clinicaltrialsgov-mcp-server
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Alternatives to clinicaltrialsgov-mcp-server
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- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to search and retrieve clinical trial data from ClinicalTrials.gov, supporting filters, study details, metadata, and statistics.ISC
- FlicenseNot gradedqualityDmaintenanceEnables searching and retrieving information from the ClinicalTrials.gov database of over 400,000 clinical studies, including trial details, eligibility criteria, locations, and results across 220+ countries.5-
- FlicenseNot gradedqualityDmaintenanceEnables AI agents to search and analyze clinical trial data from ClinicalTrials.gov using both structured SQL queries for filtering trials by status, phase, and conditions, and semantic vector search for exploring detailed protocol information like exclusion criteria.-
- AlicenseAqualityFmaintenanceEnables conversational access to 400,000+ clinical trials on ClinicalTrials.gov, allowing users to search, compare, and retrieve trial details using plain English through MCP-compatible clients like Cursor and Claude Desktop.524 PyPI3MIT
- AlicenseNot gradedqualityAmaintenanceEnables agents to search the ClinicalTrials.gov registry, retrieve full study records and posted results, explore API field names and values, and match patient demographics and conditions to eligible recruiting trials. Runs over STDIO or Streamable HTTP with rate-limit handling, geographic proximity search, and read-only public access requiring no authentication.1,881 npmApache 2.0
- AlicenseAqualityAmaintenanceProvides LLMs with structured access to critical biomedical databases including PubTator3 (PubMed/PMC), ClinicalTrials.gov, and MyVariant.info through the Model Context Protocol.35761 PyPI668MIT
TDQS
Scored across 7 tools
Each tool targets a fairly distinct operation: count, search, single record, results, field values, field definitions, and patient-eligibility matching. The only real overlap is clinicaltrials_get_field_values vs clinicaltrials_get_field_definitions (and to a lesser degree search_studies vs get_study_record), but the descriptions draw clear lines between them.
All tools share the clinicaltrials_ prefix and a predictable verb_noun snake_case pattern (get_study_count, search_studies, get_study_record, get_field_values, get_study_results, find_eligible). The one verb deviation (find_eligible vs get_*) is semantically meaningful and still readable.
Seven tools is a well-scoped surface for a ClinicalTrials.gov wrapper, covering discovery, retrieval, results, and eligibility without redundancy. Each tool earns its place in a typical workflow.
The set covers counting, searching, field discovery, full records, results data, and patient matching, which is strong lifecycle coverage for the domain. Minor gaps remain, e.g. no batch record fetch for multiple NCT IDs (only results supports up to 20) and no dedicated sponsor/intervention entity lookup.