Dataxplan MCP Server

io.github.arikanatakan/dataxplan-mcp

local only

Dataxplan MCP runs on your own machine — the client starts it, so there is no endpoint to ping. 55 installs a week from pypi.

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Installs per day peak 32 · avg 10 · -4% w/w

a month agotoday

Installs / week

pypi · dataxplan-mcp

—

Stars

on GitHub

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Last commit

0 releases in 90 days

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License

language unknown

Connect this server

This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.

Claude Code Claude Desktop Codex Cursor VS Code

run in your terminal

claude mcp add dataxplan-mcp -- uvx dataxplan-mcp

~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "dataxplan-mcp": {
      "args": [
        "dataxplan-mcp"
      ],
      "command": "uvx"
    }
  }
}

~/.codex/config.toml

[mcp_servers.dataxplan-mcp]
command = "uvx"
args = ["dataxplan-mcp"]

.cursor/mcp.json

{
  "mcpServers": {
    "dataxplan-mcp": {
      "args": [
        "dataxplan-mcp"
      ],
      "command": "uvx"
    }
  }
}

.vscode/mcp.json

{
  "mcpServers": {
    "dataxplan-mcp": {
      "args": [
        "dataxplan-mcp"
      ],
      "command": "uvx"
    }
  }
}

Dataxplan MCP — questions

Answers built from our own checks of this server.

Why is there no uptime for Dataxplan MCP?

Dataxplan MCP runs on your own machine over stdio — there is no network address to reach, so uptime cannot be measured for it by anyone. What can be measured is adoption: the pypi package dataxplan-mcp was installed 55 times last week.

How do I connect Dataxplan MCP?

Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It runs locally, so the command pulls dataxplan-mcp straight from pypi; nothing to host, nothing to sign up for.

How many people use Dataxplan MCP?

The pypi package dataxplan-mcp was installed 55 times in the last week. Week over week that is -4%. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.