Hiver MCP Server for Pydantic AIGive Pydantic AI instant access to 12 tools to Create Shared Draft, Get Api Status, Get Conversation Details, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Hiver through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
Ask AI about this App Connector for Pydantic AI
The Hiver app connector for Pydantic AI is a standout in the Communication Messaging category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Hiver "
"(12 tools)."
),
)
result = await agent.run(
"What tools are available in Hiver?"
)
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 Hiver MCP Server
Connect your Hiver account to any AI agent and transform your Gmail-based customer support into an intelligent, automated operation through natural conversation.
Pydantic AI validates every Hiver 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
- Shared Inbox Management — List all shared mailboxes and retrieve detailed metadata for active email conversations
- Workflow Automation — Programmatically update conversation statuses (open, pending, closed) and manage assignments across your team
- Collaborative Drafting — Create shared drafts within Gmail threads directly through your agent to orchestrate perfect replies
- Tagging & Organization — Search and apply tags to categorize threads and maintain a high-fidelity collaboration ecosystem
- Team Visibility — List and search for inbox members to understand who is available and manage workload distribution
The Hiver 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.
All 12 Hiver tools available for Pydantic AI
When Pydantic AI connects to Hiver through Vinkius, your AI agent gets direct access to every tool listed below — spanning shared-inbox, gmail-integration, email-management, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Draft team reply
Check connection
Read email thread
Get mailbox info
List shared threads
List team members
Get mailbox tags
List Hiver inboxes
Find tags
Find members
Verify credentials
Modify conversation
Connect Hiver to Pydantic AI via MCP
Follow these steps to wire Hiver into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install Pydantic AI
pip install pydantic-aiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use Pydantic AI with the Hiver MCP Server
Pydantic AI provides unique advantages when paired with Hiver 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 Hiver integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Hiver connection logic from agent behavior for testable, maintainable code
Hiver + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Hiver MCP Server delivers measurable value.
Type-safe data pipelines: query Hiver with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Hiver tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Hiver and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Hiver responses and write comprehensive agent tests
Example Prompts for Hiver in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Hiver immediately.
"List all shared inboxes in my Hiver account."
"Show me the last 5 open conversations in the 'Support' inbox."
"Assign conversation 'thread-123' to user 'user-456' and add the tag 'priority'."
Troubleshooting Hiver MCP Server with Pydantic AI
Common issues when connecting Hiver to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiHiver + Pydantic AI FAQ
Common questions about integrating Hiver 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.