Wikidata is a free and open knowledge base that can be read and edited by both humans and machines. It acts as central storage for the structured data of its Wikimedia sister projects including Wikipedia, Wikivoyage, Wiktionary, Wikisource, and others.
Enables AI assistants to run pay-per-result web data and media tools such as website tech stack detection, document-to-Markdown conversion, SEO audits, OCR, and domain lookups via Apify.
14
MIT
Why this server?
Provides entity verification and data enrichment for ForceDream tools like extract_data, score_lead, and generate_sentiment.
Enables discovery and invocation of AI agents from the ForceDream platform. Provides cryptographic verification of agent outputs for trustless task integrity.
6
119 npm
1
MIT
Why this server?
Integrates Wikidata knowledge graph data to enhance entity profiles with verified information, contributing to comprehensive business intelligence dossiers.
Structured business intelligence for AI agents. 11.3M verified entities, 40.3M BORME mercantile acts, EU VAT validation (VIES), GLEIF LEI and healthcare registries. 12 tools.
6
1
MIT
Why this server?
Integrates with Wikidata to find alignments and cross-references for concepts in schema.gov.it, enabling discovery of international correspondences via owl:sameAs and skos:exactMatch links.
Enables AI agents to semantically explore and analyze the Italian government data catalog (schema.gov.it), including ontologies, vocabularies, datasets, and data quality checks.
47
9
MIT
Why this server?
Allows resolving Wikidata IDs to amodb IDs and including Wikidata facts in movie and TV records.
Enables MCP clients such as Claude, Cursor, and VS Code to search movie and TV titles, read full records for movies, TV shows, seasons, and people, check trending lists, discover titles, and find cinema showtimes.
9
MIT
Why this server?
Allows fetching authoritative formulas from Wikidata, providing access to a vast repository of mathematical and scientific expressions.
MCP server for symbolic computation that enables AI agents to perform step-by-step derivations, transform formulas, and verify results with full provenance, combining natural language with formal mathematical operations.
41
30 PyPI
13
Apache 2.0
Why this server?
Validates Wikidata QIDs used as research topic references, checking that they exist and are of the expected type.
Enables producing verifiable FORRT nanopublication chains with grounded quote verification and compact Science Live constellation projections, supporting reproduction, replication, and new research workflows.
15
169 PyPI
1
MIT
Why this server?
Uses Wikidata as a data source for regional statistics: population and area values (normalised via P2046), capitals, subdivision types, ISO 3166-2 subdivision lookups, and per-region links. The server queries Wikidata's SPARQL endpoint to resolve administrative subdivisions and enrich each region with its own population, area, capital city and identifiers.
Serves country facts, administrative boundary GeoJSON, and per-region population, area, and capital statistics as structured data, letting an AI assistant build interactive maps, comparisons, and multilingual geography content instead of reciting prose. It also normalises region names across sources so boundary shapes can be joined to their statistics.
3
MIT
Why this server?
Enables alignment of world-reference entities (Taxon, ChemicalEntityTerm, Country) to Wikidata via SPARQL search, resolving wikidataId / skos:exactMatch keys through the wikidata_alignment_search tool.
Enables querying organism taxonomy, OBO reference terms, food and nutrition composition, organism and weather observations, and Wikidata alignments through nine MCP tools, with keyed source credentials resolved server-side.
