aprs-mcp
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: sending messages, looking up positions, finding nearby stations, streaming raw packets, and listing commands. There is minimal overlap between these operations.
Naming Consistency3/5All tools share the 'aprs_' prefix, but the pattern is inconsistent: some use verb_noun (send_message), some are bare verbs (listen), and others are nouns or adjectives (position, nearby). The naming is readable but does not follow a single consistent convention.
Tool Count5/5With 5 tools, the server is well-scoped for its purpose. Each tool serves a distinct APRS-related function, and the count is neither overwhelming nor too sparse.
Completeness4/5The toolset covers key APRS operations: sending messages, retrieving positions, discovering nearby stations, and listening to filtered packet streams. Missing advanced features like weather data or route history are minor gaps that do not impede core workflows.
Average 3.8/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 4 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 MIT License.
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
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry behavioral transparency. It mentions a 'fixed duration' but does not disclose blocking behavior, early termination via max_packets, or any side effects. This is a minimal disclosure that leaves significant room for clarity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no redundant words. It efficiently conveys the core purpose, earning a perfect score for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The output schema exists and parameters are fully described in the schema, but the description lacks behavioral context (e.g., blocking, stopping conditions) and usage guidance relative to siblings. It is minimally viable but has gaps in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides 100% parameter coverage, including default values and examples for filter_text. The description adds nothing beyond the schema, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Stream' and identifies the resource as 'packets matching an APRS-IS filter string'. This distinguishes it from siblings like aprs_send_message or aprs_position, 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 Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a streaming/monitoring use case but does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions or prerequisites. Sibling tools exist but are not referenced.
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 present, so the description carries the full behavioral burden. It only states that it sends via APRS-IS, omitting side effects, authentication requirements, rate limits, or what happens on failure. For a mutation tool, this is a notable gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no filler. It is front-loaded with the key action and resource, making it extremely easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter tool with an output schema, the description adequately states the core operation, but it lacks usage guidance and behavioral transparency. It is minimal but not fully self-contained, especially given the absence of annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides full descriptions for both parameters, including a max length hint and an example callsign. The description adds no parameter-specific detail beyond what the schema covers, so it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies the verb 'Send' with a clear resource: 'an APRS message to another callsign via APRS-IS.' This clearly distinguishes it from sibling tools like aprs_listen, aprs_position, and aprs_nearby.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for sending APRS messages but provides no explicit when/when-not guidance or alternatives. Sibling tool names offer context, but the description itself does not distinguish when this tool should be preferred over them.
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 must convey behavior. It states a read operation ('List') but does not disclose details such as the timeout-based collection behavior (via the 'timeout' parameter), potential no-data scenarios, or any network/rate considerations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
A single, focused sentence that conveys the core function without unnecessary words. Fully front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With a full input schema and an output schema present, the description provides enough for basic invocation. However, it lacks explicit usage guidance and behavioral caveats, making it slightly above average but not fully comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes all parameters with 100% coverage. The description adds no extra semantic meaning beyond the schema, such as clarifying interaction between radius and timeout, so it meets the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'List' with a clear resource ('APRS stations') and a precise scope ('within a radius of a latitude/longitude'), which distinguishes it from sibling tools like aprs_send_message or aprs_listen.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for finding nearby stations but provides no explicit guidance on when to use it instead of the sibling tools (e.g., aprs_position or aprs_cmd_list). The usage context is only implicit.
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 full burden. It states the tool 'lists' tools, implying a read-only operation with no side effects, but it does not explicitly disclose safety characteristics or provide context about what happens when invoked. For a simple listing tool, this is adequate but not exceptional.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that directly conveys the tool's purpose with no superfluous words. It is perfectly sized for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's trivial nature (no parameters, clear purpose, and an output schema), the description is complete enough. It fully explains what the tool does, and the output schema handles return value documentation. There is no ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so the baseline for parameter semantics is 4. The description does not need to add parameter information beyond what the schema provides, and it correctly omits any parameter details that would be irrelevant.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'List' and identifies the resource 'APRS tools exposed by this MCP server.' This clearly distinguishes it from sibling tools that perform APRS operations (send, position, nearby, listen).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for discovering available tools but does not explicitly state when to use it or mention alternatives. Unlike the TDQS 4.3 example, there is no explicit exclusion or alternative reference. However, the tool's purpose is self-evident, so an agent can infer when to invoke it.
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 the API-first behavior, fallback to APRS-IS stream listening, and dependency on the timeout parameter for the fallback path. This is meaningful context that helps the agent anticipate latency or failure modes. Minor omission: what happens if the API is configured but fails.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: one clear purpose sentence plus two sentences for the fallback logic. Front-loaded with the main action, no filler or redundant detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter tool with complete schema coverage and an output schema, the description adequately explains the core behavior, fallback logic, and timeout edge case. A slight ambiguity about API failure fallback prevents a 5, but overall it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters. The description adds contextual color about the timeout in the stream-listening mode, but it does not introduce meaning beyond what the schema already states. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Look up') and resource ('last known position(s) of a callsign'), clearly distinguishing it from sibling tools like aprs_send_message or aprs_listen. The first sentence fully captures the tool's function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use the tool (when you need a callsign's last known position) and provides context about the two execution modes based on APRSFI_API_KEY configuration. It does not explicitly name alternatives, but the overview makes the use case obvious.
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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- Evaluate tool definition quality.
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