Encode Toolkit vs Folklore Clinical Variant Interpretation MCP
A side-by-side look at the Encode Toolkit and Folklore Clinical Variant Interpretation MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Encode Toolkit for biology & bioinformatics work as a local process; choose Folklore Clinical Variant Interpretation MCP for biology & bioinformatics over a hosted endpoint. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Encode Toolkit when
- You need dedicated capabilities in the Biology & Bioinformatics domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: No auth required.
- You want tools like
encode_search_experiments, encode_get_experiment, encode_list_files.
Choose Folklore Clinical Variant Interpretation MCP when
- You need dedicated capabilities in the Biology & Bioinformatics domain.
- You prefer a remote HTTP/SSE transport.
- Its auth model fits you: No auth required.
- You want tools like
search_variant_evidence, search_variant_literature, get_publication_details.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Biology & Bioinformatics | Biology & Bioinformatics |
| Quality signal | 61/100 · Good | 79/100 · Great |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Remote HTTP/SSE |
| Auth | No auth required | No auth required |
| Pricing | Free | Free |
| Required env vars | None listed | None listed |
| Verified owner | Community listing | Verified |
| GitHub stars | 21 | 1 |
| Directory activity | 3 views 0 installs 0 upvotes | 5 views 0 installs 0 upvotes |
| Tools | 20 | 7 |
| Full listing | View Encode Toolkit | View Folklore Clinical Variant Interpretation MCP |
Tools & capabilities
Encode Toolkit tools 20
encode_search_experimentsSearch ENCODE experiments with comprehensive filters. Examples: - Find all Histone ChIP-seq on human pancreas tissue: assay_title="Histone ChIP-seq", organ="pancreas", biosample_type="tissue" - Find ATAC-seq on human brain: assay_title="ATAC-seq", organ="brain" - Find RNA-seq on GM12878 cell line: assay_title="total RNA-seq", biosample_term_name="GM12878" - Find ChIP-seq targeting H3K27me3: assay_title="Histone ChIP-seq", target="H3K27me3" - Find all mouse liver experiments: organism="Mus musculus", organ="liver" - Free text search: search_term="CRISPR screen pancreatic" Common assay_title values: "Histone ChIP-seq", "TF ChIP-seq", "ATAC-seq", "DNase-seq", "total RNA-seq", "polyA plus RNA-seq", "WGBS", "intact Hi-C", "CUT&RUN", "CUT&Tag", "STARR-seq", "MPRA", "eCLIP", "CRISPR screen" Common organ values: "pancreas", "liver", "brain", "heart", "kidney", "lung", "intestine", "skin of body", "blood", "spleen", "thymus" biosample_type values: "tissue", "cell line", "primary cell", "in vitro differentiated cells", "organoid" WHEN TO USE: Use as the primary entry point when users want to find experiments. Start with encode_get_facets if unsure what filters to use. RELATED TOOLS: encode_get_facets, encode_get_metadata, encode_search_files Args: assay_title: Assay type (e.g., "Histone ChIP-seq", "ATAC-seq", "total RNA-seq") organism: Species (default: "Homo sapiens"). Also: "Mus musculus" organ: Organ/tissue system (e.g., "pancreas", "brain", "liver") biosample_type: Sample classification ("tissue", "cell line", "primary cell", "organoid") biosample_term_name: Specific cell/tissue name (e.g., "GM12878", "HepG2", "pancreas") target: ChIP/CUT&RUN target (e.g., "H3K27me3", "CTCF", "p300") status: Data status (default: "released"). Also: "archived", "revoked" lab: Submitting lab name award: Funding project assembly: Genome assembly (e.g., "GRCh38", "mm10") replication_type: "isogenic", "anisogenic", or "unreplicated" life_stage: "embryonic", "postnatal", "child", "adult" sex: "male", "female", "mixed" treatment: Treatment name if perturbation experiment genetic_modification: Modification type ("CRISPR", "RNAi") perturbed: True for perturbation experiments only search_term: Free text search across all fields date_released_from: Start date (YYYY-MM-DD) for date range filter date_released_to: End date (YYYY-MM-DD) for date range filter limit: Max results to return (default 25, use larger for comprehensive searches) offset: Skip first N results (for pagination) Returns: JSON with experiment results, total count, and pagination info.encode_get_experimentGet full details for a specific ENCODE experiment by accession ID. Returns the experiment's