preflight-mcp

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool covers a distinct preflight information need—airport data, aircraft performance, fuel estimation, NOTAMs, alternates, and weather—with no overlap. The descriptions and names make boundaries clear.
Naming Consistency4/5
Most tools follow a verb_noun pattern (get_, estimate_, find_), but 'aircraft_performance' is a noun-only name, and 'get_metar_taf' uses acronym-heavy naming. Still, the overall style is predictable and readable.
Tool Count5/5
Six tools is well-scoped for a preflight briefing server. Each tool directly maps to a distinct 14 CFR 91.103 requirement, with no redundancy or excess.
Completeness4/5
The server covers the core regulatory preflight items (weather, fuel, alternates, runway lengths, performance, NOTAMs). The only gap is that find_alternates requires the caller to supply candidate airport IDs, so it cannot discover nearby alternates on its own—a minor limitation in an otherwise complete surface.
Average 4/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 5 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under AGPL 3.0.
This repository includes a README.md file.
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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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses a key behavioral trait: the tool does not perform bulk geo-radius search and requires candidateAirportIds. However, it does not describe the return format, how radiusNm interacts with candidate filtering, or the behavior when no candidates meet the weather minima. The mismatch with the schema (candidateAirportIds not marked required) also introduces uncertainty.
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 two sentences, front-loaded with the primary purpose, and the critical caveat is highlighted with 'IMPORTANT.' Every clause adds value, and there is no redundant content.
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?
The tool has 5 parameters, no output schema, and no annotations, yet the description is very brief. It does not explain the return value, how the candidates are evaluated, what radiusNm does, or the outcome if none meet the minima. The regulatory context helps but does not compensate for the operational details needed to use the tool correctly.
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 0%, so the description must compensate. It explains the meaning of minCeilingFt/minVisibilitySm via 'ceiling/visibility' and makes candidateAirportIds a central concept. However, it omits radiusNm entirely and contradicts the schema by stating candidateAirportIds 'must be supplied' while the schema lists only airportId as required. This creates confusion rather than clarity.
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 function: 'Find alternate airports near a given airport that currently meet minimum ceiling/visibility.' It also distinguishes itself from sibling tools by emphasizing the weather-based alternate selection and the regulatory context (14 CFR 91.103(a)). The explicit caveat about no bulk geo-radius search further sharpens its scope.
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 a clear when-to-use signal: satisfying the 14 CFR 91.103(a) requirement to consider alternates. It also gives an explicit usage instruction: 'you must supply candidateAirportIds,' and warns against expecting discovery. It does not mention alternative tools, but the context is sufficient.
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 transparency burden. It discloses that data is 'approximate POH-style performance data' and directs users to warnings for extrapolation caveats. However, it does not explain the impact of variable obstacle height despite mentioning a fixed 50ft obstacle, and it lacks details on output format or edge cases.
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?
Two sentences, no fluff. The first sentence states the core function and aircraft; the second adds regulatory context and a caveat. Every clause earns its place.
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?
For a 7-parameter tool with no output schema and no annotations, the description provides essential context (purpose, aircraft, approximation) but omits units, return structure, and parameter-specific guidance. It is adequate for orientation but not fully complete for an agent to invoke correctly without schema inspection.
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 0%, so the description must compensate, but it only hints at 'operation' and 'obstacleHeightFt' implicitly. It does not explain pressureAltitudeFt, temperatureC, weightLbs, headwindKt, or runwaySurface, leaving 5 of 7 parameters without added meaning beyond their names and constraints.
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 opens with a specific verb 'Compute' and names the exact resource: takeoff or landing ground roll and total distance over a 50ft obstacle for a Cessna 172R/S. This clearly distinguishes it from sibling tools like get_metar_taf or estimate_fuel, which address weather or fuel, not aircraft performance.
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 clearly identifies the context: satisfying 14 CFR 91.103(b) preflight distance requirements. It does not explicitly name alternatives or exclusions, but the regulatory reference makes it clear when this tool is appropriate, and sibling names imply other tools for other needs.
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. It discloses that the tool requires environment variables and returns a clear 'not configured' error if they are unset, rather than silently omitting NOTAMs. This is meaningful behavioral context beyond the schema. It does not mention rate limits or response format, but for a simple fetch operation these are not critical.
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 two sentences, front-loading the main purpose and following with authentication details and failure mode. Each part contributes valuable information, though the inclusion of the registration URL and regulation citation adds slight density. Overall, it is well-structured and concise.
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 single-parameter tool with no output schema, the description provides the core purpose, required credentials, error behavior, and regulatory rationale. It does not detail the success response structure, but that is somewhat implicit. The description covers essential operational details, making it sufficiently complete for an agent to use the tool effectively.
