SeqBench

SeqBench MCP Server & API

Call SeqBench’s DNA, RNA and protein tools straight from an AI agent or your own code. The same pure algorithms behind the website are exposed as a Model Context Protocol (MCP) server and a plain JSON REST API — a bioinformatics MCP server and sequence-analysis REST API in one. Prefer a conversation in the browser? SeqBench-GPT uses the same tools for multi-step cloning and CRISPR design, with a code-enforced verification gate before a design is marked finished.

  • Stateless execution
  • Deterministic tools
  • 82 tools
  • MCP + REST
  • Works with Claude & Cursor

Connect via MCP

Add the Streamable-HTTP endpoint https://seqbench.com/api/mcp to your MCP client (Claude Code, Claude Desktop, Cursor, …). In Cursor, one click:

▷ Add to Cursor

Or add it to your client config manually:

json
{
  "mcpServers": {
    "seqbench": {
      "type": "http",
      "url": "https://seqbench.com/api/mcp"
    }
  }
}

A client that only supports stdio servers can bridge to this URL with npx mcp-remote https://seqbench.com/api/mcp.

Use the REST API

Every tool is also at POST /api/v1/<tool> with a JSON body. List all tools and their schemas at GET /api/v1.

bash
curl -X POST https://seqbench.com/api/v1/melting_temperature \
  -H "Content-Type: application/json" \
  -d '{"sequence":"GCGGATCCATGAGCAAAGGAGAAGAA"}'

Batch & workflows

Process a whole multi-FASTA in one call. POST /api/v1/batch runs one tool over every record; POST /api/v1/workflow runs a multi-tool pipeline where each step’s sequence output feeds the next. Both are also MCP tools (batch, workflow). List batchable/pipeline tools and limits at GET /api/v1/batch and GET /api/v1/workflow.

bash
curl -X POST https://seqbench.com/api/v1/batch \
  -H "Content-Type: application/json" \
  -d '{"tool":"gc_content","input":">a\nATGC\n>b\nGGCC"}'
bash
curl -X POST https://seqbench.com/api/v1/workflow \
  -H "Content-Type: application/json" \
  -d '{"input":">cds\nATGAGCAAAGGA","steps":[
        {"tool":"reverse_complement"},
        {"tool":"translate"},
        {"tool":"protein_properties"}
      ]}'

Tools (82)

Sequence (5)

reverse_complement⧉Reverse, complement and reverse complement of a DNA or RNA sequence.
gc_content⧉GC content, AT content and per-base composition of a sequence.
format_sequence⧉Clean, case-fold, DNA↔RNA convert, reverse and line-wrap a sequence.
motif_finder⧉Find (overlapping) occurrences of an IUPAC motif on either strand, allowing mismatches.
random_sequenceGenerate a random DNA, RNA or protein sequence, optionally with a target GC content.

Translation & ORFs (3)

translate⧉Translate a nucleotide sequence to protein (single frame or all six frames; standard code).
find_orfs⧉Find open reading frames (ATG…stop) across all six frames.
reverse_translate⧉Back-translate a protein to DNA (most-frequent codon per organism, or degenerate IUPAC consensus).

Primers & oligos (11)