metadata, all associated files, the accessions of its possible controls, replicate counts, and the number of audit flags at each level (ERROR, NOT_COMPLIANT, WARNING, INTERNAL_ACTION). It does not return QC metric values such as FRiP or NSC; those are on the experiment's page at encodeproject.org. WHEN TO USE: Use when you have a specific accession and need full details including files, controls, and audit counts. RELATED TOOLS: encode_list_files, encode_track_experiment, encode_compare_experiments Args: accession: ENCODE experiment accession (e.g., "ENCSR133RZO", "ENCSR000AKS") Returns: JSON with full experiment details and file listing.encode_list_filesList all files for a specific ENCODE experiment, with optional filters. Examples: - All BED files: experiment_accession="ENCSR133RZO", file_format="bed" - FASTQs only: experiment_accession="ENCSR133RZO", file_format="fastq" - Signal tracks: experiment_accession="ENCSR133RZO", output_category="signal" - Default/recommended files: preferred_default=True - Peaks from GRCh38: file_format="bed", output_type="IDR thresholded peaks", assembly="GRCh38" Common file_format values: "fastq", "bam", "bed", "bigWig", "bigBed", "tsv", "hic" Common output_type values: "reads", "alignments", "signal of unique reads", "signal of all reads", "fold change over control", "IDR thresholded peaks", "pseudoreplicated peaks", "replicated peaks", "gene quantifications", "transcript quantifications", "contact matrix" WHEN TO USE: Use to browse files within a known experiment. Use encode_search_files instead to find files across experiments. RELATED TOOLS: encode_search_files, encode_get_file_info, encode_download_files Args: experiment_accession: ENCODE experiment accession (e.g., "ENCSR133RZO") file_format: Filter by format ("fastq", "bam", "bed", "bigWig", "bigBed", etc.) file_type: Filter by specific type ("bed narrowPeak", "bed broadPeak", etc.) output_type: Filter by output type ("reads", "peaks", "signal", etc.) output_category: Filter by category ("raw data", "alignment", "signal", "annotation") assembly: Filter by genome assembly ("GRCh38", "hg19", "mm10") status: Filter by status ("released", "archived", "in progress") preferred_default: If True, return only default/recommended files limit: Max files to return (default 200) Returns: JSON list of files with accession, format, size, download URL, and metadata.encode_search_filesSearch files across ALL experiments with combined experiment + file filters. This is powerful for finding specific file types across many experiments. Examples: - All BED files from human pancreas ChIP-seq: file_format="bed", assay_title="Histone ChIP-seq", organ="pancreas" - FASTQs from mouse liver RNA-seq: file_format="fastq", assay_title="total RNA-seq", organ="liver", organism="Mus musculus" - All IDR peak files for H3K27me3: output_type="IDR thresholded peaks", target="H3K27me3" - BigWig signal tracks from ATAC-seq on brain tissue: file_format="bigWig", assay_title="ATAC-seq", organ="brain", biosample_type="tissue" WHEN TO USE: Use to find specific file types across ALL experiments. More powerful than encode_list_files for cross-experiment file discovery. RELATED TOOLS: encode_list_files, encode_batch_download, encode_get_file_info Args: file_format: File format ("fastq", "bam", "bed", "bigWig", etc.) file_type: Specific file type ("bed narrowPeak", "bed broadPeak", etc.) output_type: Output type ("reads", "peaks", "signal", etc.) output_category: Output category ("raw data", "alignment", "signal", "annotation") assembly: Genome assembly ("GRCh38", "hg19", "mm10") assay_title: Filter by assay type of parent experiment organism: Filter by organism of parent experiment organ: Filter by organ of parent experiment biosample_type: Filter by biosample type ("tissue", "cell line", etc.) target: Filter by ChIP/CUT&RUN target status: File status (default: "released") preferred_default: If True, only default/recommended files search_term: Free text search limit: Max results (default 25) offset: Skip first N results (pagination) Returns: JSON with file results, total count, and pagination info.encode_download_filesDownload specific ENCODE files by accession to a local directory. Downloads files from ENCODE to your local machine. Supports MD5 verification, concurrent downloads, and skip-if-already-downloaded. WHEN TO USE: Use for