How do I get an Eden AI API Key?

Log in to your Eden AI account, navigate to **Account Settings** or the **API** section, and you can generate or retrieve your unique API Key from there.

Does the integration support all AI providers?

Yes, Eden AI provides a unified interface for many providers. The agent can retrieve availability and pricing for any provider currently supported by the Eden AI platform.

Can the agent trigger workflow executions?

This integration currently focuses on listing and auditing workflows, providers, and usage. Triggering new workflow executions should be managed via specific Eden AI API calls or the platform dashboard.

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

Name: Eden AI
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 Eden AI 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 Eden AI "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Eden AI?"
    )
    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 Eden AI MCP Server

Integrate Eden AI, the unified AI API platform, directly into your AI workflow. Manage your automation workflows and pipelines, track available AI providers (OpenAI, Google, AWS, etc.) across various features, monitor real-time API usage and costs, and oversee your LLM models using natural language.

Pydantic AI validates every Eden AI 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

Workflow Oversight — List and retrieve detailed information and status for all your configured AI automation workflows.
Provider Intelligence — Access the provider registry to monitor available AI capabilities, pricing, and service levels for specific features.
Usage Monitoring — Track real-time API consumption statistics, credit balance, and organizational spending across all providers.
Model Management — List all specific large language models (LLMs) and AI features supported by the Eden AI platform.

The Eden AI 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 Eden AI to Pydantic AI via MCP

Follow these steps to integrate the Eden AI 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 Eden AI with type-safe schemas

Why Use Pydantic AI with the Eden AI MCP Server

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

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

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

Eden AI + Pydantic AI Use Cases

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

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

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

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

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

Eden AI MCP Tools for Pydantic AI (10)

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

get_ai_feature_pricing

Identify the pricing for a specific AI feature across different providers

get_api_usage_statistics

Retrieve technical statistics on your API usage and costs

get_eden_ai_metadata

Retrieve metadata and credit balance for your Eden AI account

get_workflow_configuration

Get detailed settings and steps for a specific AI workflow

list_ai_providers

List all AI providers (OpenAI, Google, AWS, etc.) available for a specific feature

list_ai_workflows

List all AI automation workflows configured in your Eden AI account

list_all_llm_models

List all specific large language models available through the unified API

list_available_ai_features

List all AI features and subfeatures supported by the Eden AI platform

list_latest_ai_automations

Identify the most recently updated AI workflows

quick_ai_provider_audit

Retrieve a high-level summary of available providers for text analysis

Example Prompts for Eden AI in Pydantic AI

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

"List all active AI workflows."

"Show me the pricing for 'sentiment_analysis' across providers."

"What is my current Eden AI credit balance?"

Troubleshooting Eden AI MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Eden AI + Pydantic AI FAQ

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