Open Targets Platform MCP
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Alternatives to Open Targets Platform MCP
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- FlicenseBqualityDmaintenanceEnables AI assistants to query genetic variant data, gene constraints, and population genetics information from the gnomAD (Genome Aggregation Database) through its GraphQL API. Supports searching for genes and variants, retrieving constraint scores, analyzing population frequencies, and accessing genomic coverage data.910-
- AlicenseBqualityDmaintenanceEnables AI assistants to execute GraphQL queries and retrieve schema information from any GraphQL endpoint.28 npm8MIT
- AlicenseNot gradedqualityBmaintenanceEnables querying disease/target/drug knowledge graph from Open Targets, supporting searches, profiles, and associations via natural language through the Pipeworx gateway.6 npmMIT
- AlicenseAqualityDmaintenanceProvides comprehensive GraphQL introspection, filtering, and query/mutation execution with safety controls. Enables AI agents to explore and interact with GraphQL APIs through natural language.79 npm1MIT
- AlicenseBqualityAmaintenanceMCP server that exposes the Open Targets Platform GraphQL API as a set of tools for querying biomedical data such as targets, diseases, drugs, and genetic evidence.68150 PyPI19MIT
- AlicenseNot gradedqualityDmaintenanceEnables LLMs to interact with GraphQL APIs through schema introspection and query execution.889 npm1MIT
TDQS
Scored across 5 tools
The two schema-discovery tools (get_open_targets_graphql_schema and get_type_dependencies) overlap somewhat, but their category-based versus type-based approaches are clearly described. The search, query, and batch-query tools have distinct purposes and are unlikely to be confused.
Tool names are consistently snake_case and mostly verb-first, but the convention mixes get_, search_, query_, and batch_query_ prefixes, and the long open_targets_graphql descriptor appears inconsistently. The docs also reference search_entity while the actual tool is search_entities.
Five tools is well-scoped for a read-only GraphQL data platform: schema discovery, type dependency exploration, entity search, single query execution, and batch query execution each serve a necessary role without redundancy or bloat.
The toolset covers the full workflow: search to resolve identifiers, schema introspection to learn query structure, single-query execution, and batch execution for repeated queries. There are no obvious missing operations for the stated purpose of interacting with the Open Targets Platform API.