skforecast-ai-mcp
The MCP server of skforecast-ai: deterministic time series forecasting as tools for coding agents (Claude Code, Cursor, VS Code, Codex, Claude Desktop and other MCP clients).
The agent brings the language model and calls skforecast-ai as tools: profile a CSV file, plan a forecaster, backtest it, compare candidates and forecast. Every decision comes from rule-based code, every result comes with the script that produced it, and responses never carry rows of your data.
Usage
The server runs over stdio and needs one directory, --allow-dir: it only reads CSV files inside it. With uv:
uvx skforecast-ai-mcp --allow-dir /absolute/path/to/project
As the entry of an MCP client:
{
"mcpServers": {
"skforecast-ai": {
"command": "uvx",
"args": ["skforecast-ai-mcp", "--allow-dir", "/absolute/path/to/project"]
}
}
}
The setup of each client, the tools, every option and what the server does with your data are in MCP server for coding agents.
What this package is
A launcher with no logic of its own. It installs skforecast-ai[mcp] at the same version and runs skforecast-ai mcp with the arguments it receives, so these two commands start the same server:
uvx skforecast-ai-mcp --allow-dir /absolute/path/to/project
uvx --from "skforecast-ai[mcp]" skforecast-ai mcp --allow-dir /absolute/path/to/project
It exists because the MCP registry names a package, not one of its extras.
License
Apache-2.0, as skforecast-ai.
Metadata
Release files for skforecast-ai-mcp 0.4.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| skforecast_ai_mcp-0.4.2.tar.gz | 6.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| skforecast_ai_mcp-0.4.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 13.8 kB
Release files / skforecast_ai_mcp-0.4.2.tar.gz
| Download URL | skforecast_ai_mcp-0.4.2.tar.gz |
|---|---|
| Size | 6.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / skforecast_ai_mcp-0.4.2-py3-none-any.whl
| Download URL | skforecast_ai_mcp-0.4.2-py3-none-any.whl |
|---|---|
| Size | 7.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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cfaf1f03c314f8637104f927983486f162b0c81b1399c07129f0594d42de990a
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 12, 2026.
Transparency log