How do I get a Credly API Key?

Log in to your Credly account and navigate to the organization settings to generate or retrieve your API Key. Ensure you have administrative privileges.

Can the agent issue badges to new recipients?

This integration currently provides tools for listing and auditing badges and templates. Issuing new badges should be handled through the Credly dashboard or specific automated workflows.

What badge details can I retrieve?

You can retrieve full badge profiles including recipient details, template criteria, associated skills, and current status (e.g., pending, accepted).

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

Name: Credly
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 Credly 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 Credly "
            "(10 tools)."
        ),
    )

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

asyncio.run(main())

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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 Credly MCP Server

Integrate Credly, the world's largest digital credential network, directly into your AI workflow. Manage your organization's badge templates, audit issued credentials, and track member skills using natural language.

Pydantic AI validates every Credly 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

Badge Management — List all issued badges and explore your organization's badge templates.
Issuance Auditing — Monitor which recipients have received badges and track authorized issuers.
Skill Tracking — Explore the full inventory of skills mapped to your digital credentials.
Organization Insights — Retrieve metadata and member lists for your connected organizations.

The Credly 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 Credly to Pydantic AI via MCP

Follow these steps to integrate the Credly 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 Credly with type-safe schemas

Why Use Pydantic AI with the Credly MCP Server

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

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

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

Credly + Pydantic AI Use Cases

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

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

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

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

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

Credly MCP Tools for Pydantic AI (10)

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

get_badge_details

Get detailed information for a specific issued badge

get_organization_info

Get metadata for a specific organization

get_template_details

Get full design and criteria for a badge template

list_authorized_issuers

List people authorized to issue badges

list_badge_recipients

List people who have received badges

list_badge_skills

List all skills mapped to badges in the system

list_badge_templates

List all badge templates available for issuance

list_connected_organizations

List organizations connected to your account

list_issued_badges

List all badges issued by your organization

list_org_members

List all members of your organization on Credly

Example Prompts for Credly in Pydantic AI

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

"List all badges issued by my organization in the last month."

"Show me the details for badge ID 'b8s9df7'."

"What skills are associated with the 'Senior DevOps Engineer' badge template?"

Troubleshooting Credly MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Credly + Pydantic AI FAQ

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