Retrograde MCP

by Griboedow

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct astrological function: incident explanation, risk score, briefing, window finding, lunar phase, planetary status, space weather, historical retrograde periods, and action recommendation. No two tools overlap in purpose.
Naming Consistency4/5
Most tools follow a 'verb_noun' pattern (e.g., get_planetary_status), but 'retrograde_history' reverses the order and 'should_i_do_it' uses a full phrase. This slight inconsistency is minor and does not hinder understanding.
Tool Count5/5
With 9 tools, the server covers the core functionalities for an astrological software advisory service without being bloated or sparse. Each tool serves a clear role.
Completeness4/5
The set covers risk assessment, daily briefings, favorable windows, lunar phases, planetary status, space weather, historical retrograde periods, and action recommendations. Missing perhaps a detailed full report tool, but the existing set is largely complete for the stated purpose.
Average 4.1/5 across 9 of 9 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on April 3, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under Creative Commons Zero v1.0 Universal.
This repository includes a README.md file.
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```
{
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  "maintainers": [
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  ]
}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states data source. It does not disclose behavioral traits such as read-only nature, latency, rate limits, or error handling, leaving significant unknowns.
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 very concise at two sentences plus a list, with the purpose stated first. Every sentence adds value, including the Kp-index scale and data source, with no wasted words.
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 simple no-param tool that returns the Kp-index, the description is reasonably complete: it explains what the tool returns and its interpretation. The presence of an output schema likely covers return format. Minor lack of tie-in to sibling tools.
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?
There are no parameters, and schema description coverage is 100% trivially. The baseline is 4 for zero parameters, and the description adds no extra param info, which is acceptable.
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 fetches the current planetary Kp-index from NOAA SWPC, a specific verb-resource combination. It distinguishes from sibling tools like get_lunar_phase by focusing on geomagnetic activity.
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 guidance is provided on when to use this tool vs alternatives. The description explains Kp-index levels but does not mention situations favoring this tool over siblings like get_daily_briefing or get_cosmic_risk_score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full burden. It discloses score components, data sources, and parameter behavior but does not mention side effects, permissions, rate limits, or error handling for missing data. The phrase 'when NOAA data is available' hints at conditional behavior but without stating fallback.
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 concise, front-loaded with the purpose, uses bullet points for readability, and every sentence adds value. It provides a clear structure without redundancy.
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?
The description explains the score components and data sources thoroughly. However, it does not summarize the output format (even though an output schema exists) and omits potential error conditions for unavailable data. Despite this, it is largely complete for the tool's complexity.
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?
The input schema has 0% coverage for the date parameter, but the description explains its ISO 8601 format, optionality, and default behavior, adding significant meaning beyond the schema's minimal definition.
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 composite cosmic risk score from 0 to 100, lists the components and data sources, and distinguishes it from sibling tools that focus on individual factors or actions.
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 obtaining a risk score, but it does not explicitly state when to use this tool versus alternatives like get_lunar_phase or get_planetary_status. No when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses key behaviors: references current planetary positions, constructs a causally coherent cosmic narrative, and maintains a professionally grave tone. It does not mention whether the tool is read-only or has side effects, but given the nature (analysis), this is reasonable. A 4 reflects good disclosure for an analysis tool.
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 succinct with three sentences and an Args section. The first sentence immediately states the purpose. Every part contributes value: purpose, planetary references, tone, and parameter doc. No redundant or unnecessary text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 required param, no nested objects) and the presence of an output schema, the description covers all essential aspects: purpose, parameter meaning, and behavioral traits. It does not need to explain return values because an output schema exists. The description is fully complete for the context.
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?
The description includes a docstring for the 'description' parameter: 'A description of the incident, outage, or anomaly.' This adds meaning beyond the input schema, which only provides type and title. With schema description coverage at 0%, the description effectively compensates by clarifying parameter usage.
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's action: 'Receive an incident or outage description and return a rigorous astrological root-cause analysis.' It specifies the verb (receive/return), resource (incident/outage description), and output (astrological analysis). This differentiates it from sibling tools like get_cosmic_risk_score or get_daily_briefing, which serve different purposes.
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?
The description does not provide guidance on when to use this tool versus its siblings. It implies use for incident descriptions but offers no exclusions, prerequisites, or comparisons to the 8 sibling tools. This lack of usage context reduces its helpfulness for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden for behavioral disclosure. It mentions data sources but does not disclose any behavioral traits such as rate limits, authentication requirements, or side effects. This is insufficient for a tool with no annotation coverage.
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 very concise with three sentences, each adding value. It is front-loaded with the tool's purpose and efficient in conveying essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and the existence of an output schema, the description adequately covers the tool's functionality and data sources. It is complete for a no-parameter tool.
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?
The tool has no parameters, so the baseline score of 4 applies. The description does not need to add parameter meaning since there are none.
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 it generates a 'morning cosmic standup' summarizing astrological conditions for software teams, listing covered aspects (planetary status, lunar phase, space weather, risk score, recommendation). It distinguishes itself from sibling tools that provide individual components.
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 provides context (morning, for software teams) implying when to use it, but does not explicitly state when not to use it or mention alternatives. It gives clear usage context without exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral disclosure burden. It mentions the use of 'NASA JPL DE421 ephemeris' and that the maximum years is 10, which adds validity. However, it does not discuss error handling, performance, or what happens when no records are found.