melting_temperature⧉Primer/oligo melting temperature: nearest-neighbour (SantaLucia 1998) plus Wallace and salt-adjusted estimates, with the length-appropriate recommendation and molecular weights.
oligo_analysis⧉Full oligo analysis: nearest-neighbour Tm/ΔG/ΔH/ΔS plus hairpin and self-dimer screening with base-pair diagrams and warnings.
in_silico_pcr⧉Predict PCR products for a template and a pair of primers (IUPAC-aware, allows mismatches, handles circular templates).
primer_designDe-novo PCR primer design (Primer3-style penalty picker): enumerate and score candidate primer pairs against length/Tm/GC/3'-clamp/structure constraints.
dna_molarity⧉Nucleic-acid quantity conversions: molar mass, amount (pmol/nmol), molar and mass concentration, and copy number, from mass ± volume and either a length or a sequence.
site_directed_mutagenesisDesign site-directed mutagenesis primers (QuikChange overlapping or Q5 back-to-back) for a nucleotide substitution or an amino-acid codon swap.
cross_dimerScreen two oligos for the most stable heterodimer (cross-dimer) between them.
primer_specificity⧉Self-hosted e-PCR-style screen for off-target amplicons predicted by a primer pair against a small set of curated reference genomes (currently: E. coli K-12 MG1655 — see genomesChecked for the exact list). This checks background/host-genome specificity, NOT whether the primers hit your intended target — pair it with in_silico_pcr against your own template for that. Batchable over candidate REVERSE primers against one fixed forward primer (screen many candidates against a shared partner) — not independent primer-pair batching, which this tool doesn't support.
sirna_designDesign siRNA duplexes against an mRNA target using the established Reynolds (2004) 8-criteria score and the Ui-Tei (2004) rules, plus a siDirect-style seed-duplex Tm off-target flag (≥21.5 °C). Returns ranked candidates with sense/guide oligos (with UU 3' overhangs) and, per candidate, a ready shRNA cassette (sense–loop–antisense–Pol III terminator). Heuristic sequence rules only — no RNA-folding accessibility model and no transcriptome-wide off-target search.
aso_designDesign antisense-oligonucleotide (ASO) gapmers against an mRNA target: scans candidate sites, builds the antisense oligo in the standard 5-10-5 architecture (chemically-modified wings, central DNA gap for RNase H1, phosphorothioate backbone), and screens each for known liabilities (G-quadruplex motifs, CpG immunostimulation, self-complementarity, GC extremes). No transcriptome-wide off-target search.
kasp_primer_designDesign KASP/ARMS allele-specific genotyping primers for a SNP: two allele-specific forward primers differing only at the 3' terminal base (one per allele), each with the standard KASP universal tail (FAM for allele A, HEX for allele B), a deliberate internal ARMS secondary mismatch near the 3' end whose strength complements the natural allele mismatch (strong↔weak), and one common downstream reverse primer sized to a chosen amplicon range. Reuses the site's nearest-neighbor Tm engine.

Enzymes & cloning (13)

restriction_sites⧉Find restriction enzyme recognition sites in a DNA sequence.
double_digestRecommend a single NEB buffer (and flag caveats) for digesting with two enzymes in one tube.
cloning_simulateAssemble fragments by Gibson/overlap, Golden Gate (Type IIS) or restriction–ligation, returning the product and junction primers.
plasmid_annotate⧉Auto-detect common cloning features (promoters, tags, origins, resistance markers, MCS, primers) on both strands.
construct_qc⧉Lint a coding DNA sequence for premature stops, internal RBS/polyA motifs, unwanted restriction sites, GC extremes and repeats.
construct_autofixIteratively substitutes synonymous codons to resolve unwanted restriction sites (domestication for Golden Gate), homopolymers, tandem repeats, predicted secondary structure, cryptic RBS/polyA motifs and hidden alternate-frame ORFs that construct_qc flags — without changing the encoded protein (verified). Does NOT touch premature stops or GC extremes; re-run construct_qc afterward to confirm. A native TypeScript alternative to a constraint-solver sidecar.
virtual_gel⧉Predict restriction-digest fragment sizes and their gel migration positions against a chosen DNA ladder.
plasmid_identifyScreen a query plasmid against a small curated set of common backbones (cloning vectors, expression vectors, BACs — see referencesChecked for the exact list) to identify which one(s) it resembles, separate an unmatched region (normal — your own insert) from a POSSIBLE CHIMERA (a region matching a different known backbone than its neighbor), and report per-match %identity/%coverage. NOT a search against Addgene's ~100k-plasmid catalog or PlasmidScope's 850k+ — a curated-set screen only.
plasmid_full_report⧉One combined view of 'what is this plasmid': recognized common features (from plasmid_annotate), backbone identity / possible chimera (from plasmid_identify), and — the two crossed together — any region that neither a curated backbone nor a recognized common feature explains. That last list is a triage signal (an unusual insert, an unannotated part, or worth a closer look), not a defect finding: a real gene-of-interest legitimately has no curated-feature match.
plasmid_deep_annotateAnnotate a plasmid against pLannotate's open-source feature library — a much larger signature set (GenoLIB parts + Swiss-Prot + FPbase + Rfam, cross-referenced against ~195k Addgene-deposited plasmids) than plasmid_annotate's built-in curated list, and it reports partial/low-identity hits rather than only exact signature matches. Each feature carries its percent identity, reference coverage and a fragment flag so you can judge a weak hit. Runs a multi-second search on a shared service and is therefore rate limited (see 429/503); use plasmid_annotate for an instant, unmetered first pass.
verify_constructRe-derive a construct's insert from the PCR (template + primers) claimed to have produced it, then check — independently of that claim — whether the expected insert actually appears (either orientation) in the claimed final construct, at what identity, and with exact mismatch positions if not. Optionally also checks for a premature stop in a declared reading frame. This re-derives from the claim's own stated inputs; it does not review the claim's prose.
verify_assemblyDeterministic self-check: given the same method/parts cloning_simulate would use (restriction-ligation, Gibson, or Golden Gate — optionally deriving a part by in-silico PCR first), re-derive the expected WHOLE product and diff it against a claimed final sequence. Returns pass/fail plus the exact position and nature of any discrepancy — not an opinion, the same deterministic simulation SeqBench already runs, run a second time as a check. See verify_construct for a narrower, insert-only check that doesn't require declaring the vector/enzymes/method.
golden_gate_fidelityScore a candidate set of 4-base Golden Gate/MoClo junction overhangs against real published T4-ligase ligation-count data: per-overhang specificity, the weakest link in the set, and any risky cross-reacting pairs. Optionally compare against a named published overhang set. This is SeqBench's own transparent scoring methodology — it does not reproduce NEB's/Potapov's own published aggregate fidelity percentages for named sets (their exact formula isn't disclosed anywhere accessible).

