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Residential Proxies MCP Server for LlamaIndexGive LlamaIndex instant access to 10 tools to Check Proxy Status, Get Br Proxies, Get De Proxies, and more

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LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Residential Proxies 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 Residential Proxies app connector for LlamaIndex is a standout in the Developer Tools 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

python
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 Residential Proxies. "
            "You have 10 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Residential Proxies?"
    )
    print(response)

asyncio.run(main())
Residential Proxies
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
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 Residential Proxies MCP Server

Connect your AppVidLab Residential Proxies account to any AI agent and take full control of your automated web data collection and proxy rotation workflows through natural conversation.

LlamaIndex agents combine Residential Proxies 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

  • Proxy Pool Orchestration — List and manage your entire high-fidelity database of working residential proxies programmatically, retrieving detailed IP and port technical metadata
  • Geo-Targeting Intelligence — Programmatically query and monitor proxies from specific countries to coordinate your international data mining strategy in real-time
  • Rotation Architecture — Access high-fidelity rotating IP strings to maintain a perfectly coordinated audit trail of your scraping sessions and bypass bot detection
  • Availability Monitoring — Access real-time status updates and track proxy health directly through your agent for instant operational reporting
  • Infrastructure Verification — Verify account-level API connectivity and monitor proxy usage directly through your agent for perfectly coordinated service scaling

The Residential Proxies 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 Residential Proxies tools available for LlamaIndex

When LlamaIndex connects to Residential Proxies through Vinkius, your AI agent gets direct access to every tool listed below — spanning proxy-rotation, ip-anonymity, data-collection, 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.

check_proxy_status

Verify Residential Proxies API connectivity

get_br_proxies

Get Brazil residential proxies

get_de_proxies

Get Germany residential proxies

get_multi_country_proxies

Returns a summary with counts and sample proxies per country. Get proxies from multiple countries at once

get_proxies_by_country

g., US, GB, DE, BR). Get residential proxies filtered by country

get_proxies_limited

Useful for testing or sampling available proxies. Get a limited number of proxies

get_proxy_count

Get the total number of available proxies

get_uk_proxies

Get United Kingdom residential proxies

get_us_proxies

Get United States residential proxies

list_proxies

List all available residential proxies

Connect Residential Proxies to LlamaIndex via MCP

Follow these steps to wire Residential Proxies into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 10 tools from Residential Proxies

Why Use LlamaIndex with the Residential Proxies MCP Server

LlamaIndex provides unique advantages when paired with Residential Proxies through the Model Context Protocol.

01

Data-first architecture: LlamaIndex agents combine Residential Proxies tool responses with indexed documents for comprehensive, grounded answers

02

Query pipeline framework lets you chain Residential Proxies tool calls with transformations, filters, and re-rankers in a typed pipeline

03

Multi-source reasoning: agents can query Residential Proxies, a vector store, and a SQL database in a single turn and synthesize results

04

Observability integrations show exactly what Residential Proxies tools were called, what data was returned, and how it influenced the final answer

Residential Proxies + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Residential Proxies MCP Server delivers measurable value.

01

Hybrid search: combine Residential Proxies real-time data with embedded document indexes for answers that are both current and comprehensive

02

Data enrichment: query Residential Proxies to augment indexed data with live information before generating user-facing responses

03

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Residential Proxies for fresh data

04

Analytical workflows: chain Residential Proxies queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for Residential Proxies in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Residential Proxies immediately.

01

"List 10 working residential proxies from the USA."

02

"Show available residential proxies for country code 'GB'."

03

"Check my RapidAPI status and proxy usage metrics."

Troubleshooting Residential Proxies MCP Server with LlamaIndex

Common issues when connecting Residential Proxies to LlamaIndex through the Vinkius, and how to resolve them.

01

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Residential Proxies + LlamaIndex FAQ

Common questions about integrating Residential Proxies MCP Server with LlamaIndex.

01

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.
02

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Residential Proxies tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.
03

Does LlamaIndex support async MCP calls?

Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.