Search arXiv papers, download full text, semantic search, citation graphs, and alerts via MCP.
Islam West Africa Collection (IWAC) is installed from its publisher's own source and answers where it runs, so this marketplace is not in the path of a single call. There is no address here to send one to, and a panel that pretended otherwise would be showing you an answer we made up. Install it and call it from your own client — the Installation tab has the entry for each one.
What it does
Read-only access to the Islam West Africa Collection via Hugging Face datasets.
Quickstart
# 1 — add it to Claude Code
claude mcp add --scope user --transport http islam-west-africa-collection-iwac-mcp https://islam.zmo.de/mcp/
# 2 — ask your agent for something these tools do
# search, fetch, explore_corpus and 32 more
Islam West Africa Collection (IWAC) costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Collected from a public index. Nobody has claimed this account, so nothing here was written by its author — claim it if it is yours.
Where are you running it?
Every route below installs the same thing and ends at the same approval screen. Nothing here runs on your machine and nothing runs on ours: this server answers at its publisher’s own address, and what you install is the connection straight to it.
This is a public server: it answers at its publisher’s own address and this marketplace is not in the path. Claude Code registers it in one command; --scope user makes it available in every project. The transport below is http, as the publisher's own manifest declares it.
claude mcp add --scope user --transport http islam-west-africa-collection-iwac-mcp https://islam.zmo.de/mcp/Reconnect, or start a new session, and the tools appear in the model’s tool list.
One config entry pointing straight at the publisher’s own address — this marketplace is not in the path, and nothing from this listing executes on your machine.
35 tools, with what each one reads, writes and reaches shown before you agree — the same list on every route above. Read the tool surface.
Tool surface
What the model actually sees. Descriptions are diffed on every release — see version history.
Search the Islam West Africa Collection across newspaper articles, Islamic publications, archival documents, academic references, audiovisual recordings, photographs, and the authority index (persons/places/organisations/events/subjects). Pass ONE concept or name — e.g. 'Tijaniyya', 'laïcité', 'Sheikh Gumi', 'pèlerinage'. Matching is accent- and case-insensitive; a multi-word query requires every
| Parameter | Type | Required | Notes |
|---|---|---|---|
| query | string | yes | One concept, name, or short phrase; use French concept terms for primary sources, and French/English terms for references |
| limit | integer | no | Max results across all categories. Default 20, max 50. |
Retrieve the full text and metadata of one IWAC item by an id returned from search (format '<category>:<number>', e.g. 'articles:28576'). Returns {id, title, text, url, metadata}: text is the item's OCR / abstract / transcription / description, url is the canonical islam.zmo.de link to cite, and metadata holds the remaining fields (author, date, country, newspaper, AI sentiment, …). Catego
| Parameter | Type | Required | Notes |
|---|---|---|---|
| id | string | yes | Item id from search, e.g. 'articles:28576' or 'references:11045' |
Selection workbench: items, concordance, coverage, compare (requires comparison), attention, aliases, or paginated manifest/CSL-JSON/BibTeX exports. Exact filters intersect. Coverage measures archive availability. Exports identify this page and dataset snapshot; compare snapshot IDs across pages. Schema discovery: iwac://datasets/{subset}.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| mode | string | no | — |
| subset | string | no | — |
| selection | object | no | — |
| comparison | object | no | — |
| offset | integer | no | — |
| limit | integer | no | — |
Search IWAC newspaper articles by keyword (title + OCR + AI abstracts, French and English), country, newspaper, subject, and date range. Use French concept keywords regardless of the user's report language. Matching is accent- and case-insensitive.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| keyword_mode | string | no | — |
| keyword_aliases | array | no | — |
| exact | object | no | AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>. |
| keyword | string | no | Concept keyword; substring match on title, OCR text, and the French and English AI abstracts. Prefer French for the OCR; an English term still matches via the English abstract |
| country | string | no | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Togo (accents optional) |
