Tools observed via MCP handshake

archives_extract_all — Extract all members from an archive (.zip, .tar, .tar.gz, .tgz, .tar.bz2, .tar.xz, .gz, .7z) to a destination directory on disk. Returns the paths of extracted
archives_extract_member — Extract a single named member from an archive (.zip, .tar, .tar.gz, .tgz, .tar.bz2, .tar.xz, .gz, .7z) and return its content as text. Binary content is decoded
archives_list — List the contents of an archive file (.zip, .tar, .tar.gz, .tgz, .tar.bz2, .tar.xz, .gz, .7z). Returns a table or JSON array of members with name, size, compres
arrow_read — Read an Apache Arrow or Feather file and display a human-readable preview: schema summary and first N rows as a formatted text table.
arrow_schema — Print the schema of an Apache Arrow or Feather file: column names, Arrow types, and nullable flags.
arrow_to_csv — Convert an Apache Arrow or Feather file to CSV (one row per record; nested types JSON-serialized).
arrow_to_json — Convert an Apache Arrow or Feather file to a JSON array of objects (one object per row).
avro_sample — Return the first N records from an Avro file as a pretty-printed JSON array (default 10).
avro_schema — Extract and pretty-print the embedded writer schema from an Avro file as JSON.
avro_to_csv — Convert an Avro file to RFC 4180 CSV. Nested fields are serialised as JSON strings. Optionally limit rows or supply a reader schema for field projection.
avro_to_json — Convert an Avro file to a pretty-printed JSON array. Optionally limit rows or supply a reader schema for field projection.
avro_to_jsonl — Convert an Avro file to newline-delimited JSON (one record per line). Optionally limit rows or supply a reader schema for field projection.
dbf_schema — Print the field definitions and file header of a dBase .dbf file: version, record count, encoding, and a table of field names, types, lengths, and decimal count
dbf_to_csv — Convert a dBase .dbf file to RFC 4180 CSV text (header row of field names, one data row per record).
dbf_to_json — Convert a dBase .dbf file to a JSON array of objects (one object per record, keyed by field name; dates as ISO-8601 strings).
dbf_to_text — Read a dBase .dbf file and return a human-readable text summary: header info, field schema, and record values.
doc_to_csv — Extract text from a legacy Word .doc file and return it as CSV (columns: paragraph_index, text; UTF-8, LF line endings).
doc_to_json — Extract text and OLE metadata from a legacy Word .doc file. Returns a JSON object: {"paragraphs": [...], "metadata": {...}} with author, title, and timestamps w
doc_to_text — Extract text from a legacy Word .doc (OLE/CFB binary) file and return it as plain text, one paragraph per line.
eml_extract_attachments — Extract attachment files from an EML to a destination directory and return a summary of the saved paths.
eml_read — Read an EML (RFC 822) email file and return decoded body text with a header summary (From, To, Subject, Date) and an attachment list.
eml_to_csv — Parse an EML file and return a CSV row with key header fields (from, to, cc, subject, date, message_id, body_text, attachment_count).
eml_to_json — Parse an EML file and return a JSON object containing all decoded headers, plain-text body, HTML body, and attachment metadata (filename, content-type, size).
epub_summary — Summarize an EPUB e-book: metadata (title, creator, language, publisher, date, identifier) and a chapter list with word counts.
epub_to_csv — Convert an EPUB e-book to CSV. One row per chapter with columns: index, title, word_count, text.
epub_to_json — Convert an EPUB e-book to JSON. Returns {"metadata": {...}, "chapters": [...]} where each chapter has index, title, and text fields.
epub_to_text — Convert an EPUB e-book to plain text. Chapters are extracted in spine order and separated by '--- Chapter Title ---' headers.
geojson_summary — Summarize a GeoJSON file: feature count, geometry types, property keys, bounding box, and the first N features.
geojson_to_csv — Flatten a GeoJSON file's features to CSV (one row per feature; properties as columns + a geometry column).
geojson_to_json — Validate and pretty-print a GeoJSON file as JSON.
gpx_summarize — Summarize a GPX file: track count, segment count, total track points, waypoint count, route count, elevation range, time span, and first N points.
gpx_to_csv — Convert a GPX file to CSV. data_type='tracks' (default): one row per track point with track_name, segment_index, point_index, lat, lon, ele, time. data_type='wa
gpx_to_geojson — Convert a GPX file to a GeoJSON FeatureCollection. Track segments become LineString features, waypoints become Point features, and routes become LineString feat
gpx_to_json — Convert a GPX file to a structured JSON object with tracks, waypoints, and routes arrays.
hcl_blocks — Summarize the top-level block types and their labels in an HCL/Terraform file or directory. Returns a newline-separated list of 'block_type: [label, ...]' lines
