Mention MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Mention through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 Mention "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Mention?"
)
print(result.data)
asyncio.run(main())
* 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 Mention MCP Server
Connect your Mention account to any AI agent and take full control of your social monitoring and brand alerts through natural conversation.
Pydantic AI validates every Mention 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
- Alert Management — List all active monitoring alerts and fetch detailed configuration metadata
- Mention Tracking — Retrieve recent social media mentions, filter for favorites, and search by text
- Deep Inspection — Fetch full content, metadata, and sentiment analysis for specific mentions
- Brand Analytics — Access volume and sentiment statistics for your monitoring alerts instantly
- Account Visibility — List authorized users and connected external social media accounts
The Mention 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 Mention to Pydantic AI via MCP
Follow these steps to integrate the Mention 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 Mention with type-safe schemas
Why Use Pydantic AI with the Mention MCP Server
Pydantic AI provides unique advantages when paired with Mention 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 Mention integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Mention connection logic from agent behavior for testable, maintainable code
Mention + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Mention MCP Server delivers measurable value.
Type-safe data pipelines: query Mention with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Mention tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Mention and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Mention responses and write comprehensive agent tests
Mention MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Mention to Pydantic AI via MCP:
get_account_info
Get account information
get_alert
Get details for a specific alert
get_alert_statistics
Get statistics for an alert
get_mention_details
Get details for a specific mention
list_account_users
List users associated with the account
list_alerts
List all monitoring alerts
list_connected_external_accounts
) linked. List connected social accounts
list_favorite_mentions
List favorite mentions for an alert
list_mentions
List mentions for an alert
search_mentions
Search mentions by text
Example Prompts for Mention in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Mention immediately.
"List all active alerts in my Mention account."
"Search mentions for 'artificial intelligence' in alert ID 123."
"Show volume statistics for my primary brand alert."
Troubleshooting Mention MCP Server with Pydantic AI
Common issues when connecting Mention to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiMention + Pydantic AI FAQ
Common questions about integrating Mention MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
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?
Can I switch LLM providers without changing MCP code?
Connect Mention with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Mention to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.