Scaleway MCP Server for LlamaIndexGive LlamaIndex instant access to 3 tools to Create Instance, List Instances, Perform Instance Action

Name: Scaleway
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Scaleway as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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The Scaleway MCP Server for LlamaIndex is a standout in the Developer Tools category — giving your AI agent 3 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

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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 Scaleway. "
            "You have 3 tools available."
        ),
    )

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

asyncio.run(main())

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Ed25519Audit chain

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* 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 Scaleway MCP Server

Connect your Scaleway account to any AI agent to manage your cloud infrastructure through natural language. This server provides direct access to the Scaleway Instances API.

LlamaIndex agents combine Scaleway tool responses with indexed documents for comprehensive, grounded answers. Connect 3 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

Instance Discovery — List all virtual machines across different availability zones (e.g., fr-par-1, nl-ams-1)
Provisioning — Create new instances by specifying names, commercial types (like DEV1-S), and image IDs
Power Management — Remotely power on, power off, or reboot your servers
Lifecycle Control — Terminate instances that are no longer needed directly from the chat

The Scaleway MCP Server exposes 3 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 3 Scaleway tools available for LlamaIndex

When LlamaIndex connects to Scaleway through Vinkius, your AI agent gets direct access to every tool listed below — spanning cloud-computing, virtual-machines, bare-metal, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

create

Create instance on Scaleway

Create a new Scaleway instance (server)

list

List instances on Scaleway

List Scaleway instances (servers) in a specific zone

perform

Perform instance action on Scaleway

Perform an action on a Scaleway instance (e.g., poweron, poweroff)

Connect Scaleway to LlamaIndex via MCP

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

Install dependencies

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

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 3 tools from Scaleway

Why Use LlamaIndex with the Scaleway MCP Server

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

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

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

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

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

Scaleway + LlamaIndex Use Cases

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

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

Data enrichment: query Scaleway 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 Scaleway for fresh data

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

Example Prompts for Scaleway in LlamaIndex

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

"List all my instances in the Paris zone (fr-par-1)."

"Create a new DEV1-S instance named 'staging-app' in fr-par-1 using the Ubuntu image."

"Reboot the server with ID 550e8400-e29b-41d4-a716-446655440000 in nl-ams-1."

Troubleshooting Scaleway MCP Server with LlamaIndex

Common issues when connecting Scaleway to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Scaleway + LlamaIndex FAQ

Common questions about integrating Scaleway MCP Server with LlamaIndex.

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.

Can I combine MCP tools with vector stores?

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