Proteins & peptides (6)

protein_properties⧉Protein properties: molecular weight, isoelectric point, GRAVY, extinction coefficient and composition.
protein_hydrophobicity⧉Sliding-window hydropathy/hydrophobicity profile (ProtScale-style) over a published amino-acid scale.
protease_digestion⧉In-silico protease/chemical digestion: cleave a protein and report each peptide's position, length and neutral mass.
protein_annotate_submitSubmit a protein sequence to EBI InterProScan for domain architecture, family and GO-term annotation. Returns a jobId immediately — the job itself takes minutes; poll it with protein_annotate_poll.
protein_annotate_pollCheck an InterProScan job submitted via protein_annotate_submit. Returns {status, ready:false} while still running; once FINISHED, also returns the parsed domain architecture, per-match details and deduplicated GO terms.
alphafold_lookupLook up a UniProt accession in the AlphaFold Protein Structure Database (CC-BY 4.0). Returns confidence, model version and structure file URLs, or {found:false} when no prediction exists for that accession.

Codon usage (2)

codon_optimize⧉Codon-optimise a protein (or coding DNA) for an expression host by picking the most-frequent codon per residue.
codon_adaptation_index⧉Codon Adaptation Index (CAI) and per-codon relative adaptiveness of a CDS against an expression host, with rare-codon and GC3 analysis.

Alignment & variants (5)

pairwise_alignmentGlobal (Needleman-Wunsch) or local (Smith-Waterman) pairwise alignment of two sequences with match/mismatch/gap scoring.
multiple_sequence_alignmentCenter-star multiple sequence alignment of a multi-FASTA input, with consensus and per-column conservation.
variant_comparatorAlign a query to a reference and call variants (substitutions, insertions, deletions) in HGVS g. notation, with optional coding effects.
hgvs_convertParse an HGVS "c." variant description (by gene symbol, RefSeq NM_, or Ensembl ENST accession), convert it to genomic (g.) coordinates via a real, live-fetched Ensembl exon/CDS map (transcripts resolved through the bundled MANE RefSeq<->Ensembl crosswalk), apply 3'-rule normalization to any del/dup/ins, and predict the protein (p.) effect where that is safely computable. Refuses cleanly — rather than guessing — for circular/mitochondrial genomes, RNA-level or protein-level input, uncertain/mosaic syntax, splice-junction-adjacent or inversion protein effects, and non-MANE/non-Ensembl transcripts.
variant_annotate⧉One-box variant lookup against MyVariant.info: accepts an rsID, chrom:pos:ref:alt, genomic HGVS ("chr17:g.7676154G>C"), or transcript HGVS c. ("NM_000546.6:c.215C>G" / "TP53:c.215C>G", bridged via the hgvs_convert tool). Returns a ClinVar significance summary, gnomAD exome/genome allele frequencies, and CADD/SIFT/PolyPhen2/REVEL pathogenicity predictor scores — each section explicitly null when that source has no data, never silently omitted. See the result's own "caveats" for real data-freshness limits (frozen gnomAD/CADD snapshots, periodic ClinVar snapshot).

