Search and monitor ClinicalTrials.gov and EU trial registry records, with trial change tracking and
Scored across 7 tools
The three search tools are clearly distinguished by source (ClinicalTrials.gov, EU CTIS, openFDA), and compare/get/changes each target distinct actions. However, get_clinical_trial and get_trial_intelligence_brief both return study information and could be confused at selection time, with the brief's broader scope (sponsor, condition, intervention, watchlists) being the only clear differentiator.
All names use consistent snake_case verb_noun structure: compare_, get_, and search_ prefixes map cleanly to their actions. Minor variation in nouns (clinical_trials vs trial vs eu_trials) does not break the predictable pattern.
Seven tools is well-scoped for a clinical trial tracker, with each tool earning its place across search, retrieval, change tracking, comparison, and briefing. No redundant or filler tools.
The surface covers search across registries, single-study retrieval, change history, comparison, and synthesized briefs, which is strong lifecycle coverage for a read-only tracker domain. The notable gap is that briefs reference 'your watchlists' but no tool exists to create, list, or manage watchlists.
Side-by-side registry attributes for 2 to 5 studies. A structural comparison only, never an efficacy or safety ranking.
| Name | Required | Description | Default |
|---|---|---|---|
| nct_ids | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only, idempotent, open-world, non-destructive behavior, so the bar is lower. The description adds a genuinely useful scope caveat — 'a structural comparison only, never an efficacy or safety ranking' — which prevents an agent from presenting the output as a comparative judgment.
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?
Two short sentences, zero filler, with the primary scope (what is compared) front-loaded and the critical limitation immediately after. Nothing needs trimming.
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?
With one parameter, no output schema, and rich annotations, the description covers what is needed: what is compared and what the output must not be read as. The main remaining gap is that it does not state the identifier format required for nct_ids.
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?
There is one parameter with 0% schema description coverage, but the description partially compensates by stating the accepted count range of 2 to 5 studies, mirroring minItems/maxItems. It does not explain that the values must be NCT identifiers or match the strict NCT\d{8} pattern, so meaning is only partly added.
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 names the operation (side-by-side comparison), the resource (registry attributes), and the scope (2 to 5 studies), which is enough to distinguish it from the retrieval siblings like get_clinical_trial. It stops short of explicitly naming which sibling to use instead, so it lands at 4 rather than 5.
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?
Usage is implied by 'Side-by-side ... for 2 to 5 studies' — an agent can infer this is for multi-trial comparison rather than single-trial retrieval. However, it never names an alternative tool or states when not to use this one, so guidance is inferential only.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
One study by NCT id: full structured record (status, dates, enrollment, eligibility text, sites and contacts, outcomes, documents), plus the changes AgentStructure has observed and data freshness.
| Name | Required | Description | Default |
|---|---|---|---|
| nct_id | Yes | ||
| max_locations | No | ||
| location_filter | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds useful return-content context — observed changes and data freshness — but says nothing about pagination behavior for locations or how much of the record can be truncated.
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?
A single dense sentence that front-loads the identifier-based lookup and then lists returned fields; there is little waste. The trailing clause about observed changes and freshness makes it slightly run-on but still readable.
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?
With no output schema, the description does a fair job describing the returned record's shape. However, for a tool with a nested object parameter and zero schema descriptions, the description is silent on filtering/limiting semantics, and the overlap with get_trial_changes is left unexplained.
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 0% across three parameters, including a nested location_filter object with city/state/country and a max_locations cap. The description only hints at nct_id ('by NCT id') and leaves the location-filtering parameters entirely undocumented, so it fails to compensate for 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 names a precise verb and resource — retrieving one study by NCT id — and enumerates the record's contents (status, dates, enrollment, eligibility, sites, contacts, outcomes, documents). 'One study by NCT id' clearly separates it from the search_* siblings, though no sibling is named explicitly.
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?
Usage is only implied: the agent must already hold an NCT id, which the description states but never turns into a when-to-use rule. It also mentions 'the changes AgentStructure has observed' without telling the agent how this differs from the get_trial_changes sibling, leaving a real routing ambiguity unresolved.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
The change history AgentStructure recorded for a study: previous and new values, event type, dates and provenance. Starts monitoring the study if it was unknown.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| since | No | ||
| nct_id | Yes | ||
| event_types | No | ||
| include_baseline | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description states the tool 'Starts monitoring the study if it was unknown,' which is a persistent server-side state change, while the annotations declare readOnlyHint=true and destructiveHint=false. The disclosure is genuinely useful, but it directly conflicts with the read-only claim, so per the contradiction rule this scores 1.
