Vastu Shastra MCP Server by RoxyAPI

Generate Vastu Purusha Mandala - 81 pada and 64 pada grid API

post_vastu_mandala

Read-only

Vastu Purusha Mandala projected over a real plot: send the ground and the API returns every square with the devata holding it, the brahmasthan as a polygon you can draw, the marma points, the six vamsa diagonals named by their devatas and the nine atimarma crossings. Choose the 81 pada Paramasayika or the 64 pada Manduka, and the response says which verses each part rests on. Built for floor plan overlays, practitioner reports and any tool that has to place rooms against the classical grid.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`grid`	No	Which division of the ground to read: 81-pada is the Paramasayika of Brihat Samhita 53.42, the grid the chapter numbers and names every devata on, and 64-pada is the Manduka of 53.55, for which the chapter gives structure only and no devata names. Defaults to 81-pada.	81-pada
`lang`	No	Response language (BCP 47). Supported: en, tr, de, es, hi, pt, fr, ru, zh-Hans, zh-Hant. Defaults to en. Coverage varies by domain, and a field with no translation in the requested language returns English.	en
`plot`	Yes	The ground the mandala is projected over. Send width and depth for a compass-aligned rectangle, or polygon for anything else. The x axis runs east and the y axis north, and the mandala is aligned to the compass rather than to the building.
`compact`	No	Set true for the same data in a compact shape: arrays of same-shaped objects arrive columnar as {"__cols":[names],"__rows":[[values]]}. Lossless, typically 40 to 52 percent fewer tokens.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedSep 6, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds meaningful behavioral detail: it lists what the response contains, including polygons, points, diagonals, crossings, and verse references. It accurately portrays a read-only projection operation without contradicting 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 dense but well-structured, front-loading the core action and returning value before enumerating outputs and use cases. Every sentence earns its place, and the length is appropriate for the tool's complexity.

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?

With no output schema, the description does a good job explaining what the response contains and what the tool is for. It covers the main variants (81-pada vs 64-pada) and the practical use cases, though it avoids details like error conditions or unit behavior, which are partially covered by the schema.

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 the schema already documents every parameter thoroughly. The description reinforces the grid choice and output nature but does not add new parameter semantics beyond the schema.

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

Purpose4/5

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

The description clearly states what the tool does: it projects the Vastu Purusha Mandala over a real plot and returns devata-assigned squares, brahmasthan polygon, marma points, vamsa diagonals, and atimarma crossings. It is specific about the resource and outputs, though it does not explicitly contrast itself with sibling tools like get_vastu_devatas or post_vastu_rooms.

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 gives clear application context: 'Built for floor plan overlays, practitioner reports and any tool that has to place rooms against the classical grid.' It implies when to use this tool but does not explicitly state when not to use it or name alternatives.

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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TDQS

A4.4/5.0

Disambiguation5/5

Each tool targets a distinct resource or analytical step: reference lookups (devatas, directions) are cleanly separated from computations (ayadi, entrance, mandala, plot, rooms, timing), and the list endpoints are distinguished from their _id counterparts by an explicit suffix. Although three post_ tools accept plot geometry, their outputs are mutually exclusive (grid overlay vs. property verdict vs. room-by-room check), and the descriptions state each purpose with enough precision to prevent misselection.

Naming Consistency5/5

All ten tools follow a uniform lowercase snake_case pattern with a get_ or post_ prefix and the vastu domain token consistently in second position. The get_ prefix is reserved for read-only reference data while post_ marks computational endpoints, and the _id suffix uniformly marks single-item lookups, creating a highly predictable scheme.

Tool Count5/5

Ten tools is a well-scoped count for a domain-specific server covering reference data, analysis, and timing. Each tool earns its place: the two list/detail pairs follow standard API practice without redundancy, and the six computational tools each address a distinct stage of Vastu analysis.

Completeness4/5

The tool surface covers the full Vastu consulting workflow: reference data (devatas, directions), land assessment (plot), grid projection (mandala), entrance validation, room placement, dimensional proportion checks (ayadi), and housewarming date selection (griha pravesh). The only notable gap is that timing is restricted to griha pravesh, leaving other Vastu-related muhurta events like construction commencement uncovered.

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