downloading specific files by accession. For bulk downloads, prefer encode_batch_download. RELATED TOOLS: encode_batch_download, encode_search_files, encode_log_derived_file Args: file_accessions: List of file accessions to download (e.g., ["ENCFF635JIA", "ENCFF388RZD"]) download_dir: Local directory path to save files (e.g., "./data/encode") organize_by: How to organize downloaded files: - "flat": All files in download_dir (default) - "experiment": download_dir/ENCSR.../filename - "format": download_dir/bed/filename - "experiment_format": download_dir/ENCSR.../bed/filename verify_md5: Verify file integrity with MD5 checksum (default True) Returns: JSON with download results for each file (path, size, success/error, MD5 status).encode_get_metadataGet available filter values for ENCODE searches. Use this to discover valid values for search parameters. WHEN TO USE: Use to discover valid filter values before searching. Helps prevent typos in assay_title, organ, biosample_type etc. RELATED TOOLS: encode_get_facets, encode_search_experiments Args: metadata_type: Type of metadata to retrieve. Options: - "assays": Available assay types (Histone ChIP-seq, ATAC-seq, total RNA-seq, etc.) - "organisms": Available organisms (Homo sapiens, Mus musculus, etc.) - "organs": Available organ/tissue systems (pancreas, brain, liver, etc.) - "biosample_types": Biosample classifications (tissue, cell line, primary cell, etc.) - "file_formats": File format types (fastq, bam, bed, bigWig, etc.) - "output_types": Output data types (reads, peaks, signal, etc.) - "output_categories": Output categories (raw data, alignment, signal, etc.) - "assemblies": Genome assemblies (GRCh38, hg19, mm10, etc.) - "life_stages": Life stages (embryonic, adult, child, etc.) - "replication_types": Replication types (isogenic, anisogenic, unreplicated) - "statuses": Experiment statuses (released, archived, etc.) - "file_statuses": File statuses (released, archived, in progress, etc.) Returns: JSON list of valid values for the specified metadata type.encode_batch_downloadSearch for files and download them all in batch. First searches for files matching the criteria, then downloads them. By default runs in dry_run mode to preview what would be downloaded. Set dry_run=False to actually download. WHEN TO USE: Use for searching and downloading files in one step. Always use dry_run=True first to preview. For specific file accessions, use encode_download_files. RELATED TOOLS: encode_download_files, encode_search_files Examples: - Download all BED files from human pancreas ChIP-seq: file_format="bed", assay_title="Histone ChIP-seq", organ="pancreas", download_dir="/data/encode", dry_run=False - Preview FASTQ downloads for mouse brain RNA-seq: file_format="fastq", assay_title="total RNA-seq", organ="brain", organism="Mus musculus", download_dir="/data/encode" - Download IDR peaks for H3K27me3 in GRCh38: output_type="IDR thresholded peaks", target="H3K27me3", assembly="GRCh38", download_dir="/data/encode", dry_run=False Args: download_dir: Local directory to save files file_format: File format filter ("fastq", "bam", "bed", "bigWig", etc.) output_type: Output type filter ("reads", "peaks", "signal", etc.) output_category: Output category ("raw data", "alignment", "annotation", etc.) assembly: Genome assembly ("GRCh38", "mm10", etc.) assay_title: Assay type ("Histone ChIP-seq", "ATAC-seq", "total RNA-seq", etc.) organism: Organism (default: "Homo sapiens") organ: Organ/tissue ("pancreas", "brain", "liver", etc.) biosample_type: Biosample type ("tissue", "cell line", "primary cell", etc.) target: ChIP/CUT&RUN target ("H3K27me3", "CTCF", etc.) preferred_default: If True, only download default/recommended files organize_by: File organization ("flat", "experiment", "format", "experiment_format") verify_md5: Verify downloads with MD5 checksums (default True) limit: Max files to download (default 100, safety limit) dry_run: If True (default), only preview what would be downloaded. Set False to download. offset: Skip the first N matching files; pass the next_offset of the previous reply to continue a search that has more files than limit Returns: JSON with download preview (dry_run=True) or download results (dry_run=False).encode_manage_credentialsManage ENCODE API credentials for accessing restricted/unreleased data. Most ENCODE data is public