Encode Toolkit vs Notch — MCP Server Comparison | AllMCPs
Encode Toolkit vs Notch
A side-by-side look at the Encode Toolkit and Notch 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, medicine and bioinformatics work as a local process; choose Notch for multimedia process 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, Medicine and 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.
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.
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 is categorized under Biology, Medicine and Bioinformatics and uses a local stdio subprocess. Notch belongs to Multimedia Process and uses a remote HTTP/SSE transport. Pick Encode Toolkit for biology, medicine and bioinformatics work and Notch for multimedia process.
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. Notch has no declared pricing — check the project's own site. 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 notch 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. Notch has 45/100 (Fair) with 26 views, 12 installs and 0 GitHub stars.
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.
Choose Encode Toolkit when