Mention MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Create Monitoring Alert, Favorite Mention, Get Alert Details, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Mention as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The Mention app connector for LlamaIndex is a standout in the Marketing Automation category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Mention. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Mention?"
)
print(response)
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 manage brand monitoring through natural conversation.
LlamaIndex agents combine Mention tool responses with indexed documents for comprehensive, grounded answers. Connect 12 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Brand Monitoring — Track mentions across social media, blogs, and news
- Alert Management — Create and configure keyword monitoring alerts
- Sentiment Analysis — Analyze the sentiment (positive/negative) of mentions
- Social Listening — Browse recent mentions and filter by source or language
- Competitor Tracking — Monitor competitor share of voice
The Mention MCP Server exposes 12 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 12 Mention tools available for LlamaIndex
When LlamaIndex connects to Mention through Vinkius, your AI agent gets direct access to every tool listed below — spanning brand-monitoring, social-listening, sentiment-analysis, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Add new alert
Mark as favorite
Get alert info
Check reach metrics
Read mention details
Get account info
Get event configs
List your alerts
List findings
Mark as seen
Delete an alert
Find mentions
Connect Mention to LlamaIndex via MCP
Follow these steps to wire Mention into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Mention MCP Server
LlamaIndex provides unique advantages when paired with Mention through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Mention tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Mention tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Mention, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Mention tools were called, what data was returned, and how it influenced the final answer
Mention + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Mention MCP Server delivers measurable value.
Hybrid search: combine Mention real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Mention to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Mention for fresh data
Analytical workflows: chain Mention queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Mention in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Mention immediately.
"Show recent mentions for the 'Vinkius Launch' alert."
"List all active alerts and their mention volumes."
"Show negative mentions from the last 2 days."
Troubleshooting Mention MCP Server with LlamaIndex
Common issues when connecting Mention to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpMention + LlamaIndex FAQ
Common questions about integrating Mention MCP Server with LlamaIndex.