and requires no authentication. Credentials are only needed for unreleased or restricted datasets. Credentials are stored securely in your OS keyring (macOS Keychain, Linux Secret Service, Windows Credential Locker) and never in plaintext. WHEN TO USE: Use only for accessing unreleased/restricted ENCODE data. Public data requires no authentication. RELATED TOOLS: encode_search_experiments Args: action: What to do: - "store": Save new credentials (requires access_key and secret_key) - "check": Check if credentials are configured - "clear": Remove stored credentials access_key: Your ENCODE access key (only for action="store") secret_key: Your ENCODE secret key (only for action="store") Returns: JSON with action result.encode_get_facetsGet live filter counts from ENCODE to discover what data is available. Returns faceted counts showing how many experiments/files exist for each filter value. Useful for exploring what's available before searching. WHEN TO USE: Use to explore what data exists before searching. Shows counts per filter value. Best first step for unknown datasets. RELATED TOOLS: encode_get_metadata, encode_search_experiments Examples: - What assays are available for pancreas? organ="pancreas" - What organs have Histone ChIP-seq data? assay_title="Histone ChIP-seq" - What targets are available for mouse brain ChIP-seq? assay_title="Histone ChIP-seq", organism="Mus musculus", organ="brain" Args: search_type: Object type ("Experiment" or "File") assay_title: Pre-filter by assay type organism: Pre-filter by organism organ: Pre-filter by organ biosample_type: Pre-filter by biosample type Returns: JSON with facet names and their term counts.encode_get_file_infoGet detailed information about a specific ENCODE file. WHEN TO USE: Use when you need detailed metadata for a specific file (size, md5, assembly, biological replicate info). RELATED TOOLS: encode_download_files, encode_list_files Args: accession: File accession ID (e.g., "ENCFF635JIA") Returns: JSON with file metadata including format, size, download URL, MD5, assembly, etc.encode_track_experimentTrack an ENCODE experiment locally with its publications, methods, and pipeline info. Fetches full experiment metadata from ENCODE and stores it in a local SQLite database along with any associated publications (PMIDs, DOIs, authors, journal) and pipeline/analysis information (software versions, methods). This is like adding an experiment to your "library" - similar to Endnote for papers. WHEN TO USE: Use to save an experiment to your local library with publications and pipeline info. Required before compare or citations. RELATED TOOLS: encode_compare_experiments, encode_get_citations, encode_export_data Args: accession: ENCODE experiment accession (e.g., "ENCSR133RZO") fetch_publications: Also fetch and store publications/citations (default True) fetch_pipelines: Also fetch and store pipeline/analysis info (default True) notes: Optional notes to attach to this experiment Returns: JSON with tracking result including publications and pipeline info found.encode_list_trackedList all experiments you've tracked locally, with optional filters. Shows your local library of tracked ENCODE experiments, their metadata, publication counts, and derived file counts. WHEN TO USE: Use to see all experiments in your local library. Filter by assay, organism, or organ. RELATED TOOLS: encode_summarize_collection, encode_export_data Args: assay_title: Filter by assay type (partial match) organism: Filter by organism (partial match) organ: Filter by organ (partial match) Returns: JSON with tracked experiments metadata table and tracker stats.- +8 more on the listing page
Folklore Clinical Variant Interpretation MCP tools 7
