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skforecast-ai MCP Server

by skforecast Your server? Claim it
local only

skforecast-ai runs on your own machine — the client starts it, so there is no endpoint to ping. 251 installs a week from pypi. Last commit 16 Oct 2026.

Forecast time series in CSV files: deterministic skforecast workflows and the script that ran.

Installs per day peak 551 · avg 49 · -55% w/w
a month agotoday
251
Installs / week
pypi · skforecast-ai-mcp
52
Stars
1 open issue
16 Oct 2026
Last commit
from GitHub
Apache-2.0
License
Python

What the code does

We read the source, 4 d ago · rules 995398eba69f

In the project's build, not in the package

Found in continuous integration, deployment or infrastructure files, or in a neighbouring package of the same monorepo. None of this is installed when you add the server: it describes how the project is built and released. We list it because a leaked key in a build pipeline is still a real problem, but it is not something this server does on your machine.

Builds a file path from a variable .claude/hooks/stop_check.py:39
        and os.path.isfile(os.path.join(cwd, f))
Executes code built at runtime skforecast_ai/execution/_exec.py:84
                exec(compiled, namespace)  # noqa: S102
Unsafe deserialization tools/perf/_datasets.py:94
            return pickle.load(file)
Dumps the whole environment tools/perf/mcp_startup.py:138
    env = dict(os.environ)

Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.

Nothing serious here today

Today is the operative word: we check skforecast-ai every 15 minutes and re-read its code on every release. Watch it and you find out the day that stops being true.

Three servers free · no card

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.

run in your terminal
claude mcp add skforecast-ai -- uvx skforecast-ai-mcp
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "skforecast-ai": {
      "command": "uvx",
      "args": [
        "skforecast-ai-mcp"
      ]
    }
  }
}
~/.codex/config.toml
[mcp_servers.skforecast-ai]
command = "uvx"
args = ["skforecast-ai-mcp"]
.cursor/mcp.json
{
  "mcpServers": {
    "skforecast-ai": {
      "command": "uvx",
      "args": [
        "skforecast-ai-mcp"
      ]
    }
  }
}
.vscode/mcp.json
{
  "servers": {
    "skforecast-ai": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "skforecast-ai-mcp"
      ]
    }
  }
}

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skforecast-ai — questions

Answers built from our own checks of this server.

Why is there no uptime for skforecast-ai?
skforecast-ai 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 skforecast-ai-mcp was installed 251 times last week.
How do I connect skforecast-ai?
Copy the ready config from this page. We generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each in the form that client actually reads. It runs locally, so the command pulls skforecast-ai-mcp straight from pypi; nothing to host, nothing to sign up for.
How many people use skforecast-ai?
The pypi package skforecast-ai-mcp was installed 251 times in the last week. Week over week that is -55%. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.
Is skforecast-ai open source?
Yes — it is published under the Apache-2.0 licence, written in Python, 52 stars on GitHub and 1 open issue. The source link is on this page, so you can read exactly what it does with your data before you connect it.