hcl_resources — List all resource and data block identifiers in an HCL/Terraform file or directory. Returns one 'resource_type.name' (or 'data.resource_type.name') identifier p
hcl_to_csv — Export resource and data blocks from an HCL/Terraform file or directory as CSV. Columns: block_type, resource_type, name. One row per resource/data block.
hcl_to_json — Parse an HCL/Terraform file or directory and return the full configuration as pretty-printed JSON. Strips internal python-hcl2 metadata and extra quote-wrapping
hdf5_to_csv — Convert HDF5 datasets to CSV. Each dataset is preceded by a '# dataset: <path>' comment line. Compound datasets use field names as column headers; numeric array
hdf5_to_json — Convert HDF5 datasets to JSON. With 'dataset': returns a JSON array of row-objects for that dataset (or a JSON object of arrays if the path is a group). Without
hdf5_tree — Inspect an HDF5 file: print a human-readable tree of all groups and datasets with their shapes, dtypes, attributes, and sample values.
ical_merge — Merge multiple iCalendar (.ics) files into a single VCALENDAR. When dedup is true (default), VEVENTs with duplicate UIDs are collapsed to the first occurrence.
ical_to_csv — Convert an iCalendar (.ics) file to CSV — one row per VEVENT. Columns: uid, summary, dtstart, dtend, location, description, organizer, attendees (semicolon-sepa
ical_to_json — Parse an iCalendar (.ics) file and return a JSON array of all calendar components (VEVENT, VTODO, VJOURNAL, etc.) with structured fields: uid, summary, dtstart,
ical_to_text — Read an iCalendar (.ics) file and return a human-readable summary of its events — one block per VEVENT with summary, start/end, location, organizer, attendees,
image-ocr_extract_text — Extract layout-preserving plain text from an image file (.png, .jpg, .tiff) using Tesseract OCR. Multi-page TIFFs are supported; each page's text is separated b
image-ocr_extract_to_csv — Extract word-level OCR data from an image file as CSV. Columns: page, word, conf, left, top, width, height. Suitable for importing into spreadsheets or data pip
image-ocr_extract_to_json — Extract word-level OCR data from an image file as a JSON array. Each element contains page number, word text, confidence score, and bounding box coordinates (le
ipynb_read — Read and render a Jupyter notebook (.ipynb) file. Supports three output formats: 'text' (human-readable with cell headers and outputs), 'markdown' (markdown cel
ipynb_strip_outputs — Return a Jupyter notebook (.ipynb) as JSON with all code cell outputs and execution counts cleared. Useful for producing a clean, reproducible copy of a noteboo
kml_summary — Summarize a KML or KMZ file: placemark count, geometry types, ExtendedData keys, and the first N placemarks.
kml_to_csv — Flatten KML/KMZ placemarks to CSV (one row per placemark; columns: name, description, geometry_type, first_coordinate, plus all ExtendedData keys).
kml_to_geojson — Convert KML/KMZ placemarks to a GeoJSON FeatureCollection. Each Placemark becomes a Feature with Point, LineString, Polygon, or GeometryCollection geometry. Wor
kml_to_json — Convert KML/KMZ placemarks to a JSON array. Each object has name, description, geometry (with type and coordinates), and attributes (ExtendedData key/value dict
mbox_split — Split an mbox file into individual .eml files, one per message, written as 00000.eml, 00001.eml, … into the specified output directory. Returns a manifest with
mbox_to_csv — Read an mbox mailbox file and return RFC 4180 CSV with a header row. Columns: from, to, date, subject, message_id, labels, body.
mbox_to_json — Read an mbox mailbox file and return newline-delimited JSON — one JSON object per line with fields: from, to, date, subject, body, message_id, labels.
mbox_to_text — Read an mbox mailbox file and return a human-readable block per message, with From, To, Date, Subject, optional Labels/Message-ID, and body.
msg_to_csv — Read an Outlook .msg file and return a CSV string (header row + one data row) with columns: from, to, cc, subject, date, message_id, body_text, attachment_count
msg_to_json — Read an Outlook .msg file and return its full content as pretty-printed JSON with keys: headers (from, to, cc, bcc, subject, date, message_id, message_class), b
msg_to_text — Read an Outlook .msg file and return the email as plain text: a header summary block (From, To, Cc, Subject, Date) followed by the decoded body. HTML body is st
odp_to_json — Extract text and speaker notes from an .odp OpenDocument Presentation file and return a JSON array, one object per slide: {"slide": N, "title": "...", "body": [
odp_to_text — Extract text and speaker notes from an .odp OpenDocument Presentation file and return a human-readable dump with === Slide N === headers.
ods_list_sheets — List all sheet names in an ODS file, one per line.