| newspaper | string | no | — |
| subject | string | no | — |
| date_from | string | no | YYYY-MM-DD (or YYYY) |
| date_to | string | no | YYYY-MM-DD (or YYYY) |
| hijri_month | string | no | Islamic lunar month: 1-12, or a name (Ramadan, Chaabane, Chawwal, Dhu al-Hijja). Pulls the articles behind an observance peak — matches only items with a full YYYY-MM-DD date. |
| hijri_year | integer | no | Islamic (Umm al-Qura) year, e.g. 1445 |
| with_description | boolean | no | Include each article's ~500-char AI abstract (description_ai) for triage without get_article. Adds ~125 tokens/row, so limit defaults to 10 and caps at 25 while this is on. |
| limit | integer | no | Default 20, max 100 (10 and 25 with with_description) |
| offset | integer | no | — |
Get one article (by id): full metadata, the AI abstract (description_ai), AI sentiment, and OCR text, in 25k-char parts (follow next_offset). Pass a keyword to get ~2000-char excerpts around each match instead.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| article_id | integer | yes | — |
| keyword | string | no | Return excerpts around matches instead of the full OCR (accent-insensitive) |
| context_chars | integer | no | Default 2000, max 5000 |
| max_excerpts | integer | no | Default 10, max 25 |
| offset | integer | no | Read from this character on: the previous part's next_offset |
Filter articles by gpt-5-6-luna sentiment labels (accent/case-insensitive exact match). One model's reading, not a consensus — 4 other models scored the same articles and often disagree; get_sentiment_distribution with model:"all" shows by how much. subjectivity is much the weakest of the three scales, so treat a set selected on it as a lead to read rather than as a finding.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| polarity | string | no | Très positif | Positif | Neutre | Négatif | Très négatif | Non applicable |
| centrality | string | no | Très central | Central | Secondaire | Marginal | Non abordé |
| subjectivity | string | no | Très objectif | Plutôt objectif | Mixte | Plutôt subjectif | Très subjectif — least to most subjective. Unscored where the model answered Non abordé, so this filter also excludes those. |
| country | string | no | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Togo (accents optional) |
| subject | string | no | — |
| disputed | string | no | polarite | centralite | subjectivite — keep only articles the panel SPLIT on for that field (French field names, as stored). Selects contested readings, not a sentiment value. |
| limit | integer | no | Default 20, max 100 |
| offset | integer | no | — |
Aggregate AI labels over a shared selection. model:"all" compares independent annotators and their coverage; model:"consensus" reads the stored panel majority. Choose compare_models and agreement_field for pairwise Cohen's kappa and quadratic weighted kappa, with explicit denominators. Labels are interpretations, not ground truth; subjectivity is weak evidence and its caveat must accompany finding
| Parameter | Type | Required | Notes |
|---|---|---|---|
| keyword | string | no | — |
| country | string | no | Exact country name (accents optional) |
| newspaper | string | no | Newspaper/periodical substring |
| subject | string | no | Exact tag |
| date_from | string | no | Inclusive date bounds: YYYY[-MM[-DD]] |
| date_to | string | no | — |
| hijri_month | string | no | — |
| hijri_year | integer | no | — |
| keyword_mode | string | no | — |
| keyword_aliases | array | no | — |
| exact | object | no | AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>. |
| model | string | no | gpt-5-6-luna | mistral-small-2603 | deepseek-v4-flash-0731 | gemma-4-31b-it | qwen3-8-27b | all | consensus; default gpt-5-6-luna. Vendor aliases accepted; retired models rejected. |
| compare_models | array | no | Pair of model IDs or aliases; requires model:"all" |
| agreement_field | string | no | — |
Search the IWAC authority index (persons, places, organisations, events, subjects) by name. Accent/case-insensitive.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| keyword | string | yes | Search term matched against the entry title |
| index_type | string | no | Exact type (accents optional), validated against: Personnes | Lieux | Organisations | Événements | Sujets | Notices d'autorité. An unrecognised value returns an error listing the valid types. |
| limit | integer | no | Default 20, max 100 |
| offset | integer | no | — |
Get full details of an index entry by id (raw dataset columns, French names — Titre, Prénom, Coordonnées…).
| Parameter | Type | Required | Notes |
|---|---|---|---|
| entry_id | integer | yes | — |
List sujets from the IWAC index, sorted by frequency (most-referenced first).