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?
Two tight sentences, front-loaded with what is returned before the side-effect note. No filler, no restatement of the title or name.
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?
With no output schema, the description does good work describing the returned fields, and it flags the monitoring side effect. However, for a five-parameter tool with zero schema documentation it omits all filter/pagination guidance (since, limit, event_types, include_baseline), leaving an agent guessing how to scope the query.
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 0% across five parameters (limit, since, nct_id, event_types, include_baseline), so the description carries the full burden and does not meet it: it never mentions nct_id, the date filter, the limit, or the event-type filter. 'Event type' appears only as a returned field, which could even mislead an agent into not using the event_types filter.
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 names a specific verb+resource: the recorded change history for a study, with the return contents spelled out (previous/new values, event type, dates, provenance). It is clearly distinguishable from get_clinical_trial and search_clinical_trials, though it never names a sibling to route against.
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?
Usage is only implied: an agent can infer this is the tool for inspecting what changed on a trial, but there is no explicit 'use this when...' versus the other five trial/search siblings, and no stated prerequisites. The note that monitoring starts when the study is unknown is useful context but is not framed as a guidance rule.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
A source-linked brief on a study, sponsor, condition, intervention, or one of your watchlists: current facts, observed developments, unknowns, and freshness.
| Name | Required | Description | Default |
|---|---|---|---|
| value | Yes | NCT id, sponsor, condition, intervention, or watchlist id | |
| subject | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety and idempotency profile is covered. The description adds that the brief is source-linked and includes unknowns and freshness, but does not state cost/latency, whether it performs live retrieval, or return shape. This adds some behavior beyond annotations but remains thin.
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?
Single front-loaded sentence with no filler; every clause earns its place by naming the subject types and the brief's contents.
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?
For a read-only retrieval tool with no output schema, the description covers what the brief contains but omits key calling context: no routing guidance vs siblings, no note on source coverage or latency, and no statement that subject must match the value's type. Adequate but with clear gaps.
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 50%: value is documented as an NCT id, sponsor, condition, intervention, or watchlist id, while subject's enum is present without a description. The description mentions the same subject types, adding little beyond the enum. Baseline 3 is appropriate.
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 what the tool produces: a source-linked brief covering facts, developments, unknowns, and freshness, for a study/sponsor/condition/intervention/watchlist. This is a specific verb+resource (get a synthesized brief) that differs from siblings like get_clinical_trial and get_trial_changes, though it does not name them explicitly.
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 lists possible subjects but gives no guidance on when to use this tool instead of get_clinical_trial, get_trial_changes, or compare_clinical_trials. An agent has no rule to pick it over the raw-data or raw-diff siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search ClinicalTrials.gov by condition, intervention, sponsor, phase, recruitment status, location, institution, study type or dates. Returns structured studies with source links and retrieval time.
| Name | Required | Description | Default |
|---|---|---|---|
| near | No | ||
| phase | No | ||
| query | No | Free-text search across the registry | |
| nct_ids | No | ||
| sponsor | No | Sponsor or collaborator name | |
| location | No | Free-text place, e.g. 'Boston, Massachusetts' | |
| condition | No | Disease or condition, e.g. multiple sclerosis | |
| page_size | No | ||
| page_token | No | ||
| study_type | No | ||
| institution | No | Research site / facility name | |
| intervention | No | Drug or other intervention name | |
| start_date_to | No | ||
| updated_since | No | ||
| location_filter | No | Show only sites in this city/state/country in each result | |
| start_date_from | No | ||
| first_posted_since | No | ||
| recruitment_status | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds return-value context (structured studies with source links and retrieval time), which is useful, but says nothing about pagination semantics, result caps, or rate limits for a query tool that clearly paginates.
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?
Two dense sentences with zero filler; the search scope leads and the return summary follows. It is well front-loaded and correctly sized for a query tool, though being a single enumeration it offers little structural help for such a wide schema.
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?
With 18 parameters, 0 required, nested objects (near, location_filter), no output schema, and low schema coverage, the description is too thin. It leaves the agent without guidance on combining filters, the pagination model, or the distinction between the several geographic filtering mechanisms.
