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HellenicStar Astrology MCP Server

HellenicStar Astrology MCP Server

by qingxiayi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

calculate_davison_chart

Read-onlyIdempotent

Calculate a Davison relationship chart from two people's exact birth data to derive their time-space midpoint chart with real axes, houses, and planetary positions.

Instructions

Davison relationship chart (time-space midpoint chart) for two people with exact birth data: calculates the real physical midpoint in time (UT) and geographic coordinates, casting an independent chart with its own real axes, houses and planetary positions. Supports placidus or whole_sign; orb_profile: greene (default) or tight. 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
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: aspects, chart, midpoint_space_time. Use these exact names.
person_aNo
person_bNo
orb_profileNogreene
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
house_systemNoplacidus

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: aspects, chart, midpoint_space_time. 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

A4.3/5.0
Behavior5/5

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

Annotations already declare read-only, idempotent, non-destructive, and closed-world traits. The description adds valuable context beyond annotations: server checks before results, verification workflow requirements, the fact that psychological interpretations are unchecked, and detailed output truncation behavior for summary mode.

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 description is front-loaded with purpose and follows a logical structure. It is somewhat long but every sentence adds useful information; no redundant fluff. Slight room for tightening, especially the final sentence about verification references.

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?

For a calculation tool with no output schema and moderate annotation coverage, the description provides enough behavioral guidance, workflow steps, and output control details for an agent to use it correctly. Minor gaps exist around exact return format, but overall it is 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?

With only 33% schema description coverage, the description compensates by explaining optional parameters: orb_profile options (greene/tight), house_system (placidus/whole_sign), and the behavior of detail_level=summary and include. It does not detail the BirthInput fields, but core optional param semantics are well covered.

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?

States a specific verb (calculates) and resource (Davison relationship chart, time-space midpoint) with scope details (real physical midpoint in time and geographic coordinates, independent chart). Clearly distinguishes from rendering siblings like render_davison_chart by focusing on calculation rather than rendering.

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?

Implies usage for two people with exact birth data and includes a post-calculation workflow (call verify_calculation_claims). However, it does not explicitly state when to choose this tool over alternatives like calculate_relationship_charts or render_davison_chart, nor does it name any sibling tool.

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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