query_clinicaltrialsSearch ClinicalTrials.gov for clinical trials. Can search by drug name, condition, target, or NCT ID. Returns trial status, phase, sponsor, primary endpoints, and why_stopped if terminated.
| Name | Required | Description | Default |
|---|---|---|---|
| phase | Yes | any | |
| query | Yes | Search term: drug name, condition, NCT ID, or target | |
| status | Yes | any | |
| max_results | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description is the sole source of behavioral transparency. It discloses the return fields (status, phase, sponsor, primary endpoints, why_stopped if terminated), adding useful context beyond a bare 'search' description. However, it omits potential limitations such as pagination, result count behavior, or error scenarios.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, action-first, and every clause adds value. It efficiently covers purpose, search options, and return fields without repetition or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description carries the burden of explaining return values; it lists key fields and notes the special 'why_stopped' condition. It also mentions search flexibility. It lacks details on result limits or sorting, but for a moderate-complexity search tool it is mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 25% (only 'query' has a description), so the description must compensate. It mostly repeats the schema's query description and provides no additional explanation for status, phase, or max_results. Although the schema's enums and defaults give some meaning, the description fails to bridge the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'Search ClinicalTrials.gov for clinical trials' with specific search modalities (drug name, condition, target, NCT ID) and lists return fields. This distinguishes it from sibling query tools like query_chembl and query_openfda by making the clinical trial domain explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes the use case evident (searching clinical trials) but does not explicitly say when to choose this over alternatives like web_search or query_pubmed. It provides no exclusions or comparisons to sibling tools, leaving usage guidance implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools have overlapping responsibilities: search, search_claims, search_preprint_flags, and claidex_claim_risk_matrix all query claim/failure data, while rank_documents_by_embedding and rerank_documents both perform relevance ranking. The compatibility-oriented fetch/search tools add further confusion because their names collide with fetch_research_url and search_claims.
Names are grouped by prefixes (claidex_, query_, search_, run_) but the groups use different conventions, and bare verbs like 'fetch' and 'search' sit alongside prefixed forms like 'fetch_research_url' and 'search_claims'. The pattern is readable but not uniform.
24 tools is at the heavy end for an MCP server; while the breadth reflects many biomedical data sources and utilities, the count includes several meta/compatibility tools that could be consolidated. It is borderline but not unreasonable.
The surface covers the core biomedical workflows: searching claims, retrieving full claim content, querying failure graphs, checking preprints, and looking up drugs/trials/targets/adverse events. Minor gaps exist, such as no direct way to fetch a single clinical trial by ID beyond the search function, and no write/update operations for claims, but these are likely outside the read-only research scope.