How do I find my Facebook Page ID?

Go to your Facebook Page, click **About** > **Page Transparency**, and you will find your Page ID there. Alternatively, it is available in your **Meta Business Suite** settings.

Can the agent send messages to any Facebook user?

The agent can only send messages to users who have previously messaged your Page (generating a PSID). This is consistent with Meta's developer policies for enterprise messaging.

Is it possible to retrieve full message history via the agent?

Yes. Use the `get_messages` tool providing the Conversation ID. Your agent will retrieve the history, including content and timestamps for all messages in that thread.

Messenger MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: Messenger
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 8 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Messenger 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 Messenger "
            "(8 tools)."
        ),
    )

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

Empower your AI agent to orchestrate your entire mobile communication strategy on Facebook Messenger, the leading platform for social engagement. By connecting Messenger to your agent, you transform enterprise messaging into a natural conversation. Your agent can instantly list your conversations, audit message history, and send replies without you ever touching a complex Meta dashboard. Whether you are providing customer support or managing brand personas, your agent acts as a real-time communication assistant, ensuring your Page is always responsive and your community data is organized.

Pydantic AI validates every Messenger tool response against typed schemas, catching data inconsistencies at build time. Connect 8 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

Conversation Auditing — List all active conversations for your Page and retrieve detailed message history including timestamps.
Messaging Intelligence — Send direct text replies to users instantly to maintain a high response rate.
Persona Oversight — List and retrieve information for brand personas to ensure your bot's identity is correctly applied.
Page Governance — Monitor Page settings and info to maintain strict organizational control over your brand presence.
Content Insights — List message creatives to ensure your automated responses are using the correct media assets.

The Messenger MCP Server exposes 8 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 Messenger to Pydantic AI via MCP

Follow these steps to integrate the Messenger 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 8 tools from Messenger with type-safe schemas

Why Use Pydantic AI with the Messenger MCP Server

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

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

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

Messenger + Pydantic AI Use Cases

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

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

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

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

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

Messenger MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect Messenger to Pydantic AI via MCP:

get_messages

Get message history for a specific conversation

get_page_info

Get basic information about the connected Facebook Page

get_page_settings

Get settings for the Facebook Page

get_persona_info

Get details for a specific persona

list_conversations

List recent Messenger conversations for the page

list_message_creative

List message creatives for the page

list_personas

List all personas for the page

send_message

Send a text message reply to a recipient

Example Prompts for Messenger in Pydantic AI

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

"List all active Messenger conversations for my Page."

"Send 'Thank you for contacting us!' to recipient ID 12345678."

"Show me the message history for conversation t_xxxx."

Troubleshooting Messenger MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Messenger + Pydantic AI FAQ

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