How do I send a High Five through the agent?

Use the `send_high_five` tool and provide the recipient's email or ID and a recognition message. Your agent will process it immediately and notify the recipient.

Can I see team pulse scores with this integration?

Yes, you can use the `list_checkins` tool to retrieve check-in data which includes employee pulse scores and sentiment analysis.

Does the agent support managing OKRs?

The agent can list and track progress on objectives using the `list_objectives` tool, allowing you to monitor goal attainment across your team.

15Five MCP Server for Pydantic AI 6 tools — connect in under 2 minutes

Name: 15Five
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 6 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect 15Five through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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 15Five "
            "(6 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in 15Five?"
    )
    print(result.data)

asyncio.run(main())

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* 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 15Five MCP Server

Transform your team’s engagement and performance with 15Five, the holistic performance management platform now accessible through your AI agent. By bridging 15Five with the Model Context Protocol, you turn employee check-ins and objective tracking into a seamless conversation. Your agent can help you celebrate wins with High Fives, monitor team sentiment via Pulse scores, and audit OKRs without you ever leaving your primary workspace. It’s the ultimate tool for managers who want to stay connected to their team’s heartbeat while focusing on strategic growth.

Pydantic AI validates every 15Five tool response against typed schemas, catching data inconsistencies at build time. Connect 6 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

Check-ins & Feedback — Retrieve recent check-ins, view employee answers, and monitor pulse scores to gauge team sentiment.
High Fives & Recognition — List received high fives or send new ones to celebrate team wins and boost morale directly from chat.
Objectives (OKRs) — Track progress on company or individual objectives and key results without manual dashboard lookups.
User & Team Management — List employees, departments, and groups to maintain organizational clarity.
Engagement Insights — Quickly access historical performance data and feedback cycles to support meaningful 1-on-1 conversations.

The 15Five MCP Server exposes 6 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 15Five to Pydantic AI via MCP

Follow these steps to integrate the 15Five 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 6 tools from 15Five with type-safe schemas

Why Use Pydantic AI with the 15Five MCP Server

Pydantic AI provides unique advantages when paired with 15Five 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 15Five integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your 15Five connection logic from agent behavior for testable, maintainable code

15Five + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the 15Five MCP Server delivers measurable value.

Type-safe data pipelines: query 15Five with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple 15Five tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query 15Five and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock 15Five responses and write comprehensive agent tests

15Five MCP Tools for Pydantic AI (6)

These 6 tools become available when you connect 15Five to Pydantic AI via MCP:

list_checkins

Use this to monitor team sentiment or review previous employee submissions. You can filter by user ID. List recent employee check-ins and performance reports

list_departments

Useful for finding the department ID or identifying team structures. List all departments and their members

list_high_fives

List recent High Fives (public recognition) across the company

list_objectives

List company and individual objectives (OKRs)

list_users

Use this to find the identifier for a person. List all active employees and users in the 15Five organization

send_high_five

Requires the email address of the recipient and a personal message. Send a High Five to publicly recognize a colleague

Example Prompts for 15Five in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with 15Five immediately.

"Show me the last 5 check-ins for my team."

"Send a High Five to Sarah for her great work on the project."

"List all active company objectives."

Troubleshooting 15Five MCP Server with Pydantic AI

Common issues when connecting 15Five to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

15Five + Pydantic AI FAQ

Common questions about integrating 15Five MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an 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?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your 15Five MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.