ods_to_csv — Convert a sheet in an ODS file to CSV. Returns comma-separated rows. Optionally include raw formula expressions as extra columns.
ods_to_json — Convert a sheet in an ODS file to JSON. By default treats the first row as column headers and returns an array of objects. Set has_header=false to return an arr
odt_read — Extract the full body of an OpenDocument Text (.odt) file as plain text. Headings are prefixed with # markers; list items are prefixed with -.
odt_to_csv — Extract the first table from an OpenDocument Text (.odt) file and return it as CSV. Raises an error if the document contains no tables.
odt_to_json — Parse an OpenDocument Text (.odt) file and return a JSON object with three keys: 'meta' (document metadata), 'body' (list of paragraph/heading objects), and 'ta
orc_sample — Preview the first N rows of an Apache ORC file as a JSON array (default 10 rows).
orc_schema — Inspect the schema of an Apache ORC file: print column names and their Arrow/ORC types.
orc_to_csv — Convert an Apache ORC file to RFC 4180 CSV. Returns CSV text with a header row.
orc_to_json — Convert an Apache ORC file to a JSON array. Returns all rows (or up to `rows`) as JSON.
parquet_sample — Return the first N rows of a Parquet file as a JSON array.
parquet_schema — Inspect a Parquet file's schema: return all column names and their Arrow/Parquet types.
parquet_to_csv — Convert a Parquet file to RFC 4180 CSV, returning the CSV as a string.
parquet_to_json — Convert a Parquet file to a JSON array string.
plist_convert — Convert an Apple plist file to a different serialization format. to='json' returns JSON text; to='xml' returns XML plist text; to='binary' writes a binary bplis
plist_read — Read an Apple property list (.plist) file and return its contents as formatted text, JSON, or CSV. Optionally drill into a nested key path using dotted notation
reg_read — Read a Windows registry export (.reg) file and return a human-readable text summary: key paths, value names, types, and decoded data.
reg_to_csv — Convert a Windows registry export (.reg) file to CSV with columns: key, key_deleted, value_name, type, data — one row per registry value.
reg_to_json — Convert a Windows registry export (.reg) file to JSON: a flat object keyed by registry key path, each with a 'deleted' flag and a 'values' array ({name, type, d
rtf_to_json — Parse an RTF file and return a JSON object containing filename, format, any embedded metadata (title, author, subject, keywords), the full plain text, and an ar
rtf_to_markdown — Convert an RTF file to Markdown. Headings (detected from \sN style markers or \outlinelevel) become ATX headings; bold and italic spans are preserved as ** and
rtf_to_text — Extract plain text from an RTF file, stripping all RTF control sequences and formatting.
shapefile_summary — Summarize a Shapefile (.shp) or GeoPackage (.gpkg) layer: driver, CRS, geometry type, field schema, feature count, and the first N features.
shapefile_to_csv — Flatten a Shapefile (.shp) or GeoPackage (.gpkg) layer to CSV — one row per feature; attribute columns plus a WKT geometry column.
shapefile_to_geojson — Convert a Shapefile (.shp) or GeoPackage (.gpkg) layer to a GeoJSON FeatureCollection string.
shapefile_to_ndjson — Convert a Shapefile (.shp) or GeoPackage (.gpkg) layer to newline-delimited JSON (one GeoJSON Feature object per line).
sqlite_query — Execute a read-only SELECT query against a SQLite database and return results as text, CSV, or JSON. Only SELECT and WITH...SELECT statements are permitted.
sqlite_read — Read a SQLite database and return its contents as text (default), CSV, or JSON. Shows schema and row samples for all tables, or a single table if specified.
sqlite_schema_diff — Compare the schemas of two SQLite databases and return a readable diff. Reports tables/views added, removed, or changed (column additions, removals, type change
vcard_to_csv — Convert a vCard (.vcf) file to CSV (one row per contact; columns: full_name, first_name, last_name, organization, title, phones, emails, addresses, birthday, ur
vcard_to_json — Parse a vCard (.vcf) file and return a JSON array of contact objects. Each object has keys: full_name, first_name, last_name, organization, title, phones, email
vcard_to_text — Read a vCard (.vcf) file and return a human-readable text summary with one block per contact showing name, phones, emails, addresses, organization, title, birth
xls_list_sheets — List the sheet names (and visibility) in a legacy .xls workbook. Returns one line per sheet: '<index>: <name>' with optional [hidden] or [very-hidden] tags.
xls_to_csv — Convert a legacy .xls workbook to CSV text. All sheets are included by default (each preceded by a '# Sheet: <name>' comment line when multiple sheets are prese
xls_to_json — Convert a legacy .xls workbook to a JSON array of sheet objects. Each element has 'sheet' (name), 'rows' (array of arrays), and optionally 'hidden' for non-visi

