How do I get a DeveloperHub API Key?

Log in to your DeveloperHub account, navigate to **Project Settings > API**, and you can generate or retrieve your unique API Key from that section.

Can the agent retrieve the Markdown content of a page?

Yes, you can use the get_documentation_page_content tool to retrieve the full technical structure and text content of any page in your project.

Does the integration support searching across portals?

You can search within a specific project using the search_documentation_portal tool. To search across multiple portals, simply perform separate queries for each project ID.

DeveloperHub MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: DeveloperHub
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

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

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

asyncio.run(main())

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About DeveloperHub MCP Server

Integrate DeveloperHub, the specialized platform for developer documentation, directly into your AI workflow. Manage your documentation portals, monitor page updates and versions, and track product changelogs using natural language.

Pydantic AI validates every DeveloperHub 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

Project Oversight — List and retrieve technical metadata for all your documentation projects and portals.
Page Management — Access the full page hierarchy, retrieve Markdown content, and track recent updates.
Version Control — Monitor available documentation versions and identify which one is currently active.
Changelog Tracking — List product release notes and updates associated with your documentation projects.

The DeveloperHub 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.

How to Connect DeveloperHub to Pydantic AI via MCP

Follow these steps to integrate the DeveloperHub 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 10 tools from DeveloperHub with type-safe schemas

Why Use Pydantic AI with the DeveloperHub MCP Server

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

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

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

DeveloperHub + Pydantic AI Use Cases

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

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

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

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

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

DeveloperHub MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect DeveloperHub to Pydantic AI via MCP:

get_account_metadata

Retrieve metadata and usage limits for your DeveloperHub account

get_documentation_page_content

Get the full content and metadata for a specific documentation page

get_documentation_project_details

Get detailed information for a specific documentation project

get_documentation_sitemap

Retrieve a structural map of all pages in a project

list_documentation_pages

List all pages and sub-pages within a specific project

list_documentation_projects

List all documentation projects in your DeveloperHub account

list_documentation_versions

List all versions (e.g. v1.0, v2.0) available for a project

list_product_changelogs

List all changelog entries associated with a documentation project

list_recently_updated_pages

Identify documentation pages that have been recently modified

search_documentation_portal

Search for specific keywords across all pages in a documentation project

Example Prompts for DeveloperHub in Pydantic AI

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

"List all documentation pages in the 'API-Reference' project."

"What were the latest updates in our project changelog?"

"Search for 'webhooks' in our documentation portal."

Troubleshooting DeveloperHub MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

DeveloperHub + Pydantic AI FAQ

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