AgentFire MCP Server for Pydantic AIGive Pydantic AI instant access to 10 tools to Check Agentfire Status, Create Lead, Get Lead, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect AgentFire 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 AgentFire app connector for Pydantic AI is a standout in the Real Estate category — giving your AI agent 10 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 AgentFire "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in AgentFire?"
)
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 AgentFire MCP Server
Connect your AgentFire account to any AI agent and take full control of your real estate website and automated lead capture workflows through natural conversation.
Pydantic AI validates every AgentFire 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
- Lead Portfolio Orchestration — List and manage all captured property inquiries programmatically, retrieving detailed lead profile metadata and contact tags
- Web Engagement Intelligence — Programmatically monitor property clicks and access engagement metadata to coordinate your sales follow-up strategy
- Property Graph Monitoring — Access real-time updates for active listings and track user interaction duration directly through your agent for instant reporting
- Metadata Management — Programmatically retrieve interest signals and search history to maintain a perfectly coordinated CRM record
- Operational Monitoring — Verify account-level API connectivity and monitor lead capture volume directly through your agent for perfectly coordinated service scaling
The AgentFire 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.
All 10 AgentFire tools available for Pydantic AI
When Pydantic AI connects to AgentFire through Vinkius, your AI agent gets direct access to every tool listed below — spanning property-listings, real-estate-marketing, lead-capture, 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.
Verify AgentFire API connectivity
Email is required. Create a new lead
Get lead details
Get listing details
Get your AgentFire profile
List all contacts
List all leads
List all property listings
Search property listings
Only provided fields are changed. Update a lead
Connect AgentFire to Pydantic AI via MCP
Follow these steps to wire AgentFire 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 AgentFire MCP Server
Pydantic AI provides unique advantages when paired with AgentFire 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 AgentFire integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your AgentFire connection logic from agent behavior for testable, maintainable code
AgentFire + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the AgentFire MCP Server delivers measurable value.
Type-safe data pipelines: query AgentFire with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple AgentFire tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query AgentFire and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock AgentFire responses and write comprehensive agent tests
Example Prompts for AgentFire in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with AgentFire immediately.
"List all new leads captured in AgentFire this week."
"Show the property interest for lead ID 'lead_123'."
"Check for any active listings with zero engagement this month."
Troubleshooting AgentFire MCP Server with Pydantic AI
Common issues when connecting AgentFire to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiAgentFire + Pydantic AI FAQ
Common questions about integrating AgentFire 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.