mne.tools — September 2026 traffic, keywords & AI visibility

Search engines send mne.tools an estimated 3,122 visits a month. Effectively all of it is organic — about 3,122 visits from unpaid results. Spread across 158 ranking keywords, that averages roughly 20 organic visits per keyword.

mne.tools scores 85 out of 100 on our AI visibility scale, grade A. It takes full marks for LLMS.txt and Structured data. The biggest gap is Crawlability, at 0 of 10 points (robots ✗ · sitemap ✗), worth 10 points if closed. It also loses points on Company profile (22/25) and SEO health (18/20).

The llms.txt on mne.tools runs to 150 lines (7,907 characters) across 12 sections, last generated in May 2026. It introduces the site as "MNE-Python: Open source Python-based toolbox for analyzing human neurophysiological data". It tells AI engines the business works in Neuroscience, Data Analysis and Open Source Software. It describes 4 products, with prices such as MNE-Python at Free (Open Source), MNE-BIDS at Free (Open Source) and MNE-NAT at Free (Open Source). Services it lists include Community Tutorials, Forum Support, Custom Pipeline Development and Workshop Hosting. The audience it names is Academic Researchers, Neuroscientists, Data Analysts, aged 25-55 (Global). Technologies it mentions include Python 3, NumPy, SciPy, Matplotlib and scikit-learn. The keywords it claims start with "MNE-Python", "MNE", "MNE tools" and "neuroscience". It gives the company type as Open Source Project.

# MNE-Python: Open source Python-based toolbox for analyzing human neurophysiological data

## About
MNE-Python delivers a robust ecosystem for handling MEG and EEG datasets right in Python. It covers everything from loading raw files in various formats to sophisticated forward and inverse modeling. Users preprocess signals with filtering, artifact rejection, and epoching tailored to experimental designs. Visualization tools render topomaps, sensor layouts, and 3D brain surfaces interactively. Statistical modules support non-parametric tests and cluster-based inference for publication-ready results. The package thrives on community input, with plugins for hyperscanning and real-time analysis. It bridges neuroscience and data science by leveraging pandas for metadata and xarray for multidimensional arrays. Tutorials walk beginners through sleep staging or motor imagery decoding. Advanced folks customize with C extensions for speed on big data. BIDS support streamlines sharing across labs. Machine learning integration lets you train decoders on evoked responses. It's battle-tested in hundreds of papers yearly. Free access democratizes high-end tools once locked in proprietary software. Contributors span continents, ensuring cross-platform reliability. Documentation rivals commercial suites, with galleries showcasing real analyses. From academia to pharma, it accelerates hypothesi

Google lists mne.tools for about 158 keywords, which together bring an estimated 3,122 organic visits a month.

The latest technical audit of mne.tools scored 89 out of 100 overall. Performance is its weakest area at 67, while accessibility scores highest at 100. The audit makes 12 recommendations in all, and 4 of the 4 listed first are rated high priority or critical.

MNE-Python's company profile names https://www.eeglab.org, https://www.fieldtriptoolbox.org, https://www.biosignaltools.com and https://www.mne-cpp.org as competitors. Its own llms.txt adds https://www.openvibe.org and https://www.neurokit.org. Outside its market, the domains ranked closest to it in our worldwide ranking are powercorecollective.co.uk, e5336.cn, feuerwehr-stadtmarlow.de and nathanmyhrvold.com.

https://www.eeglab.org

https://www.fieldtriptoolbox.org

https://www.biosignaltools.com

https://www.mne-cpp.org

https://www.openvibe.org

https://www.neurokit.org