CRISPR (6)

crispr_grna_design⧉Find and score candidate guide RNAs (protospacer + PAM) in a target DNA for common nucleases (SpCas9, SpCas9-NG, SaCas9, Cas12a).
crispr_offtarget_checkScreen a guide's protospacer for off-target sites (protospacer match + valid PAM, both strands) against a small curated set of common lab reference genomes (see genomesChecked) — NOT a whole human/mouse genome search. Use this the same way primer_specificity is used: a useful sanity check within the covered organisms, not a clearance guarantee for a mammalian expression host.
crispr_hdr_donorBuild an HDR donor (homology arms flanking an edit) from a target sequence and either an explicit edit window (editStart/editEnd) or a guide's cut site (guideStart/guideEnd/guideStrand/nuclease — SpCas9-family only; Cas12a's staggered cut needs an explicit editStart/editEnd). Also designs genotyping primers spanning the edit site on the original sequence (a real size-shift or sequencing target to confirm the edit), reusing the same primer-design engine as primer_design.
prime_editing_designDesign SpCas9 prime-editing pegRNAs for a substitution, insertion, deletion, or small replacement: for each usable NGG PAM it builds the spacer, a primer-binding-site (PBS) length sweep targeting a ~30 C melting temperature, the reverse-transcriptase template (RTT) that encodes the edit, and the full 3' extension, plus PE3 nicking-sgRNA suggestions 40-90 bp away on the opposite strand. Designs where the edit destroys the pegRNA's own PAM (preventing re-nicking of the edited allele) are ranked first. Off-target activity is not evaluated (no in-browser reference genome).
prime_editing_twin_designDesign a twinPE pegRNA pair (Anzalone et al. 2022) for a replacement too large for a single pegRNA's RTT: a left pegRNA nicks the + strand at/before the replacement window and a right pegRNA nicks the - strand at/after it, each synthesizing a new 3' flap; both flaps are truncated at a shared overlap in the middle of the new sequence so they anneal and resolve the edit without an HDR donor. Off-target activity is not evaluated (no in-browser reference genome).
base_editing_designDesign cytosine (CBE, C→T) or adenine (ABE, A→G) base-editing gRNAs for an SpCas9 target: for each NGG gRNA it reports every editable base inside the editor's activity window, flags bystander edits (more than one editable base in the window), and — with a CDS reading frame — classifies each edit's amino-acid consequence (silent / missense / nonsense / stop-loss). Bystander-free guides are ranked first. Handles both strands (a C→T on the protospacer of a reverse-strand guide is reported as the forward-strand G→A).

Files & formats (13)