| Parameter | Type | Required | Notes |
|---|---|---|---|
| limit | integer | no | Default 50, max 200 |
| offset | integer | no | — |
List lieux from the IWAC index, sorted by frequency (most-referenced first). The optional 'country' filter selects entries that APPEAR IN records from that country (mentioned-in, not located-in), ranked by collection-wide 'frequency' — so foreign and cross-border entries can appear. Nigeria returns none here (index frequency is computed from articles + publications + references, which have no Nige
| Parameter | Type | Required | Notes |
|---|---|---|---|
| limit | integer | no | Default 50, max 200 |
| offset | integer | no | — |
| country | string | no | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Nigeria | Togo (accents optional). Selects lieux MENTIONED IN records from that country, not entities located there |
List personnes from the IWAC index, sorted by frequency (most-referenced first). The optional 'country' filter selects entries that APPEAR IN records from that country (mentioned-in, not located-in), ranked by collection-wide 'frequency' — so foreign and cross-border entries can appear. Nigeria returns none here (index frequency is computed from articles + publications + references, which have no
| Parameter | Type | Required | Notes |
|---|---|---|---|
| limit | integer | no | Default 50, max 200 |
| offset | integer | no | — |
| country | string | no | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Nigeria | Togo (accents optional). Selects personnes MENTIONED IN records from that country, not entities located there |
Overall statistics for every IWAC subset, including fulltext_coverage — how many items in each subset actually carry searchable full text in this dataset. Read that before treating any keyword count as a full-text census.
No parameter schema on file.
Per-newspaper article counts and date ranges.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| country | string | no | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Togo (accents optional) |
Compare article counts, newspaper counts, date ranges, and gpt-5-6-luna polarity across countries.
No parameter schema on file.
Counts by Gregorian or Hijri year/month, or pooled lunar month. Group by country/newspaper. Partial dates and missing lunar dates are disclosed. normalize_by returns numerator counts and per-bucket denominators in the same country/outlet/date scope, removing thematic filters. Shares describe IWAC holdings.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| keyword | string | no | — |
| country | string | no | Exact country name (accents optional) |
| newspaper | string | no | Newspaper/periodical substring |
| subject | string | no | Exact tag |
| date_from | string | no | Inclusive date bounds: YYYY[-MM[-DD]] |
| date_to | string | no | — |
| hijri_month | string | no | — |
| hijri_year | integer | no | — |
| keyword_mode | string | no | — |
| keyword_aliases | array | no | — |
| exact | object | no | AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>. |
| normalize_by | string | no | Share per bucket in the same country/outlet/date scope; searchable restricts both counts to full text. Thematic filters are removed from the denominator. |
| subset | string | no | articles (default) | publications | references | documents | audiovisual | images |
| granularity | string | no | year (default) | month | lunar_month (all years collapsed into 12 lunar months; needs calendar=hijri) |
| calendar | string | no | gregorian (default) | hijri — bucket by the Islamic (Umm al-Qura) calendar |
| group_by | string | no | country | newspaper — one distribution per group value |
Counts of offline LDA topic assignments, optionally over time. Topic labels are interpretive model outputs; exact topic_id filters select assignments rather than keyword matches. Reports unclassified coverage.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| subset | string | no | articles (default) | references |
| keyword | string | no | — |
| country | string | no | Exact country name (accents optional) |
| newspaper | string | no | Newspaper/periodical substring |
| subject | string | no | Exact tag |
| date_from | string | no | Inclusive date bounds: YYYY[-MM[-DD]] |
| date_to | string | no | — |
| hijri_month | string | no | — |
| hijri_year | integer | no | — |
| keyword_mode | string | no | — |
| keyword_aliases | array | no | — |
| exact | object | no | AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>. |
| min_prob | number | no | 0-1; keep only assignments at or above this probability |
| over_time | boolean | no | Also return per-year counts for the leading topics |
| top_n | integer | no | Topics given their own band in over_time (default 8, max 15) |
Rank exact metadata values, splitting pipe-separated tags. Reports missing metadata and optional coverage over time. Choose spatial for mentioned places, country for stored country tags, or subject/author/language.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| field | string | yes | subject | spatial | author | language | newspaper | country |
| subset | string | no | articles (default) | publications | references |
| keyword | string | no | — |
| country | string | no | Exact country name (accents optional) |
| newspaper | string | no | Newspaper/periodical substring |
| subject | string | no | Exact tag |
| date_from | string | no | Inclusive date bounds: YYYY[-MM[-DD]] |
| date_to | string | no | — |
| hijri_month | string | no | — |
| hijri_year | integer | no | — |
| keyword_mode | string | no | — |
| keyword_aliases | array | no | — |
| exact | object | no | AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>. |
| top_n | integer | no | Values returned (default 25, max 100) |
| over_time | boolean | no | Also return the per-year share of items carrying a value |
Count pairs of metadata values co-tagged on the same items. Matrix/network views show descriptive associations, not causal links. Filters apply before pair counting; top_n caps the vocabulary.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| field | string | no | subject (default) | spatial | author | language |
