osmapiR
osmapiR is the rare API client that tracks its server's wiki revision numbers in the changelog.
Comparison · Analytics
graphicalMCP vs xplainfi
A side-by-side editorial comparison of graphicalMCP and xplainfi — release velocity, themes, recent moves, and the top alternatives to consider.
graphicalMCP vs xplainfi: at a glance
What is graphicalMCP?
graphicalMCP is a narrow statistical tool being hardened rather than grown.
graphicalMCP implements graphical multiple comparison procedures — the method used to control family-wise error across several endpoints in a clinical trial. The package moved under the openpharma organisation in 0.2.6, picked up Hochberg tests and internal validation in 0.2.8, and its most recent release fixes a case where graph testing by closure disagreed with the rejection-based path. Releases are roughly annual and short.
What is xplainfi?
xplainfi treats feature importance as an estimate with error bars, not a number.
xplainfi implements feature importance methods for mlr3 — perturbation-based PFI, CFI and RFI, refit-based LOCO and WVIM, and SAGE. Its defining choice is that importance scores come with inference attached: several confidence-interval methods, including the Nadeau-Bengio correction and a distribution-free option added in 1.1.0. It declared itself released at 1.0.0 in January 2026.
graphicalMCP vs xplainfi: editorial side-by-side
graphicalMCP
0.0ANALYTICS
graphicalMCP is a narrow statistical tool being hardened rather than grown.
◆ Current state
graphicalMCP implements graphical multiple comparison procedures — the method used to control family-wise error across several endpoints in a clinical trial. The package moved under the openpharma organisation in 0.2.6, picked up Hochberg tests and internal validation in 0.2.8, and its most recent release fixes a case where graph testing by closure disagreed with the rejection-based path. Releases are roughly annual and short.
◆ Where it's heading
The changelog reads as a package settling into reference-implementation status: procedure coverage widened once, then the work turned to proving the two computational routes through the same graph agree with each other. That agreement is the whole promise of this kind of tool, since the closure-based calculation is the definition and the rejection-based one is the fast path everyone actually runs. The openpharma move points the same direction — shared maintenance rather than a single author's project.
◆ Prediction
The entries show no feature roadmap, only correctness and validation work, so the next release is most likely another consistency or precision fix rather than a new procedure.
xplainfi
2.5ANALYTICS
xplainfi treats feature importance as an estimate with error bars, not a number.
◆ Current state
xplainfi implements feature importance methods for mlr3 — perturbation-based PFI, CFI and RFI, refit-based LOCO and WVIM, and SAGE. Its defining choice is that importance scores come with inference attached: several confidence-interval methods, including the Nadeau-Bengio correction and a distribution-free option added in 1.1.0. It declared itself released at 1.0.0 in January 2026.
◆ Where it's heading
Two lines of work run in parallel. The statistical side keeps adding inference options — variance corrections, conditional predictive impact, and the Lei et al. observation-wise loss-difference test — while the computational side attacks the cost of refit-based methods, most recently with a batch_size argument that parallelises refits and a default of one refit per resampling iteration. Support for pre-trained learners in 1.1.0 removes the refit requirement entirely in some workflows.
◆ Prediction
The stated reasoning that budget is better spent on resampling iterations than repeated refits suggests n_repeats may be removed from WVIM and LOCO outright, as the release notes hint.
Alternatives to graphicalMCP and xplainfi
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either graphicalMCP or xplainfi.
ymlthis
ymlthis retired itself, naming Quarto as the reason it no longer needs to exist.
forestly
forestly built an interactive safety review tool, then taught it to produce submission-ready RTF.
pharmaverseadam
pharmaverseadam is the pharmaverse's test-data mirror, and it now covers neurology.
pkglite
pkglite's whole job is knowing which files in an R package are text — and it keeps getting better at guessing.
gMCPLite
gMCPLite exists to be gMCP without Java, and its releases guard that boundary rather than extend it.
See all graphicalMCP alternatives → · See all xplainfi alternatives →
Recent activity from graphicalMCP and xplainfi
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 21d agoxplainfiRefits parallelise; repeated refits deprioritised in favour of resampling
- 4mo agographicalMCPClosure-based and rejection-based graph tests now agree
- 5mo agoxplainfiPre-trained learners supported; distribution-free inference added
- 6mo agoxplainfiVersion bumped to mark the package as released
- 9mo agoxplainfiConfidence intervals arrive for feature importance scores
- 1y agographicalMCPHochberg tests and internal validation added
- 1y agographicalMCPRepository moved to the openpharma organisation
- 2y agographicalMCPCRAN resubmission housekeeping
- 2y agographicalMCPFirst release of the graphical MCP implementation
Frequently asked questions
What is the difference between graphicalMCP and xplainfi?
They serve adjacent needs but don't currently overlap on shipped themes. xplainfi is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is graphicalMCP better than xplainfi?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. xplainfi is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to graphicalMCP?
Top graphicalMCP alternatives in Analytics are ranked by recent ship velocity. Browse the "graphicalMCP alternatives" section above for the current picks, or visit /alternatives/graphicalmcp for the full list with editorial commentary on each.
What are the best alternatives to xplainfi?
Top xplainfi alternatives in Analytics are ranked by recent ship velocity. Browse the "xplainfi alternatives" section above for the current picks, or visit /alternatives/xplainfi for the full list with editorial commentary on each.