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 concise, front-loaded with purpose, and structured with an Args section. Every sentence contributes value: purpose, use case, and parameter details. No redundant or filler content.
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 that an output schema exists, the description does not need to explain return values. Parameters are thoroughly described, and behavioral info like ephemeris source is provided. Minor gaps exist (e.g., no mention of error responses), but overall completeness is high for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description fully compensates by detailing each parameter. For 'planet,' it lists accepted values and default. For 'years,' it explains the meaning, default, and maximum. This adds significant meaning beyond the bare schema.
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 'Return all retrograde periods for a given planet over the last N years.' This specifies the verb (return), resource (retrograde periods), and scope (last N years). It distinguishes from siblings like 'get_favorable_window' and 'get_planetary_status' by focusing on historical periods.
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 suggests using the tool for 'overlaying against your deployment history to discover correlations,' providing a clear use case. However, it does not explicitly state when not to use it or mention alternatives among siblings, leaving the decision partially implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explains the recommendation is based on planetary motion, lunar phase, and Kp-index, with data sources from NASA and NOAA. It mentions optional date with default. However, it does not disclose the output format or any potential limitations, though annotations are absent.
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 well-structured with a clear first sentence stating purpose, followed by examples, data sources, and parameter details. Each part earns its place without unnecessary verbosity.
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 the tool's simplicity and that an output schema exists, the description covers input parameters and methodology adequately. It lacks mention of any prerequisites or domain limitations, but overall is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has no descriptions (0% coverage), but the description compensates fully: for 'action', it says 'Be specific' with examples; for 'date', it specifies ISO 8601 format and default behavior. This adds significant meaning.
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 it provides a yes/no astrological recommendation for a specific action, using specific verbs and resource. Examples and data source details distinguish it from sibling tools like get_cosmic_risk_score or get_favorable_window.
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?
The description provides examples of actions but offers no explicit guidance on when to use this tool versus sibling tools like get_favorable_window or get_cosmic_risk_score. There is no mention of when not to use it or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses data source (JPL DE421 ephemeris), output content (longitude, speed, domains, interpretation), and optional date format. It is transparent about what each entry includes, though the mention of 'domains of responsibility in software development' may be confusing.
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 well-structured with a clear opening sentence, details, and data source attribution. It is slightly verbose but each sentence adds value; could be slightly more concise without losing clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists, the description appropriately explains what each planet entry includes (longitude, speed, etc.). It covers parameter semantics, data source, and scope, making it complete for selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'date' is fully described: ISO 8601 format, optional, defaults to current date if not specified. Although schema description coverage is 0%, the description compensates completely.
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 returns motion status of all tracked planets (Mercury through Neptune) with details like ecliptic longitude and speed. It distinguishes from sibling tools like 'retrograde_history' or 'get_lunar_phase' by focusing on planetary status.
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 explains the optional date parameter and default behavior but does not explicitly state when to use this tool versus similar siblings. Usage context is implied through the tool's focus on planetary motion, but no when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses data source (NASA JPL DE421 via Skyfield), default behavior (current date if not specified), and the type of output (illumination percentage and interpretation). This is good transparency for a read-only tool.
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 concise (7 short sentences) with a clear structure: purpose, phase interpretations in bullet format, data source, and parameter documentation. Every sentence adds value, no redundancy.
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 the presence of an output schema (not shown), the description appropriately focuses on inputs and purpose. It covers parameter, data source, and phase meanings, but could add brief mention of error handling or return format expectations.
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?
The schema provides no description for the date parameter (0% coverage), but the description compensates by specifying it is optional, ISO 8601 format, and defaults to current date/time. This adds necessary meaning beyond the schema.
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 explicitly states it returns 'lunar phase with illumination percentage and a software development interpretation', with specific phase meanings. This clearly distinguishes it from sibling tools like get_planetary_status or get_cosmic_risk_score.
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 provides contextual usage guidance through phase interpretations (e.g., 'New Moon → poor time for deployments'), implying when to use. However, it lacks explicit when-not-to-use or direct comparison with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of transparency. It discloses that the tool uses real JPL ephemeris data, searches a 90-day range, and defines favorable conditions. It does not mention what happens if no window is found, but overall it provides good behavioral context beyond the schema.
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 well-structured and concise: a headline sentence, bullet-point criteria, followed by details on search range and data source, then parameter documentation. Every sentence adds value, and key information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with an output schema (not shown) and 2 parameters, the description covers all essential aspects: purpose, criteria, search range, data source, and parameter details. It is complete enough for an agent to understand when and how to invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description must add meaning. It clearly explains each parameter: max_retrograde_planets (maximum tolerated, default 1) and start_date (optional, ISO 8601 format, defaults to now). This adds significant value beyond the schema's type and default values.
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's purpose: 'Find the next calendar window where cosmic conditions are relatively favorable for deployments and major technical decisions.' This verb+resource combination is specific and distinguishes it from sibling tools like get_cosmic_risk_score or get_daily_briefing.
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 explains when to use the tool (for deployments and major technical decisions) and details the qualifying criteria (max retrograde planets, moon phase). However, it lacks explicit exclusions or comparisons to alternatives, such as when to prefer get_cosmic_risk_score instead.
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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