| subset | string | no | articles (default) | publications | references |
| keyword | string | no | — |
| country | string | no | Exact country name (accents optional) |
| newspaper | string | no | Newspaper/periodical substring |
| subject | string | no | Exact tag |
| date_from | string | no | Inclusive date bounds: YYYY[-MM[-DD]] |
| date_to | string | no | — |
| hijri_month | string | no | — |
| hijri_year | integer | no | — |
| keyword_mode | string | no | — |
| keyword_aliases | array | no | — |
| exact | object | no | AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>. |
| top_n | integer | no | Values on each axis (default 15, max 30) |
Place tags joined to authority coordinates. Separates publication countries from mentioned places; missing geocodes are counted explicitly.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| subset | string | no | articles (default) | publications | references |
| keyword | string | no | — |
| country | string | no | Exact country name (accents optional) |
| newspaper | string | no | Newspaper/periodical substring |
| subject | string | no | Exact tag |
| date_from | string | no | Inclusive date bounds: YYYY[-MM[-DD]] |
| date_to | string | no | — |
| hijri_month | string | no | — |
| hijri_year | integer | no | — |
| keyword_mode | string | no | — |
| keyword_aliases | array | no | — |
| exact | object | no | AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>. |
| top_n | integer | no | Geocoded places returned (default 60, max 200) |
Stable-hash sample of matching stored embeddings, projected with PCA. Reports eligible, invalid, missing and capped counts, seed and explained variance. Group counts describe the sample. Coordinates are chart-only; this is not the published UMAP landscape. Needs no API key.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| subset | string | no | articles (default) | publications | references |
| keyword | string | no | — |
| country | string | no | Exact country name (accents optional) |
| newspaper | string | no | Newspaper/periodical substring |
| subject | string | no | Exact tag |
| date_from | string | no | Inclusive date bounds: YYYY[-MM[-DD]] |
| date_to | string | no | — |
| hijri_month | string | no | — |
| hijri_year | integer | no | — |
| keyword_mode | string | no | — |
| keyword_aliases | array | no | — |
| exact | object | no | AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>. |
| color_by | string | no | country | newspaper | subject | lda_topic_label | polarity (gpt-5-6-luna's label) |
| limit | integer | no | Items projected (default 300, max 2000) |
Nearest stored embeddings by cosine similarity, without an API key. Scores rank reading candidates; no threshold proves a reprint. Returns source IDs and dates for comparison. Corpus-wide candidate generation belongs offline.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| id | string | yes | Item id — either a bare o:id ('3064') or the namespaced form search returns ('articles:3064') |
| subset | string | no | articles (default) | publications | references |
| limit | integer | no | Neighbours returned (default 12, max 50) |
| min_score | number | no | Minimum cosine similarity (-1 to 1) |
Text length, lexical richness and readability by country/newspaper/year. Metrics are precomputed; readability is French-specific and excludes other languages. Missing values are disclosed. Compare distributions as descriptive evidence.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| group_by | string | no | year (default) | newspaper | country |
| keyword | string | no | — |
| country | string | no | Exact country name (accents optional) |
| newspaper | string | no | Newspaper/periodical substring |
| subject | string | no | Exact tag |
| date_from | string | no | Inclusive date bounds: YYYY[-MM[-DD]] |
| date_to | string | no | — |
| hijri_month | string | no | — |
| hijri_year | integer | no | — |
| keyword_mode | string | no | — |
| keyword_aliases | array | no | — |
| exact | object | no | AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>. |
| top_n | integer | no | Groups returned when grouping by newspaper (default 20, max 60) |
Search Islamic publications (periodical issues, books). keyword matches title, subject, table of contents, and full OCR text (TOC hits come back as matching_toc_entries); use French concept keywords regardless of the user's report language. Filter by newspaper/series, subject, country and year. Use list_periodicals to discover series titles, and get_publication_fulltext for keyword excerpts from
| Parameter | Type | Required | Notes |
|---|---|---|---|
| keyword_mode | string | no | — |
| keyword_aliases | array | no | — |
| exact | object | no | AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>. |
| keyword | string | no | French concept keyword; substring match on title + subject + table of contents + OCR (accent-insensitive) |
| newspaper | string | no | Periodical/series title (see list_periodicals) |
| subject | string | no | Subject tag (~87% of issues are tagged) |
| country | string | no | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Togo (accents optional) |
| date_from | string | no | Earliest year, YYYY |
| date_to | string | no | Latest year, YYYY |
| hijri_month | string | no | Islamic lunar month: 1-12, or a name (Ramadan, Chaabane, Chawwal, Dhu al-Hijja). Matches only issues with a full YYYY-MM-DD date — ~83% of them. |
| hijri_year | integer | no | Islamic (Umm al-Qura) year, e.g. 1445 |
| limit | integer | no | Default 20, max 100 |
| offset | integer | no | — |
List the Islamic periodical/series titles in the publications subset, with issue counts and year ranges. Use the returned newspaper value as the newspaper filter on search_publications.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| country | string | no | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Togo (accents optional) |
Full OCR text of a publication in 25k-char parts (follow next_offset), or ~2000-char excerpts around keyword matches (accent-insensitive; capped: see match_count vs excerpts_returned).
