Degreed MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Degreed through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 Degreed "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Degreed?"
)
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 Degreed MCP Server
Integrate Degreed, the leading upskilling and learning experience platform (LXP), directly into your AI workflow. Discover available learning content, monitor employee skill profiles, and track progress across pathways and plans using natural language.
Pydantic AI validates every Degreed 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
- Content Discovery — Search the entire Degreed catalog for courses, articles, and videos matching specific keywords.
- Skill Intelligence — List and review the defined skills taxonomy and individual user skill profiles.
- Learning Oversight — Monitor user completions, active learning plans, and curated pathways.
- User Research — Retrieve detailed metadata and activity summaries for learners in your organization.
The Degreed 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 Degreed to Pydantic AI via MCP
Follow these steps to integrate the Degreed 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 Degreed with type-safe schemas
Why Use Pydantic AI with the Degreed MCP Server
Pydantic AI provides unique advantages when paired with Degreed 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 Degreed integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Degreed connection logic from agent behavior for testable, maintainable code
Degreed + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Degreed MCP Server delivers measurable value.
Type-safe data pipelines: query Degreed with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Degreed tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Degreed and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Degreed responses and write comprehensive agent tests
Degreed MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Degreed to Pydantic AI via MCP:
get_content_details
Resolves detailed descriptions, associated skill tags, and duration metadata. Get detailed metadata for a specific learning item
get_user_profile
Resolves assigned skill ratings, learning progress, and active pathways within the Degreed ecosystem. Get full profile and skill data for a specific user
list_active_learners
Identifies users with recent completion activity within the Degreed workspace. List users who have completed learning recently
list_defined_skills
Returns the standardized list of skills and competencies defined by the organization for talent mapping. List the skills taxonomy defined in your organization
list_degreed_users
Returns a list of users with metadata including system IDs, professional titles, and organizational affiliations. List all users registered in your Degreed organization
list_learning_content
Returns content metadata including titles, providers, content types (e.g., article, video, course), and external URLs. List all available learning content in the Degreed catalog
list_learning_pathways
Returns pathway metadata including objectives, total duration, and completion requirements. List curated learning pathways available to users
list_learning_plans
Returns active learning plans, including target completion dates and linked competencies. List learning plans and goals configured in the system
list_user_completions
Returns a history of all learned items with completion timestamps and earned skill points. List all learning content completed by a specific user
search_learning_catalog
Matches terms against titles, descriptions, and skill tags to return a ranked list of relevant learning materials. Search for learning content by keyword or term
Example Prompts for Degreed in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Degreed immediately.
"Search for courses related to 'Data Science with Python'."
"List all learning plans for user 'Alice Johnson'."
"What skills are most common in the 'Engineering' team?"
Troubleshooting Degreed MCP Server with Pydantic AI
Common issues when connecting Degreed to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiDegreed + Pydantic AI FAQ
Common questions about integrating Degreed 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.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
Connect Degreed with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Degreed to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.