Provenance

Where this record came from

Every source is kept verbatim. Field changes are logged as events.

ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:archives

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:arrow

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:avro

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:dbf

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:doc

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:eml

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:epub

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:geojson

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:gpx

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:hcl

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:hdf5

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:ical

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:image-ocr

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:ipynb

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:kml

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:mbox

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:msg

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:odp

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:ods

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:odt

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:orc

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:parquet

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:plist

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:reg

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:rtf

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:shapefile

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:sqlite

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:vcard

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ARD catalog (/.well-known/ard.json)urn:air:stealthstack.ai:mcp:xls

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Field history (6 recent events)

1 mo ago · declared · summary → "Runner twin of the 'archives' skill — the same tools executed server-side (no local setup). Tools: archives_extract_all
1 mo ago · declared · description → "Runner twin of the 'archives' skill — the same tools executed server-side (no local setup). Tools: archives_extract_all
1 mo ago · declared · publisherName → "www.stealthstack.ai"
1 mo ago · declared · publisherUrl → "https://www.stealthstack.ai"
1 mo ago · declared · homepageUrl → "https://www.stealthstack.ai/"
1 mo ago · declared · protocols → ["mcp"]

when	check	result	http	latency	detail
26 h ago	http head	failed	—	—	disallowed by robots.txt
9 d ago	http head	failed	—	—	disallowed by robots.txt
15 d ago	http head	failed	—	—	disallowed by robots.txt
23 d ago	http head	failed	—	—	disallowed by robots.txt
27 d ago	http head	failed	—	—	disallowed by robots.txt
29 d ago	http head	failed	—	—	disallowed by robots.txt
1 mo ago	http head	failed	—	—	disallowed by robots.txt
1 mo ago	http head	failed	—	—	disallowed by robots.txt
1 mo ago	mcp initialize	ok	200	2043 ms	server stealthstack-file-formats 0.1.0 · protocol 2024-11-05 · 98 tools
1 mo ago	mcp initialize	ok	200	353 ms	server stealthstack-file-formats 0.1.0 · protocol 2024-11-05 · 98 tools

Archive Container Reader & Converter (runner)

This record is unclaimed

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