| Parameter | Type | Required | Notes |
|---|---|---|---|
| publication_id | integer | yes | — |
| keyword | string | no | — |
| context_chars | integer | no | Default 2000, max 5000 |
| max_excerpts | integer | no | Default 10, max 25 |
| offset | integer | no | Read from this character on: the previous part's next_offset |
Search academic references (journal articles, book chapters, theses, books, reports) by keyword and metadata. keyword is a single substring match over title + abstract, so search ONE term per call (combined terms like 'pèlerinage Mecque' miss results). References are multilingual: try French and English title/abstract keywords when relevant; metadata/filter values such as reference_type and `l
| Parameter | Type | Required | Notes |
|---|---|---|---|
| keyword | string | no | One French or English concept keyword; substring match on title + abstract (one term per call, accent-insensitive) |
| author | string | no | — |
| reference_type | string | no | Substring match. Values: Article de revue | Chapitre de livre | Livre | Mémoire de maitrise | Rapport | Thèse de doctorat | Communication scientifique | Compte rendu de livre | Article d'encyclopédie |
| subject | string | no | Subject tag (sparse: ~27% of references are tagged) |
| country | string | no | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Nigeria | Togo (accents optional) |
| language | string | no | e.g. Français | Anglais |
| date_from | string | no | Earliest year, YYYY |
| date_to | string | no | Latest year, YYYY |
| limit | integer | no | Default 20, max 100 |
| offset | integer | no | — |
Full bibliographic record for one academic reference (by id), including the complete abstract (present for ~51% of references), subjects, DOI/URL, and host-work details (book, volume, issue, pages).
| Parameter | Type | Required | Notes |
|---|---|---|---|
| reference_id | integer | yes | — |
Search the small archival-documents subset (~26 items: Islamic association reports, flyers, project documents — mostly Burkina Faso). Use French concept keywords regardless of the user's report language. Most have OCR text and an AI description. Call with no arguments to list all.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| keyword | string | no | Concept keyword; substring match on title, OCR, the French and English AI descriptions, and subject (accent-insensitive) |
| country | string | no | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Nigeria | Togo (accents optional). Corpus is mostly Burkina Faso/Togo/Benin |
| limit | integer | no | Default 15, max 50 |
| offset | integer | no | — |
Get one archival document (by id): full metadata, AI description, and OCR text, in 25k-char parts (follow next_offset). Pass a keyword to get ~2000-char excerpts around each match instead, useful for long documents.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| document_id | integer | yes | — |
| keyword | string | no | Return excerpts around matches instead of the full OCR (accent-insensitive) |
| context_chars | integer | no | Default 2000, max 5000 |
| max_excerpts | integer | no | Default 10, max 25 |
| offset | integer | no | Read from this character on: the previous part's next_offset |
Search audiovisual materials by keyword and metadata: francophone web video from Burkina Faso, Togo and Benin (TV reports, association and campus recordings), plus deposited Nigerian Hausa/Arabic recordings. Keyword matches title, creator, publisher, subject, spatial, language, source, the item's own description (the richest text most of these items have) and its transcription where one exists. Ea
| Parameter | Type | Required | Notes |
|---|---|---|---|
| keyword | string | no | Substring match across audiovisual title/metadata fields |
| country | string | no | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Nigeria | Togo (accents optional). Burkina Faso, Togo, Benin and Nigeria only — no Niger or Ivorian items |
| language | string | no | Exact language value, e.g. Français | Haoussa | Arabe | Anglais | Mooré |
| medium | string | no | Exact carrier medium: Vidéo sur le web | DVD | CD (validated, accents optional) |
| publisher | string | no | Substring on the publishing channel/broadcaster, e.g. RTB | AEEM | CERFI |
| source_type | string | no | youtube (harvested web video, the large majority) | deposited (recordings with a file, 47) |
| subject | string | no | Exact subject tag — only ~27 rows carry one, so prefer publisher/keyword |
| limit | integer | no | Default 20, max 50 |
| offset | integer | no | — |
