phylokit-mcp

Align unaligned sequences with MAFFT, ready for `infer_tree`. The returned `fasta` has every row the same length and can be passed to `infer_tree` or `select_substitution_model` unchanged. Each output row, with its gaps removed, is verified to equal the input sequence before it is returned. Args: fasta: UNALIGNED sequences in FASTA, 2-200 of them. Gap characters are refused: input that is already aligned does not need this tool. sequence_type: "dna" (default) or "protein". Declared, never sniffed, and passed to MAFFT explicitly so it does not guess either.

What this server can do, and the bounds it enforces. `engine_version` is the installed piqtree version (e.g. "0.8.3"); `iqtree_version` is the IQ-TREE build inside it (e.g. "3.1.2"). Args: include_models: Include the full substitution-model list (long).

Robinson-Foulds distance between two trees, and which clades differ. Compares SPLITS, not strings: the same topology has many valid Newick representations, so string equality answers a different question. Args: newick_a: First tree in Newick format. newick_b: Second tree in Newick format.

Build a maximum-likelihood tree and measure how well the data support it. Always bootstraps. There is deliberately no option to skip it: an unsupported topology is the failure mode this server exists to prevent. Args: fasta: Aligned sequences in FASTA, nucleotide or protein as declared by `sequence_type`. All sequences must be the same length — run `align_sequences` first if they are not. model: Substitution model, e.g. "JC", "HKY", "GTR+G" (or "LG+G" for protein). Run `select_substitution_model` first if you do not have a reason to prefer one. replicates: Bootstrap replicates (20-1000). Cost is roughly linear in this, so 100 is a reasonable default and 1000 is for a final answer. seed: 0 to 2**31-1. Fixes the column resampling exactly; the engine's search is seeded too but is not bit-exact (see `reproducibility`). sequence_type: "dna" (default) or "protein". DECLARED, never sniffed: an alignment of only A/C/G/T is a valid protein alignment too, so guessing would silently fit a nucleotide model to protein data. A protein alignment also needs a protein model — "LG+G" or "WAG", not the nucleotide default — so run select_substitution_model with the same sequence_type first.

Compare substitution models and report how much the winner won by. A single model name reads as a finding. The ranking, the delta to the next model, and whether AIC/AICc/BIC agree are what make it one. Args: fasta: Aligned sequences in FASTA, nucleotide or protein as declared by `sequence_type`. criterion: "AIC", "AICc" or "BIC". BIC penalises parameters more heavily. seed: Fixes the engine's search. top_n: How many ranked models to return. sequence_type: "dna" (default) or "protein". Ranks within that molecule type's model set — nucleotide and protein models are not comparable.

Generate sequences along a tree you specify, so the true answer is known. This is the positive control for everything else here: infer a tree from the output and compare it back with `compare_trees`. If inference cannot recover a topology you generated from, the problem is the data or the settings, not the biology. Args: newick: The true tree, with a branch length on every edge. model: Substitution model to simulate under. A protein model ("LG", "WAG", ...) simulates protein; pass the output to `infer_tree` with sequence_type="protein". `alignment.moltype` says which it is. length: Number of sites. seed: Fixes the simulation.