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Resolve ambiguous names or tickers into verified canonical entity IDs.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "Entity-ID Resolver" MCP server from askskill: Run: claude mcp add 'xyz-entityresolver-resolver' -- npx -y entityresolver-mcp
Resolve “Apple” to verified canonical entity IDs and return standard identifiers such as SEC CIK, GLEIF LEI, or Wikidata ID.
Returns one or more canonical IDs for Apple and labels each ID type.
Resolve the ticker “TSLA” to the corresponding entity and output verified canonical IDs.
Returns the canonical entity name for the ticker and its relevant standard IDs.
Resolve “BTC” into a canonical crypto asset entity and return the CoinGecko or other supported standard ID.
Returns the canonical asset ID for downstream lookup and data integration.
Researchers can resolve company names, tickers, or organization aliases into authoritative IDs before retrieval and cross-checking, reducing confusion from name ambiguity.
Data analysts or developers can normalize inconsistent names and tickers into SEC CIK, GLEIF LEI, Wikidata, or CoinGecko IDs for downstream joins and analysis.
It resolves ambiguous names or tickers into verified canonical entity IDs. The provided description mentions support for SEC CIK, GLEIF LEI, Wikidata, and CoinGecko.
Based on the provided information, it handles ambiguous inputs such as names and tickers, then outputs authoritative canonical IDs. The explicitly listed ID types are SEC CIK, GLEIF LEI, Wikidata, and CoinGecko.
No installation steps, runtime details, or key requirements were provided. For implementation specifics, see the source repository.
Handle entity resolution workflows with mapping, SDK code generation, search, and troubleshooting.
Resolve company names, domains, or LinkedIn URLs into canonical identities.
Resolve US stock tickers to SEC CIKs for EDGAR lookups.
Access GLEIF data to query entities, LEI records, and relationships.
Look up verified entities, tax IDs, registries, and economic data across countries.
Match messy financial institution records to canonical regulatory identifiers.