List audiovisual materials, newest first (francophone web video from Burkina Faso, Togo and Benin; deposited Nigerian Hausa/Arabic recordings). Filter by country, publishing channel or source_type.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| country | string | no | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Nigeria | Togo (accents optional). Burkina Faso, Togo, Benin and Nigeria only — no Niger or Ivorian items |
| publisher | string | no | Substring on the publishing channel/broadcaster, e.g. RTB | AEEM | CERFI |
| source_type | string | no | youtube (harvested web video, the large majority) | deposited (recordings with a file, 47) |
| limit | integer | no | Default 20, max 50 |
| offset | integer | no | — |
Get one audiovisual record by id: full description and transcription (where one exists), creator/publishing channel, duration, medium, subjects, places, language, rights, source, and three distinct links: url (the IWAC page, the one to cite), external_url (where a harvested video plays) and media_url (a deposited file). source_type says which to expect. A long transcription comes in 25k-ch
| Parameter | Type | Required | Notes |
|---|---|---|---|
| audiovisual_id | integer | yes | — |
| keyword | string | no | — |
| offset | integer | no | Read from this character on: the previous part's next_offset |
Search the IWAC photographs (30 items: mosques, radio stations, schools, signage and street scenes documented during fieldwork). Keyword matches title, creator, subject, place and the rare caption. Each result carries image_url (the full-resolution file), coordinates ('lat, lng' where known) and the canonical IWAC page. Call with no arguments to list all. Captions are almost never present, so
| Parameter | Type | Required | Notes |
|---|---|---|---|
| keyword | string | no | French concept keyword; substring match on title, creator, subject, place and caption |
| country | string | no | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Nigeria | Togo (accents optional) |
| subject | string | no | Exact subject tag (pipe-aware) |
| spatial | string | no | Exact place name, e.g. Ouagadougou (pipe-aware) |
| creator | string | no | Photographer name (substring match) |
| date_from | string | no | YYYY-MM-DD (or YYYY) |
| date_to | string | no | YYYY-MM-DD (or YYYY) |
| limit | integer | no | Default 20, max 50 |
| offset | integer | no | — |
Get one photograph by id: title, photographer, capture date, place and coordinates, subjects, rights, the IIIF manifest, and the full-resolution image_url. The server returns URLs, not image bytes.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| image_id | integer | yes | — |
- Every tool — any call limit is its publisher’s, not ours
- No card, and mcprush charges nothing for it
- Runs at its publisher’s own address — this marketplace is not in the path
- Nothing to cap, because mcprush bills nothing
What counts against your monthly calls
| Tool | Unit | Calls used | Out of the allowance |
|---|
Nothing here is billable: mcprush charges nothing to install Islam West Africa Collection (IWAC) or to call it, at any volume.
Two independent axes, because powerful and malicious are different questions. The grade is threat only. The capability level is blast radius, and it is never a penalty on the grade — it is priced as one subtract-only term in the score, where you can see it.
This listing is an address its publisher runs, and you connect to it directly — this marketplace is not in the path. The scanner reads packages and public source, and an address is neither: the repository linked on this page is where this record was collected from, not a copy of what the address serves, so it is not graded in its place. So there is no grade — not a withheld one, an unmeasured one.
Release history
This is an address its publisher runs: which release it serves is theirs to choose, so there is nothing here to pin. The history below is for reading; the current release on file is 4.0.1.
No release note was published with this version.
One review per account, from a signed-in account that does not publish this listing. Nothing else is asked — you can say what you think before you install it. Publishers can reply once per review, and a review can be edited or deleted by whoever wrote it.
Any signed-in account that does not publish Islam West Africa Collection (IWAC) can review it, once — before installing it or after. A review from an account that has installed it is marked as one.
Nobody has reviewed this listing. The rating on the card is the mean of the reviews written here and nothing else, so there is no rating until somebody writes the first — which takes a signed-in account that does not publish it, and nothing else.