General Tools

aixenergy.io

Provides general-purpose tools through the Model Context Protocol.

WebMCP1 endpoint3 known toolsFirst detected September 30, 2026Last detected September 30, 2026

ENDPOINT 1

https://www.aixenergy.io

No auth detected

Capabilities

imperative

Open the AIxEnergy interactive map of AI infrastructure projects, energy constraints, and policy actions.

Inferred read-only

Open the AIxEnergy membership signup interface for intelligence and publication access.

Inferred read-only

Open the secure AIxEnergy member sign-in interface.

Inferred read-only

CONNECT WITH APPROVAL

Review this server and its permissions before adding it. Secret placeholders must be set locally.

Codex

~/.codex/config.toml

[mcp_servers.webmcp]
url = "https://www.aixenergy.io"
enabled = true

Claude Code

.mcp.json

{
  "mcpServers": {
    "webmcp": {
      "type": "http",
      "url": "https://www.aixenergy.io"
    }
  }
}

Claude Desktop

Settings → Connectors → Add custom connector

Name: webmcp
Remote MCP URL: https://www.aixenergy.io

Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.

Cursor

.cursor/mcp.json

{
  "mcpServers": {
    "webmcp": {
      "url": "https://www.aixenergy.io"
    }
  }
}

Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code

{
  "servers": {
    "webmcp": {
      "type": "http",
      "url": "https://www.aixenergy.io"
    }
  }
}

Generic MCP

Client-specific MCP configuration

{
  "name": "webmcp",
  "transport": "streamable-http",
  "url": "https://www.aixenergy.io"
}

MCP Inspector

Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.

TRUST AND VERIFICATION EVIDENCE

BuiltWith Trust API v2 evidence for aixenergy.io was fetched 2026-10-01T23:09:34.975Z.

Trust status Trusted

aixenergy.io is assessed as Trusted: Domain has an established technology history spanning over a year.

Indexed

Evidence is source-attributed and does not guarantee that a third-party server is safe. Risk labels are conservative metadata heuristics.