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HellenicStar Astrology MCP Server

HellenicStar Astrology MCP Server

by qingxiayi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

search_birthplace

Read-onlyIdempotent

Search birthplace candidates to retrieve canonical location IDs, regions, and timezones, so astrology calculations use verified locations instead of ambiguous place names.

Instructions

Search birthplace candidates and return canonical location IDs, regions and timezones. If supplied by the user, include country/state as City, Country or City, State, Country. One exact database-name match within an explicitly supplied verified region uses next_action=use_location_id; use it and state the selected city without asking again. next_action=ask_user means unresolved candidates: ask for the missing region or city/district choice, unless that exact location_id was already confirmed. Never choose by population or list order. Server checks run before successful results are returned. Before interpreting this data, call verify_calculation_claims with its unchanged calculation_reference and draft source-field claims. Correct contradicted facts and reverify before the final answer. Psychological interpretations are not checked. Optional detail_level=summary previews object/nested rows (up to five), preserves complete scalar membership lists, and marks truncation; include selects top-level content fields. Omit both for the original full result. Verification references always identify the complete checked calculation.

Input Schema

NameRequiredDescriptionDefault
queryYes
includeNoOptional 1-30 top-level content field names, each 1-80 characters. Omit to return all content. Control/provenance fields remain; unknown or control field names return invalid_input with available_fields. Known selectable fields: options. Use these exact names.
detail_levelNofull returns complete calculation content. summary previews up to five object/nested rows per list, preserves scalar membership lists, and reports omitted counts. References still identify the full calculation.full

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.7
    • changedInput schema / properties / include / description
      Previous value: -"Optional 1-30 top-level content field names, each 1-80 characters. Omit to return all content. Control/provenance fields remain; unknown or control field names return invalid_input with available_fields."New value: +"Optional 1-30 top-level content field names, each 1-80 characters. Omit to return all content. Control/provenance fields remain; unknown or control field names return invalid_input with available_fields. Known selectable fields: options. Use these exact names."
  2. Changed2 schema fields changed
    • addedInput schema / properties / detail_level / description
      Added value: +"full returns complete calculation content. summary previews up to five object/nested rows per list, preserves scalar membership lists, and reports omitted counts. References still identify the full calculation."
    • addedInput schema / properties / include / description
      Added value: +"Optional 1-30 top-level content field names, each 1-80 characters. Omit to return all content. Control/provenance fields remain; unknown or control field names return invalid_input with available_fields."
  3. First observedv0.1.0

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the readOnly/idempotent/non-destructive annotations, the description discloses next_action semantics, that server checks run before successful results are returned, that verification must happen before interpreting data, and how summary mode truncates nested rows while preserving scalar lists and verification references. These are substantive behavioral details an agent needs.

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

Conciseness4/5

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

The purpose is front-loaded and every major clause carries practical instructions. It is dense and somewhat run-on, with several workflow concepts packed into one block, and the line about psychological interpretations feels tangential to a birthplace search, but it is not padded.

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?

There is no output schema, and the description provides enough to interpret next_action, understand summary truncation, and know verification references always point to the complete calculation. It still leaves some details implicit, such as matching behavior, result limits, and pagination, so it is strong but not fully complete.

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

Parameters4/5

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

Schema coverage is 67%, and the description adds important query formatting guidance ('City, Country' or 'City, State, Country') as well as interaction rules for exact matches within verified regions. It also explains include and detail_level behavior, though much of that overlaps with the schema descriptions.

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 begins with a specific verb and resource: 'Search birthplace candidates and return canonical location IDs, regions and timezones.' This clearly distinguishes the tool from chart-rendering and calculation siblings, and it states what the tool returns.

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?

It gives explicit handling for next_action=use_location_id and next_action=ask_user, including not asking again when a location ID is confirmed, and it warns never to choose by population or list order. It does not explicitly compare this tool against resolve_birth_coordinates or other alternatives, which keeps it from a 5.

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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