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PopHIVE MCP Server

PopHIVE MCP Server

by Cicatriiz
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

filter_data

Filter public health datasets from PopHIVE by state, date range, age group, and condition.

Instructions

Filter PopHIVE datasets by various criteria (state, date range, demographics)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "dataset": "<dataset>"
    },
    "name": "filter_data"
  }
}

Input Schema

NameRequiredDescriptionDefault
stateNoState code (e.g., CA, TX, NY) or state name
datasetYesDataset to filter
end_dateNoEnd date for filtering (YYYY-MM-DD)
age_groupNoAge group to filter by (e.g., "0-2 years", "18-64", "65+")
conditionNoHealth condition or metric to filter by
start_dateNoStart date for filtering (YYYY-MM-DD)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removedv1.1.0
  3. First observedv1.0.0

TDQS

B3.4/5.0
Behavior2/5

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

No annotations are provided, so the description must cover behavioral traits. It states the tool filters data, but does not mention whether it is read-only, pagination, limits, or side effects. For a filter tool, read-only nature should be explicit.

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 sentence, front-loaded with the main action, and contains no unnecessary words. It is concise and to the point.

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

Completeness2/5

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

Given the tool has 6 parameters (1 required) and no output schema or annotations, the description is minimal. It lacks details on return format, empty results, sorting, or limits. For a filter tool with many optional filters, more context would improve completeness.

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 description coverage is 100%, so all parameters are documented there. The description adds a summary of criteria categories but no additional meaning beyond the schema. Baseline 3 is appropriate.

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 clearly states the action ('filter'), the resource ('PopHIVE datasets'), and examples of criteria ('state, date range, demographics'). It distinguishes from sibling tools like 'compare_states' or 'time_series_analysis' which have different purposes.

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

Usage Guidelines3/5

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

The description implies when to use this tool (for filtering datasets), but does not explicitly compare to siblings like 'search_health_data' or 'get_available_datasets'. No when-not-to-use or alternative guidance is provided.

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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