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 0% and the description adds little beyond the parameter name. It only says 'for an airport' without explaining that airportId should be a 4-letter code (e.g., ICAO identifier), providing examples, or clarifying the pattern. This leaves a gap for the agent in constructing valid input 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 a specific action ('Fetch current NOTAMs for an airport'), identifies the resource (NOTAMs), and names the source API (FAA NOTAM Search API). It also adds regulatory context (14 CFR 91.103), which distinguishes this tool from sibling tools like get_metar_taf or get_airport_info.
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 context by referencing the regulatory requirement, implying use during pre-flight information gathering. It also specifies prerequisites (FAA credentials) and failure behavior. However, it does not explicitly mention alternatives or exclusions, so it does not fully meet the 'when not to use' criterion.
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?
With no annotations, the description carries the full burden. It discloses that an error is thrown for unknown airport IDs and implies a read-only operation via 'Fetch'. However, it does not mention data source, units, or any potential side effects, leaving some behavioral aspects undisclosed.
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 two sentences with no fluff. The first sentence front-loads the core function and data, the second adds regulatory context and error behavior. Every sentence adds value without redundancy.
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?
The tool is simple (one parameter, no annotations, no output schema), and the description covers its main purpose and input. However, it does not specify the output format (e.g., units for lengths/elevation, whether multiple runways are returned), which is a gap since no output schema exists to fill that role.
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 only provides a pattern (4 alphanumeric characters) and no description. The tool description adds crucial semantics by specifying 'ICAO' and 'single', clarifying exactly what airportId should represent and how it is constrained, which compensates well for the 0% schema description coverage.
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 uses a specific verb ('Fetch') and clearly states the resource (runway lengths/widths/surfaces and field elevation) for a single ICAO airport identifier. This distinguishes it from sibling tools like get_metar_taf and aircraft_performance, which handle weather and performance respectively.
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 a clear context for use by referencing the 14 CFR 91.103(b) requirement, implying when this tool is appropriate (preflight planning needing runway lengths). It does not explicitly list exclusions or alternatives, but the purpose is specific enough that an agent can infer when to use it over siblings.
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 carries the full behavioral burden. It clearly discloses edge-case behavior (null for missing type, notFound list for absent IDs) and 'Fetch' implies a safe read operation. Omissions like auth or rate limits are less critical here, but explicit response structure is only hinted at.
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?
Two sentences deliver high informational density with the action and scope front-loaded. The second sentence efficiently covers edge cases without redundancy, making every word earn its place.
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?
The tool lacks annotations and an output schema, so the description must provide more context. It covers the core purpose and edge cases but omits the reportTypes parameter behavior, the maxItems limit, and a fuller response structure. This leaves the agent with questions about optional configuration.
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 0%, so the description must compensate. It explains airportIds via 'ICAO airport identifiers' but does not mention reportTypes, which controls whether METAR, TAF, or both are returned. This is a meaningful gap for parameter understanding.
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 opens with 'Fetch decoded current METAR observations and TAF forecasts' which is a specific verb and precise resource, clearly distinguishing it from sibling tools like get_notams or get_airport_info. The added regulatory reference reinforces the purpose without ambiguity.
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 explicitly ties usage to the 14 CFR 91.103(a) preflight requirement, giving a clear context for when to invoke it. However, it stops short of naming alternatives or stating when not to use it, so it earns a 4 rather than a 5.
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. It honestly discloses that this is a 'basic burn-rate x time model (no climb/descent profile),' which is a key limitation. It also states the prerequisite about distance derivation, making the tool's expected inputs and assumptions clear. It doesn't cover all edge cases or output format, but for a calculation tool, the core behavior is transparent.
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 two sentences long, with no redundancy. The first sentence states the primary purpose and regulatory significance; the second sentence discloses the model's simplicity and data prerequisites. Every word earns its place, making it highly scannable.
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 complexity (7 parameters, no output schema, no annotations), the description covers the essential context: what it computes, the simple model type, and how to obtain distance data. It is incomplete regarding detailed parameter relationships (e.g., how flightRules affects reserve) and return value structure, but the provided context is sufficient for a basic understanding and successful invocation.
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 0%, so the description must compensate. It provides some parameter context by mentioning 'burn-rate x time' (linking fuelBurnGph and cruiseSpeedKt) and 'Part 91 reserve fuel' (linking flightRules/reserveMinutesOverride). However, it does not explain individual parameters like taxiFuelGal, usableFuelGal, or reserveMinutesOverride, leaving the agent to infer their roles. It adds value but not full compensation.
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 function: 'Compute trip fuel, Part 91 reserve fuel, and a go/no-go fuel margin for a route.' It uses a specific verb ('Compute') and names the exact resources, distinguishing it from sibling tools focused on airport info, weather, or performance. The regulatory reference adds purpose context without ambiguity.
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 context on how to use the tool: 'Distance per leg must be supplied directly, or derived by the caller from get_airport_info coordinates first.' It also implies the model type (basic burn-rate x time) and notes limitations. However, it doesn't explicitly state when not to use it or compare to alternatives like aircraft_performance, though the description is specific enough to infer.
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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