How to Use the Metricool MCP in Pydantic AI

Q: How do I connect Pydantic AI to the Metricool MCP Server?

You register the Vinkius HTTP endpoint using the MCPToolset class. This exposes all 10 social analytics tools directly to your type-safe agents.

Q: Can I use Pydantic AI with Metricool tools offline?

No, tools like gettwitteranalytics and getlinkedinanalytics require live API access to fetch current performance data from Vinkius.

Validate Metricool social metrics at runtime using Pydantic AI type-safe agent toolsets.

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Connect Metricool MCP to Pydantic AI

Create your Vinkius account to connect Metricool 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 Metricool with Pydantic AI

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Validate Social Metrics with Pydantic AI

The `get_unified_summary` tool returns structured cross-channel data that your Pydantic AI agent validates against strict Python schemas. This prevents unexpected Metricool API changes from corrupting your downstream Pydantic AI databases.

Type-Safe Planning via MCP Server Tools

The `get_social_planner` tool retrieves scheduling data that matches your internal Pydantic AI data models. Your Pydantic AI agent parses the Metricool calendar structure with complete type safety.

Audit Connected Profiles Safely

The `list_metricool_profiles` tool provides a clean inventory of your managed social accounts to Pydantic AI. Your Pydantic AI agent verifies the structural integrity of each Metricool profile object before running deeper queries.

Setup guide

Set up Metricool 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": {
        "metricool-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Metricool now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Metricool MCP in Pydantic AI

The Pydantic AI client raises a validation error at runtime. This prevents your agent from executing decisions based on corrupted or misaligned social data.

You register the Vinkius HTTP endpoint using the `MCPToolset` class. This exposes all 10 social analytics tools directly to your type-safe agents.

No, tools like `get_twitter_analytics` and `get_linkedin_analytics` require live API access to fetch current performance data from Vinkius.

Yes, the framework handles asynchronous tool execution natively. Your agent can query `get_ads_performance` and `get_facebook_analytics` concurrently.

Vinkius handles the MCP server execution ephemerally. Your scheduling logs and API credentials are processed in memory and immediately discarded, leaving zero digital footprint.

Use it with your favorite AI tools

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