SleekFlow MCP Server for Pydantic AI 7 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect SleekFlow 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 SleekFlow "
"(7 tools)."
),
)
result = await agent.run(
"What tools are available in SleekFlow?"
)
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 SleekFlow MCP Server
Connect your SleekFlow platform to any AI agent to power up your conversational support, sales, and marketing. Read real-time chat threads spanning across multiple digital channels and dispatch replies without leaving your chat interface.
Pydantic AI validates every SleekFlow 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
- Unified Conversations — Track and retrieve ongoing chat histories across WhatsApp, Instagram, Telegram, and WeChat
- Direct Messaging — Compose and send outbound responses or proactive messages back to customers seamlessly
- Contact Management — List all synced contacts and get their deep profile metadata including CRM ties
- Chat Segmentation — View categorization labels to segment hot leads or identify VIP support customers
- Automation Overviews — Retrieve a list of your configured automation workflows and active chatbot trees
The SleekFlow 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 SleekFlow to Pydantic AI via MCP
Follow these steps to integrate the SleekFlow 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 SleekFlow with type-safe schemas
Why Use Pydantic AI with the SleekFlow MCP Server
Pydantic AI provides unique advantages when paired with SleekFlow 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 SleekFlow integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your SleekFlow connection logic from agent behavior for testable, maintainable code
SleekFlow + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the SleekFlow MCP Server delivers measurable value.
Type-safe data pipelines: query SleekFlow with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple SleekFlow tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query SleekFlow and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock SleekFlow responses and write comprehensive agent tests
SleekFlow MCP Tools for Pydantic AI (7)
These 7 tools become available when you connect SleekFlow to Pydantic AI via MCP:
get_contact_details
Retrieves details for a specific contact
list_automation_flows
Lists available automation flows
list_channels
Lists all connected communication channels
list_contact_labels
Lists all labels used for contact categorization
list_contacts
Lists all contacts in SleekFlow
list_conversations
Lists all conversations across channels
send_message
Sends a message in a conversation
Example Prompts for SleekFlow in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with SleekFlow immediately.
"Show me all unread conversations from this weekend."
"Send a reply to conversation conv-xxxx saying 'Your refund has been processed. It will appear in 3-5 business days.'"
Troubleshooting SleekFlow MCP Server with Pydantic AI
Common issues when connecting SleekFlow to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiSleekFlow + Pydantic AI FAQ
Common questions about integrating SleekFlow 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 SleekFlow 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 SleekFlow to Pydantic AI
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.