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Range MCP Server for Pydantic AIGive Pydantic AI instant access to 11 tools to Create Update, Get Objective, Get Snippet, and more

Built by Vinkius GDPR 11 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Range 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 Range app connector for Pydantic AI is a standout in the Industry Titans category — giving your AI agent 11 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

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 Range "
            "(11 tools)."
        ),
    )

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

asyncio.run(main())
Range
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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 Range MCP Server

Connect your Range.co account to any AI agent and take full control of your team communication and check-in orchestration through natural conversation. Range provides a premier platform for keeping remote and hybrid teams synchronized, and this integration allows you to retrieve team metadata, monitor check-in updates (snippets), and track organizational objectives directly from your chat interface.

Pydantic AI validates every Range tool response against typed schemas, catching data inconsistencies at build time. Connect 11 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-in & Update Orchestration — List all managed updates and retrieve detailed metadata including snippet content programmatically.
  • Team & User Lifecycle Management — Access and monitor your workspace teams and retrieve detailed user profile metadata directly from the AI interface.
  • Objective & Goal Intelligence — Access organizational objectives to maintain a clear overview of team alignment and progress via natural language.
  • Activity & Snippet Control — Retrieve specific snippets and check-in details to stay informed about daily team accomplishments.
  • Operational Monitoring — Track system activity and manage workspace metadata using simple AI commands to ensure your team remains high-performing.

The Range MCP Server exposes 11 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 11 Range tools available for Pydantic AI

When Pydantic AI connects to Range through Vinkius, your AI agent gets direct access to every tool listed below — spanning async-check-ins, team-sync, objective-tracking, 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.

create_update

Post a new standup update

get_objective

Get details for a specific objective

get_snippet

Get details of a specific check-in snippet

get_team

Get details for a specific team

get_update

Get details of a specific update (check-in)

get_user

Get details for a specific team member

list_goals

List all team goals

list_objectives

List team objectives

list_teams

List all teams

list_updates

Can be filtered by target_id or for_user_id. List team check-ins (updates)

list_users

List all users in the organization

Connect Range to Pydantic AI via MCP

Follow these steps to wire Range into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install Pydantic AI

Run pip install pydantic-ai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 11 tools from Range with type-safe schemas

Why Use Pydantic AI with the Range MCP Server

Pydantic AI provides unique advantages when paired with Range through the Model Context Protocol.

01

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

02

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Range integration code

03

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

04

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

Range + Pydantic AI Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for Range in Pydantic AI

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

01

"List all teams in my Range workspace."

02

"Show me all team standup updates from today with their mood indicators and blockers."

03

"Show me the progress on all team objectives for this quarter with completion percentages."

Troubleshooting Range MCP Server with Pydantic AI

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

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Range + Pydantic AI FAQ

Common questions about integrating Range MCP Server with Pydantic AI.

01

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.
02

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.
03

Can I switch LLM providers without changing MCP code?

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