Can I see all open job positions in my company?

Yes! Use the `list_organization_jobs` tool. The agent will return all roles, and you can filter or identify those that are currently marked as open or unfilled.

How do I check the reporting line for a specific person?

Use the `get_person_details` tool with the person's unique ID. Your agent will fetch the full profile, which includes their manager and organizational placement data.

Where do I find my ChartHop Org ID and API Token?

You can find your Org ID in the URL when logged into ChartHop. To get an API Token, you typically need to create a 'ChartHop App' or request one from your administrator.

ChartHop MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: ChartHop
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 8 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect ChartHop 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 ChartHop "
            "(8 tools)."
        ),
    )

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

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

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Ed25519Audit chain

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 ChartHop MCP Server

Connect your ChartHop account to any AI agent and take full control of your organizational data and workforce planning through natural conversation. Streamline how you manage your roster and headcount.

Pydantic AI validates every ChartHop tool response against typed schemas, catching data inconsistencies at build time. Connect 8 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

Roster Oversight — List and retrieve details for all people and filled roles in your organization natively
Headcount Planning — Access and monitor open job positions and headcount scenarios flawlessly
Organizational Mapping — List departments, teams, and their hierarchical structures securely
Deep-Dive Profiles — Retrieve complete person information, including job history and compensation metadata flawlessly
Scenario Visibility — Access and review headcount and compensation planning scenarios in real-time
System Intelligence — Retrieve core organization information and account settings directly within your workspace

The ChartHop MCP Server exposes 8 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 ChartHop to Pydantic AI via MCP

Follow these steps to integrate the ChartHop 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 8 tools from ChartHop with type-safe schemas

Why Use Pydantic AI with the ChartHop MCP Server

Pydantic AI provides unique advantages when paired with ChartHop 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 ChartHop integration code

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

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

ChartHop + Pydantic AI Use Cases

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

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

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

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

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

ChartHop MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect ChartHop to Pydantic AI via MCP:

get_job_details

Get detailed information for a specific job

get_organization_summary

Retrieve core organization information and settings

get_person_details

Get detailed profile information for a specific person

list_organization_departments

List all departments in the organization

list_organization_jobs

List all jobs (roles) in the organization

list_organization_people

List all people (employees) in the organization

list_organization_teams

List all teams in the organization

list_planning_scenarios

List headcount and compensation planning scenarios

Example Prompts for ChartHop in Pydantic AI

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

"Show me the headcount summary for my organization."

"List all departments and their leaders."

"Show me details for 'John Smith' in ChartHop."

Troubleshooting ChartHop MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

ChartHop + Pydantic AI FAQ

Common questions about integrating ChartHop 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 ChartHop MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.