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 39% across 18 parameters, so the schema does not fully document itself and the description is expected to compensate. The description names several filter categories (condition, intervention, sponsor, phase, recruitment status, location, institution, study type, dates) that map to real params, but it never clarifies ambiguities like `near` vs `location` vs `location_filter`, `nct_ids`, or `page_token`.
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?
States a specific verb (Search) and resource (ClinicalTrials.gov) and enumerates the filterable dimensions, so the agent knows exactly what this tool retrieves. It does not, however, name or differentiate itself from siblings like search_eu_trials or get_clinical_trial, leaving registry scope to be inferred from the description text.
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?
There is no when-to-use guidance, no statement of when this tool is preferable to get_clinical_trial (by NCT ID) or search_eu_trials (other registries), and no mention of pagination or how multiple filters interact. The agent gets a capability list but no routing logic.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search the EU Clinical Trials Information System (CTIS, euclinicaltrials.eu) by condition, medicine, sponsor or text, or get one trial by EU CT number (with its ClinicalTrials.gov link when listed). Experimental source.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | ||
| query | No | Free text across EU trial records | |
| sponsor | No | ||
| medicine | No | Medicine or active substance | |
| condition | No | Medical condition | |
| ct_number | No | Get one trial by EU CT number | |
| page_size | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly/idempotent/openWorld/non-destructive, so the safety profile is covered. The description adds 'Experimental source' (a reliability caveat) and the ClinicalTrials.gov cross-link behavior, but omits pagination, rate limits, or auth context.
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?
A single front-loaded sentence packs verb, system, domain, both modes, and the cross-link note with no filler. No wasted sentences, though structure is dense rather than segmented.
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?
For a 7-param search tool with no output schema, the description covers identity and the dual mode but omits pagination behavior and any sense of result shape. Adequate but with clear gaps.
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 coverage is 57%, and the description maps the key filters (condition, medicine, sponsor, text, EU CT number) to usage. However page and page_size are undocumented in both schema and description, so the description does not fully compensate for 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?
States a specific verb (Search) and resource (EU Clinical Trials Information System / CTIS) and adds the dual mode (search vs. get-one-by-CT-number). The 'EU' scoping distinguishes it from the sibling search_clinical_trials, though no sibling is named explicitly.
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 lists filter fields but gives no when-to-use or when-not-to-use guidance relative to siblings like search_clinical_trials or get_clinical_trial. 'Experimental source' is a caveat, not usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search openFDA: Drugs@FDA approvals (drug/drugsfda), recalls (drug/enforcement) or labeling (drug/label) by drug, firm, application number or date.
| Name | Required | Description | Default |
|---|---|---|---|
| drug | No | ||
| firm | No | ||
| limit | No | ||
| since | No | ||
| until | No | ||
| dataset | Yes | drug/drugsfda = approvals; drug/enforcement = recalls; drug/label = labeling | |
| application_number | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, covering the safety profile. The description adds nothing behavioral beyond that – no pagination/limit behavior, no rate-limit or result-count expectations for an open-world search.
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?
A single dense sentence with the resource and its three datasets front-loaded immediately after the verb. No filler and nothing to trim.
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?
Seven parameters with 14% schema coverage and no output schema demand more than one sentence. The description says nothing about result limits/pagination, date-range interpretation, or what a result record contains, leaving several parameters effectively undocumented.
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 14% (just the dataset enum), so the description compensates by naming the filter dimensions: drug, firm, application number, and date. That is real added meaning, but it still leaves the 'limit' parameter and the exact date-range semantics (since/until) unexplained.
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?
States a specific verb (Search) and resource (openFDA) and enumerates the three concrete datasets with their API paths and human-readable meanings. An agent can immediately see this is regulatory/FDA data, cleanly distinct from the clinical-trials siblings.
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?
Usage is only implied: the dataset-to-meaning mapping ('approvals', 'recalls', 'labeling') hints at which source to pick for which question, but there is no explicit when-to-use/when-not-to-use guidance or mention of the clinical-trials siblings as alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
compare_clinical_trialsget_clinical_trialget_trial_changesget_trial_intelligence_briefsearch_clinical_trialssearch_eu_trialssearch_fda_updatesClinical trial search and status from ClinicalTrials.gov
Search ClinicalTrials.gov: find studies, retrieve results, match patients to candidate trials.
Search and analyze ClinicalTrials.gov: trials by keyword/condition/drug/status/phase, one study's…
Search and read ClinicalTrials.gov studies, sites and outcomes.
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