Mention MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Mention through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"mention": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using Mention, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
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.
LangChain's ecosystem of 500+ components combines seamlessly with Mention through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
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 LangChain 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 LangChain via MCP
Follow these steps to integrate the Mention MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 10 tools from Mention via MCP
Why Use LangChain with the Mention MCP Server
LangChain provides unique advantages when paired with Mention through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Mention MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across Mention queries for multi-turn workflows
Mention + LangChain Use Cases
Practical scenarios where LangChain combined with the Mention MCP Server delivers measurable value.
RAG with live data: combine Mention tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Mention, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Mention tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Mention tool call, measure latency, and optimize your agent's performance
Mention MCP Tools for LangChain (10)
These 10 tools become available when you connect Mention to LangChain 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 LangChain
Ready-to-use prompts you can give your LangChain 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 LangChain
Common issues when connecting Mention to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersMention + LangChain FAQ
Common questions about integrating Mention MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
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 LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.