parse_genbankParse a GenBank flat file into its locus, definition, features and sequence.
sequence_format_convertConvert between FASTA and GenBank (whole sequence, CDS or protein), or export to TSV.
seqfile_statsStatistics for a FASTA or FASTQ file: count, length distribution, N50, GC content and (FASTQ) mean quality.
parse_sanger_traceDecode a Sanger ABIF (.ab1 / .abi) chromatogram: base calls, per-base quality, the four dye-channel traces and peak locations.
sanger_vs_reference⧉Align a Sanger ABIF read to a reference and report identity plus every mismatch, insertion and deletion.
sequence_fetchFetch a public DNA/protein record by accession from NCBI Nucleotide, NCBI Protein, UniProt, or Ensembl (e.g. NM_000546, NP_000537, P04637, ENSG00000141510). Only the accession is sent upstream. Use sequence_search first if you only know a gene/organism name, not an accession. For an Ensembl transcript ID this returns spliced cDNA; for a gene ID it returns the full genomic locus (introns included) — Ensembl's own default for each ID type.
sequence_searchResolve a gene/organism name — or a raw NCBI search term — to candidate accessions, instead of guessing one. Returns up to maxResults hits (accession, title, organism); pass the accession you want to sequence_fetch.
sequencing_readback_verifyAlign raw Sanger or NGS reads (FASTA or FASTQ) back onto a claimed reference sequence using minimap2, and report per-read mapping identity plus exact variant positions (substitutions/insertions/deletions), with a consensus view across reads and a corrected consensus sequence (the reference with every consensus-supported edit applied). Complements verify_construct/verify_assembly: those re-derive what a design SHOULD produce from its own stated inputs; this checks what a real sequencer actually read back.
fastq_qc_reportFastQC-style deep quality-control report for a FASTQ file: per-base quality and content, GC and length distributions, sequence duplication levels, overrepresented sequences, and adapter content — each with a warn/fail verdict against FastQC's own published thresholds.
fastq_trimTrim FASTQ reads: an ungapped sliding-suffix adapter match (against the same named Illumina adapters as the QC report) followed by a BWA-style 3' quality trim (the same algorithm Cutadapt's own -q option reuses), then drops reads below a minimum length. Returns the trimmed FASTQ plus before/after read-count, mean-length and mean-quality stats.
export_plate_layoutAssign a set of PCR reactions (name + forward/reverse primer + optional template label) to wells on a 96-well plate, row-major (A1, A2, … A12, then B1, B2, … up to H12). Returns the well-assignment data for rendering a plate diagram; export_opentrons_protocol and export_echo_picklist build their downloadable files from this exact same layout, so all three always agree.
export_opentrons_protocolGenerate a downloadable Opentrons Python Protocol API (v2, OT-2) script that sets up the given PCR reactions on a 96-well PCR plate, at the same well positions export_plate_layout assigns. Uses real Opentrons labware/pipette API names confirmed against docs.opentrons.com and the Opentrons shared-data labware-definitions repository (opentrons_96_wellplate_200ul_pcr_full_skirt, opentrons_96_tiprack_20ul, opentrons_24_tuberack_nest_1.5ml_snapcap, nest_12_reservoir_15ml, p20_single_gen2) and the confirmed load_labware/load_instrument/transfer method signatures. Master-mix/primer/template/water volumes are clearly-labeled placeholder constants at the top of the script — this is a starting point to review and adapt for your own enzyme and instrument, not a certified ready-to-run protocol.
export_echo_picklistGenerate a downloadable Beckman/Labcyte Echo acoustic-liquid-handler picklist CSV (columns: Source Plate Name, Source Plate Type, Source Well, Destination Plate Name, Destination Well, Transfer Volume, Name — the header row reproduced from PyEcho, a real open-source Echo-picklist generator) for the given PCR reactions, at the same well positions export_plate_layout assigns. Assumes a 5 uL Echo-scale PCR reaction (master mix 2500 nL, each primer 250 nL, template 250 nL, water 1750 nL) — a commonly used acoustic-dispensing miniaturization scale, not a universal standard; rescale the volumes for your own protocol. Source/Destination Plate Type uses a placeholder Echo plate-type code (384PP_AQ_BP) — replace with the exact type from your own Echo Plate Type Library.

Analysis (18)

