collect in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Collect immediately.
"Show me all active data collection campaigns."
"Send a data request to 'John Doe' (john@example.com) for the 'KYC Process' campaign."
"Send an automatic reminder to all clients with missing documents in the 'Tax 2025' campaign."
Troubleshooting Collect MCP Server with Pydantic AI
Common issues when connecting Collect to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiCollect + Pydantic AI FAQ
Common questions about integrating Collect 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 Collect 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 Collect to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.