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clinicaltrialsgov-mcp-server

Clinicaltrials Find Eligible

clinicaltrials_find_eligible
Read-onlyIdempotent

Match patient demographics and conditions to eligible recruiting clinical trials based on age, sex, conditions, and location.

Instructions

Match patient demographics and conditions to eligible recruiting clinical trials. Provide age, sex, conditions, and location to find studies with matching eligibility criteria, contact information, and recruiting locations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ageYesPatient age in years.
sexYesPatient's biological sex. Use 'ALL' to include studies regardless of sex restrictions.
conditionsYesMedical conditions or diagnoses. E.g., ["Type 2 Diabetes", "Hypertension"]. Plain words only — reserved chars `[ ] ( ) ,` inside an entry will fail.
locationYesPatient location as `{ country (required), state?, city? }`. Country is required; state/city narrow the match. For radius-based geographic search, use clinicaltrials_search_studies with geoFilter.
healthyVolunteerNoWhether the patient is a healthy volunteer. When true, only studies accepting healthy volunteers are queried.
recruitingOnlyNoOnly include actively recruiting studies.
maxResultsNoMaximum results to return.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
studiesYesMatching studies with eligibility and location fields.
totalCountNoTotal matching studies from the API.
searchCriteriaYesSearch criteria used.
funnelYesMatch counts at each filter stage. Diagnoses where the funnel collapsed on sparse results — e.g., conditionMatched=298 but demographicsMatched=2 means age/sex/status are the constraint.
noMatchHintsNoHints when no studies match, with suggestions to broaden the search.
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare read-only, idempotent, and open-world hints. The description adds that the tool returns matching trials with contact information and recruiting locations, providing moderate extra context beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that front-loads the primary purpose and lists key inputs and outputs. Every word earns its place, with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (7 parameters, nested object, output schema), the description adequately conveys the tool's function and output. It could briefly mention default filtering for recruiting studies (recruitingOnly=true), but the schema already provides that information.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the input schema already describes all parameters thoroughly. The description merely lists a subset of parameters (age, sex, conditions, location) without adding significant semantic detail beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the tool matches patient demographics to eligible recruiting clinical trials, clearly distinguishing it from sibling tools like clinicaltrials_search_studies which likely perform general study searches without patient-specific matching.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly indicates when to use this tool: to find trials matching a patient's age, sex, conditions, and location. It does not explicitly state when not to use it or provide alternatives, but the context suggests it is for patient-centric eligibility matching.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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