characterize_sequence⧉One-paste 'tell me everything': auto-detects DNA/RNA/protein, then reports composition, ORFs, single-cutter enzymes, end primers or protein properties, plus a BLAST link.
sequence_report⧉One-click DNA analysis: composition, ORFs, restriction-enzyme scan (single cutters) and end-primer Tm composed into a single report with a copyable text block.
session_createStart a scratch session that holds several named sequences/values (e.g. vector, insert, forward/reverse primer) for use across multiple tool calls via session_run, instead of re-pasting them into every call. Sessions expire after 24 hours.
session_getFetch named entries from a session. Prefer session_run for actually USING the values — it keeps raw sequences out of your context. Use this mainly to inspect or debug what a session currently holds.
session_setAdd or overwrite named entries in an existing session.
session_runRun any SeqBench tool, resolving selected arguments from a session's named entries instead of pasting them inline, and optionally store selected result fields back into the session by name. This is the main way to chain a multi-part design (vector + insert + primers) across calls without shuttling raw sequences through your own context.
save_permalinkRun a registered tool and save its (arguments, result) pair under a short permanent code that anyone with the link can view read-only (/permalink/{code}). Use this to cite or share a specific result (e.g. a verify_construct or verify_assembly check) rather than re-pasting it.
web_searchSearch the live web (via Tavily) for information not covered by SeqBench's own tools — recent literature, protocols, vendor/reagent info, general facts. Returns a short synthesized answer (if available) plus ranked source snippets with URLs. This does not run any bioinformatics calculation itself; use the dedicated tools for that.
id_map_submitSubmit up to 1000 ids to UniProt's ID mapping service for a single confirmed-safe hop (e.g. Gene_Name -> UniProtKB-Swiss-Prot, or UniProtKB_AC-ID -> Ensembl/GeneID/RefSeq_Protein/Gene_Name). Returns a jobId immediately — poll it with id_map_poll.
id_map_pollCheck a UniProt id-mapping job submitted via id_map_submit. Returns {status, ready:false} while still running; once FINISHED, also returns the mapped ids (normalized regardless of which target database was requested) and any ids that failed to map.
ortholog_mapLook up the orthologous (or paralogous) gene for up to 50 gene symbols in a target species, via Ensembl's homology-by-symbol REST endpoint. Symbols with no homology record are reported in `unmapped`, never silently dropped.
volcano_plot_dataValidate a differential-expression table (gene, log2 fold-change, p-value/FDR) and compute -log10(p) plus up/down/non-significant counts at conventional default thresholds (|log2FC|>=1, p<=0.05), for the Volcano Plot visualization. Invalid rows (non-finite log2FC, or p-value outside (0,1]) are dropped and reported rather than failing the whole batch.
expression_heatmap_clusterHierarchically cluster a genes x samples expression matrix (UPGMA/average, complete, or single linkage; Euclidean or correlation distance) and return the row/column leaf order, dendrogram merge trees, and row-z-scored values for the Clustered Expression Heatmap visualization.
functional_enrichmentOver-representation analysis: test which GO terms (biological process / molecular function / cellular component) and Reactome pathways are statistically enriched in a query gene list versus a background, using the hypergeometric test with Benjamini-Hochberg FDR correction across all tested terms. Uses bundled GO Consortium + Reactome reference data (human only). KEGG is not included (its license does not permit bundling gene sets).
gene_modelThe real exon/UTR/CDS structure of a human gene's canonical transcript, fetched live from Ensembl (the same exon/CDS map the HGVS Converter tool uses) — for rendering an exon diagram.
gene_dossierA gene/drug-target dossier fanned out to five independent sources in one call: Open Targets (function, tractability, top associated diseases), an NCBI/UniProt plain-English function summary, ChEMBL (known drugs and their mechanism/clinical phase, cross-referenced with indications), ClinicalTrials.gov (trials by gene/condition term), and Europe PMC (top cited papers). Each source fails independently — a down source returns null/empty for its own section rather than failing the whole call, and every failure is listed in "sourceErrors" rather than silently omitted.
gene_expressionA gene's tissue-expression fingerprint: per-tissue median TPM from GTEx (v8) and subcellular localization / RNA tissue-specificity / protein class from the Human Protein Atlas, in one call.
rna_foldPredict an RNA secondary structure by minimum free energy (MFE) using a Zuker dynamic program with Turner 1999 nearest-neighbor stacking energies (no pseudoknots). Returns the dot-bracket structure, the estimated MFE (kcal/mol), and the list of base pairs. A from-scratch, in-browser implementation (there is no usable browser ViennaRNA); the simplified loop energy model makes the MFE a good comparative estimate, not a lab-grade absolute.

⧉ = batchable (usable in /api/v1/batch and workflow pipelines). API version 1.1.0. Results are for research/educational use; verify critical results against an authoritative source.

Frequently asked questions

How do I connect to SeqBench from an agent or script?

Use the Streamable-HTTP MCP endpoint for agent clients, or call the JSON REST API directly from scripts, notebooks and workflow engines.

Which clients and agents can connect?

Any MCP client that speaks Streamable HTTP — Claude Code, Claude Desktop, Cursor and others. A stdio-only client can bridge to the URL with `npx mcp-remote`. For scripts, call the REST API from any language.

What is the difference between the MCP server and the REST API?

They expose the same tools. The MCP server lets an AI agent discover and call them inside a conversation; the REST API (POST /api/v1/<tool>) is a plain JSON endpoint for scripts, notebooks and pipelines.

Are the results deterministic and read-only?

Yes. Every tool is a pure function of its input: nothing is stored, written or persisted, and the same input always returns the same result (aside from tools that explicitly generate random sequences).

Can I process a whole FASTA file at once?

Yes. POST /api/v1/batch runs one tool over every record in a multi-FASTA, and POST /api/v1/workflow runs a multi-tool pipeline over each record. Both are also exposed as MCP tools.

What should I verify before using results operationally?

SeqBench results are designed for research and educational workflows. Verify critical experimental decisions against primary literature, vendor calculators or authoritative databases.