Clearout MCP Server for LlamaIndexGive LlamaIndex instant access to 10 tools to Cancel Bulk, Check Clearout Status, Download Results, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Clearout 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 Clearout app connector for LlamaIndex is a standout in the Marketing Automation category — giving your AI agent 10 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 Clearout. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Clearout?"
)
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 Clearout MCP Server
Connect your Clearout email intelligence account to any AI agent and simplify how you clean your contact lists, verify deliverability, and discover professional email addresses through natural conversation.
LlamaIndex agents combine Clearout tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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
- Email Verification — Instantly check if an email address is valid, active, and safe for your outreach campaigns.
- Lead Discovery — Find professional email addresses for prospects using only their full name and company domain.
- Deliverability Protection — Identify disposable, role-based, or catch-all addresses to protect your sender reputation.
- Credit Monitoring — Track your account usage and remaining API credits directly from the agent.
- Real-time Validation — Integrate verification into your automated workflows via simple AI commands.
- Prospect Insights — Verify lead data quality before adding them to your CRM or marketing machine.
The Clearout MCP Server exposes 10 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 10 Clearout tools available for LlamaIndex
When LlamaIndex connects to Clearout through Vinkius, your AI agent gets direct access to every tool listed below — spanning email-verification, email-deliverability, lead-discovery, 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.
Already processed emails retain their results. Cancel a bulk verification
Verify Clearout API connectivity
Download verification results
Find a business email
Check bulk verification progress
Check credit balance
Remove a bulk list
Returns a list ID to track progress. Verify emails in bulk
Verify catch-all domain
Verify a single email
Connect Clearout to LlamaIndex via MCP
Follow these steps to wire Clearout 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 Clearout MCP Server
LlamaIndex provides unique advantages when paired with Clearout through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Clearout tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Clearout tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Clearout, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Clearout tools were called, what data was returned, and how it influenced the final answer
Clearout + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Clearout MCP Server delivers measurable value.
Hybrid search: combine Clearout real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Clearout 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 Clearout for fresh data
Analytical workflows: chain Clearout queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Clearout in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Clearout immediately.
"Verify if the email 'john.doe@example.com' is safe to send to."
"Find the professional email for 'Steve Jobs' at 'apple.com'."
"How many validation credits do I have left?"
Troubleshooting Clearout MCP Server with LlamaIndex
Common issues when connecting Clearout to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpClearout + LlamaIndex FAQ
Common questions about integrating Clearout MCP Server with LlamaIndex.