How to Use the Credly MCP in Pydantic AI

Fetch type-safe Credly badge and skill data validated at runtime with Pydantic AI.

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Connect Credly MCP to Pydantic AI

Create your Vinkius account to connect Credly to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Credly with Pydantic AI

Ask AI about this MCP

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Claude

Perplexity

Type-safe badge template inspections

Stop worrying about API payload changes breaking your production code. Pydantic AI wraps this MCP Server and validates every response from `get_template_details` and `list_badge_templates` against strict Python schemas. If the API structure changes, the validation fails immediately at runtime. You get clean, predictable data structures for your badge criteria and design assets instead of unexpected null values.

Validate recipient records with Pydantic AI

Ensure your talent reports are completely accurate. The agent queries `list_badge_recipients` and `get_badge_details` to build a list of certified professionals. Every single recipient record is validated against strict types before your agent processes it. This prevents your model from hallucinating badge IDs or parsing dates incorrectly.

Audit organization structures securely

Track your corporate hierarchy and connected entities without data drift. Using `list_connected_organizations` and `list_org_members`, your agent maps out your entire badging footprint. The framework ensures that data returned by these tools matches your internal Pydantic models. You can confidently write automated scripts to sync your internal HR databases with external records.

Setup guide

Set up Credly MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "credly-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Credly tools.",
)

result = await agent.run("List recent Credly transactions")
print(result.output)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Credly. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

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Common questions about Credly MCP in Pydantic AI

Use the unified MCPToolset pointing to your Vinkius HTTP endpoint. Pass this toolset into your Agent constructor to give your model immediate, type-safe access to `list_badge_skills`.

The framework will raise a validation error instantly. This prevents your agent from processing corrupt or incomplete badge records, keeping your downstream databases clean.

Yes, you can control which tools are exposed when configuring your MCP Server toolset. This lets you restrict your agent to harmless lookup tools like `list_badge_templates` while hiding admin tools.

Yes, Pydantic AI is built for async Python. Your agent can query `list_issued_badges` and process hundreds of credentials concurrently without blocking your main event loop.

Your API credentials are never exposed to the LLM or stored on Vinkius. They are injected as secure environment variables, and the MCP Server environment ensures all badge and recipient data remains private.

Use it with your favorite AI tools

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