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astroway-mcp

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by astroway

MCP Multi-Chart Context

astroway_mcp_multi_chart_context
Read-only

Generates compact context for multiple natal charts, enabling AI agents to analyze compatibility, family dynamics, group interactions, or forecasts across up to six charts.

Instructions

Compact context for MCP agents working across multiple charts.

[Group: AI & MCP] [Endpoint: POST /v1/mcp/multi-chart-context] [Required: charts] [Cost: 10 credits (Tier 1)]

Input Schema

NameRequiredDescriptionDefault
chartsYes
intentNo

Output Schema

NameRequiredDescriptionDefault
notesNo
intentNo
summariesNo
chartCountNo
contextHashNo
summaryStringNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.6.0

TDQS

C2.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=true, so the safety profile is covered. The description adds two genuinely useful non-schema facts — the POST endpoint and the 10-credit (Tier 1) cost — but says nothing about what the returned context contains, how many charts get combined, or how truncation/compaction works.

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 sentence is front-loaded and the remaining lines are terse key-value metadata (group, endpoint, required, cost) with no filler. Nothing is wasted, though the brevity is partly under-specification rather than discipline.

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?

For a multi-chart orchestration tool accepting 1-6 natal chart objects with a shaping 'intent' parameter, the description omits how intent changes the result and what 'compact' means in practice. The existence of an output schema removes the need to describe return shape in detail, but the intent semantics and multi-chart behavior remain unexplained.

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?

The description only echoes "Required: charts," which the schema already enforces. The nested chart object is well documented in the schema, but the top-level 'intent' enum (compatibility / family / group / forecast) has no description anywhere, and the description does not explain what each intent does to the output — the one place prose would add real value.

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

Purpose2/5

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

The sentence "Compact context for MCP agents working across multiple charts" restates the title (MCP Multi-Chart Context) and names no concrete operation or resource. "Context" is undefined — an agent cannot tell whether this returns chart summaries, comparison data, or placement tables. Only the word "multiple" distinguishes it from the hundreds of single-chart siblings.

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

Usage Guidelines2/5

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

No when-to-use guidance is given. Nothing routes the agent between this tool and obvious candidates such as astroway_relational_synastry, astroway_relational_group_synastry, or astroway_mcp_ai_comparison_coach. The metadata lines state a required field and a credit cost, but never a selection condition.

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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