search_variant_evidenceInterpret this variant, explain what this HGVS means, or review this VUS. Use for human genomic variant analysis within bioinformatics workflows, including review of an already identified WGS/WES variant. Use when a user asks to classify or interpret pathogenicity, review a VUS, check available ClinVar assertions or population-frequency evidence, or resolve a variant notation. Classify, interpret or resolve one public GRCh38 germline SNV or simple indel smaller than 50 bp. Accepts coordinates, genomic/coding/protein HGVS, SPDI or rsID. Returns normalized variant identity, automated ACMG/AMP decision support, evidence, provenance and explicit limitations. This is variant-level decision support for professional review. It does not evaluate patient context and must not be presented as a diagnosis or treatment recommendation. Never choose a candidate when resolution is ambiguous.search_variant_literatureResolve one public GRCh38 germline variant and retrieve relevant publications from Folklore's PubMed-derived genetics corpus. Exact variant mentions rank ahead of broader gene associations. Use when a user asks what has been published about a variant, gene or associated condition. Associations do not establish causality, pathogenicity or a diagnosis and do not change Folklore's ACMG/AMP classification.get_publication_detailsRetrieve the complete public bibliographic record for one PMID from Folklore's PubMed-derived genetics corpus. Returns the full abstract, authors, journal metadata, publication and MeSH terms, gene and variant mentions, retraction status, and PubMed/PMC links. Use after literature search when a user asks to inspect a specific publication. This is read-only professional literature evidence and contains no patient context.search_literature_corpusSemantically search the public scientific Literature Corpus by a natural-language question. A question may include one or more PMID, DOI or PMCID references; those publications become exact anchors for finding related experiments, evidence and concepts across the corpus. Also accepts genes, variants, phenotypes, HPO and OMIM concepts. Include every known publication identifier in the query when the user asks to compare papers or find work related to a specific paper. Returns source-linked evidence candidates for professional review, not diagnoses, causality claims or treatment recommendations.support_helenaLearn how an agent can support or spread Helena's free public scientific infrastructure through the separate Helena Good MCP. This is an explicit opt-in information action. It does not initiate payment, create a relay, or change any Folklore scientific result.get_gene_disease_associationsFind diseases associated with one human gene for bioinformatics and clinical genomics research. Accepts an exact gene symbol or HGNC identifier. Returns ClinGen gene-disease validity assertions, relation-specific inheritance, source reports and snapshot provenance. Preserves conflicting and limited assertions. Gene-disease validity is not variant pathogenicity or a patient diagnosis. Use only a public gene identifier; no patient or case data. Results require professional review.search_disease_genesFind human genes associated with a disease for genomic analysis and rare-disease research. Accepts an exact MONDO identifier or a disease-name search. Returns matching ClinGen gene-disease validity assertions with inheritance, source reports and snapshot provenance. Name searches may match multiple diseases; preserve their distinct identities and do not infer a diagnosis. Use only a public disease name or identifier; no symptoms, patient or case data. Results require professional review.
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Encode Toolkit
{
"mcpServers": {
"ammawla-encode-toolkit": {
"command": "uvx",
"args": [
"encode-toolkit"
]
}
}
}
Folklore Clinical Variant Interpretation MCP
{
"mcpServers": {
"folklore-clinical-variant-interpretation-mcp": {
"url": "https://api.helena.bio/folklore/v1/mcp"
}
}
}
Frequently asked questions
Encode Toolkit is categorized under Biology & Bioinformatics and uses a local stdio subprocess. Folklore Clinical Variant Interpretation MCP belongs to Biology & Bioinformatics and uses a remote HTTP/SSE transport. Pick Encode Toolkit for biology & bioinformatics work and Folklore Clinical Variant Interpretation MCP for biology & bioinformatics.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Encode Toolkit is listed as free. Auth: no auth required. Folklore Clinical Variant Interpretation MCP is listed as free. Auth: no auth required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add ammawla-encode-toolkit and folklore-clinical-variant-interpretation-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Encode Toolkit has a quality signal of 61/100 (Good) with 3 views, 0 installs and 21 GitHub stars. Folklore Clinical Variant Interpretation MCP has 79/100 (Great) with 5 views, 0 installs and 1 GitHub stars.