Skip to main content
Glama

BaZi / Korean Saju MCP (Four Pillars)

Server Details

Deterministic Korean Saju / Chinese BaZi Four Pillars MCP server. Heavenly Stems, Earthly Branches, Day Master, five-element distribution, and 0-100 compatibility. No AI, no API key.

If you are the author of this connector, you can claim ownership with GitHub, an HTTP challenge, or a DNS record. Claimed connector authors can inspect health checks, view analytics, and manage their listing.
Status
Healthy
Last Tested
Transport
Streamable HTTP
URL

TDQS

A3.7/5.0
Disambiguation5/5

The two tools have clearly distinct purposes: bazi_chart computes a single person's chart, while bazi_compatibility evaluates compatibility between two people. No overlap in functionality.

Naming Consistency5/5

Both tools follow a consistent 'bazi_' prefix with underscore-separated descriptive nouns (chart, compatibility), forming a clear and predictable naming pattern.

Tool Count3/5

With only 2 tools, the server feels slightly thin for a full 'Four Pillars' server, though it covers core chart computation and compatibility. A typical server of this scope might include 3-5 tools.

Completeness2/5

The server lacks tools for interpreting the chart, analyzing element relationships, or providing detailed profiles beyond the raw chart and a compatibility score. This leaves significant gaps in the expected lifecycle.

Available Tools

2 tools
bazi_chartAInspect

Compute a deterministic BaZi (八字) / Korean Saju (사주) Four Pillars chart from a solar birth date: Heavenly Stems, Earthly Branches, Day Master, and five-element distribution. KASI-validated engine, no AI.

ParametersJSON Schema
NameRequiredDescriptionDefault
dayYes
hourNo0–23, or -1 if birth time unknown
yearYes1920–2050
monthYes
genderYes

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It adds behavioral context by stating 'deterministic' and 'KASI-validated engine, no AI', but lacks details on error handling, side effects, or rate limits.

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, front-loaded sentence that efficiently conveys the tool's purpose without unnecessary words.

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

Completeness3/5

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

There is no output schema, so the description should detail return values. It lists components but not their format. Parameter details are lacking, and no comparison with the sibling tool is provided.

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

Parameters2/5

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

Schema description coverage is low (40%). The description mentions 'solar birth date' but does not explain individual parameters like hour (0–23 or -1), gender (M/F), or the year range. It adds little beyond the schema definitions.

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 states a specific verb 'compute', the resource 'BaZi chart', and lists output components (Heavenly Stems, Earthly Branches, Day Master, five-element distribution). It clearly distinguishes from the sibling tool 'bazi_compatibility'.

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 usage for computing a BaZi chart from a solar birth date, but does not explicitly state when to use this tool vs. the sibling 'bazi_compatibility' or provide any exclusions.

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

bazi_compatibilityAInspect

Deterministic BaZi compatibility score (0–100) and band between two people, from combined five-element balance and Day Master cycle relation.

ParametersJSON Schema
NameRequiredDescriptionDefault
person_aYes{year,month,day,hour,gender}
person_bYes{year,month,day,hour,gender}

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description must disclose all behavioral traits. It mentions the tool is 'deterministic' and explains the computation basis, but does not cover error conditions, authentication needs, or output structure beyond score and band. This is a moderate disclosure.

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 that efficiently conveys the core purpose and methodology. Every word adds value with no redundancy or filler.

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 no output schema or annotations, the description adequately explains the tool's output (score and band) and logic. However, it omits details about the band interpretation, input validation, and return format. It is nearly complete but leaves minor gaps.

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% with descriptions for person_a and person_b as '{year,month,day,hour,gender}'. The description adds only that these are for two people, without specifying format or constraints. It adds little meaning beyond the schema, thus 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 tool computes a BaZi compatibility score (0–100) and band between two people, using five-element balance and Day Master cycle relation. It specifies the verb (compatibility), resource (BaZi), and output, distinguishing it from the sibling bazi_chart.

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 use for compatibility assessment but provides no explicit guidance on when to use this tool versus the sibling bazi_chart. There is no mention of prerequisites or alternatives, leaving the agent to infer usage context.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 2 tool updates
    • First observedbazi_chart
    • First observedbazi_compatibility

Frequently Asked Questions

Discussions

No comments yet. Be the first to start the discussion!

Related MCP Servers

  • A
    license
    Not graded
    quality
    D
    maintenance
    Enables detection and analysis of pre-public product launches through web search, content extraction, AI-powered scoring, and automated alerting. Provides comprehensive tools for surfacing stealth startup signals before they trend publicly.
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Browse IndustryLens's published competitive-intelligence reports and head-to-head competitor comparisons from any AI agent — real, source-backed data.
    MIT
  • A
    license
    Not graded
    quality
    C
    maintenance
    Enables AI chat clients to perform market research and competitive intelligence by gathering company overviews, competitor lists, product portfolios, pricing snapshots, and recent news via live Tavily search.
    MIT
Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources