earthquake-mcp-server

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
Most tools have distinct purposes: recent, search, significant, largest, near location, summary, count, and educational info. However, recent, search, and significant all return earthquake lists, and their boundaries could be clearer, though descriptions help differentiate time frames and filters.
Naming Consistency4/5
The naming pattern is mostly consistent with a 'tool_' prefix and a verb_noun structure (e.g., get_recent_earthquakes, search_earthquakes). One outlier is 'earthquakes_near_location' which lacks a leading verb, breaking the pattern slightly.
Tool Count5/5
With 8 tools, the server is well-scoped for an earthquake information service. Each tool covers a distinct query type without overwhelming the user, and there is no redundancy or unnecessary bloat.
Completeness4/5
The tool set covers common earthquake queries: recent, search, significant, largest, near location, summary, count, and educational info. Minor gaps include lack of a tool to fetch details for a specific earthquake by ID, but the current surface is functionally complete for most use cases.
Average 3.3/5 across 8 of 8 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
- 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 disclose behavior but only says 'abrufen' (retrieve). It does not clarify what 'largest' means (e.g., by magnitude), any limitations, or how the years parameter affects results. This leaves significant ambiguity.
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, focused sentence with no redundant content. It is front-loaded and easy to parse.
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?
Despite a full output schema and parameter documentation, the description lacks essential context about the meaning of 'largest' and how it relates to sibling earthquake tools. It is too brief to guide an agent in selecting this tool among the seven alternatives.
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 both limit and years, so baseline is 3. The description adds no additional parameter context, but the parameters are already well-documented in the input schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool retrieves the largest earthquakes of recent years, which is a specific action and resource. It doesn't explicitly distinguish from siblings like 'significant' or 'recent,' but the name and wording imply magnitude-based selection.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 versus siblings such as tool_get_recent_earthquakes or tool_get_significant_earthquakes. There are no alternative recommendations, exclusions, or prerequisites.
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?
With no annotations provided, the description carries the full burden of disclosing behavior. It only states that it retrieves earthquakes and does not mention read-only safety, result format, pagination, or any side effects. This minimal disclosure is insufficient for a tool with multiple parameters and output schema.
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 a single concise sentence that states the core purpose without redundant text. It is well-structured for a simple tool, though it lacks any additional organizational elements like examples or usage notes. This is efficient but minimal.
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?
Given the tool has three parameters and a rich sibling set, the description is too sparse. It does not explain how parameters like min_magnitude or limit affect the result, nor does it provide context on when to choose this over other earthquake tools. The presence of an output schema mitigates return-value explanation, but the overall description is incomplete for effective selection and 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?
The input schema covers 100% of parameters with descriptions and defaults, so the baseline is 3. The description adds no additional parameter semantics beyond what the schema already provides, but it does not need to compensate for any coverage gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'abrufen' (retrieve) and identifies the resource as 'Bedeutende/starke Erdbeben' (significant/strong earthquakes), which clearly distinguishes it from sibling tools like 'get_recent_earthquakes' or 'get_largest_earthquakes'. However, it does not explicitly compare with alternatives, so it doesn't fully separate itself from similar tools.
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 gives no guidance on when to use this tool versus the many sibling tools. It only states the basic function, leaving the agent to infer the appropriate context from the tool name and parameters. No exclusions or alternative references are provided.
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?
There are no annotations, so the description carries the full burden. It only says 'retrieve current earthquakes of the last N hours' and does not disclose behaviors such as result sorting, pagination, or constraints like the maximum hours (168) or default magnitude. No explicit read-only or safety information is provided.
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 one short sentence with no filler. It front-loads the purpose and is appropriately concise for a simple retrieval tool.
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 has an output schema and full parameter descriptions, but the description itself is minimal. It does not explain how this tool differs from the many earthquake siblings or provide richer context such as typical use cases. It is adequate for a basic list tool but leaves gaps in differentiation.
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?
The input schema already covers 100% of parameters with descriptive text (hours, limit, min_magnitude). The description's 'N hours' aligns with the hours parameter but does not add any new meaning beyond what the schema provides. The baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Aktuelle Erdbeben der letzten N Stunden abrufen' clearly states the action (retrieve), resource (earthquakes), and a specific time scope (last N hours). It is specific but does not explicitly distinguish itself from sibling tools like tool_search_earthquakes or tool_get_significant_earthquakes.
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 no guidance on when to use this tool versus alternatives. It does not mention any context for selecting it over sibling tools such as tool_get_earthquake_count or tool_get_largest_earthquakes, leaving usage entirely implicit.
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 of behavioral disclosure. It only states a basic function and does not reveal any behavioral traits such as default limits, pagination, return structure, or that the 'region' parameter is non-filtering. For a search tool with multiple parameters, this is insufficient.
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, concise sentence that is immediately clear and front-loaded. Every word serves a purpose, and there is no fluff or extraneous information.
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?
Although an output schema exists and the schema covers all parameters, the description is quite sparse for a tool with six parameters. It lacks usage guidance, alternative references, and any caveats. It is minimally adequate but leaves the agent to infer much from the schema and tool name.
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 100%, so the schema already documents all six parameters. The description adds only a vague mention of 'date and magnitude' without providing further semantic detail beyond the schema. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: searching earthquakes by date and magnitude. The verb 'suchen' (search) is specific and the resource is named. It doesn't explicitly differentiate from sibling tools, but the general search scope is evident.
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?
There is no guidance on when to use this tool versus alternatives. The description does not mention any prerequisites, exclusions, or mention the sibling tools. A clear context for use is absent.
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 carry the full burden of behavioral disclosure. It only states the basic action and gives no details about output format, result sorting, pagination, or any filtering behavior beyond what the schema implies. This is insufficient for a tool with no annotation support.
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 a single, front-loaded sentence with zero fluff. It is concise and to the point, though it lacks any supplementary structure or additional details. This is efficient but minimal.
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?
Given the tool's simplicity, good schema coverage, and the presence of an output schema, the description is adequate for basic selection. However, it falls short on usage guidelines and behavioral context, making it merely complete enough for simple scenarios but not for nuanced decision-making.
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 100%, so all six parameters have semantic descriptions in the schema. The tool description adds no extra parameter context beyond mentioning coordinates, which is already captured in the schema. The baseline of 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 'Erdbeben in der Naehe eines Ortes (Koordinaten) abrufen' clearly states a specific verb (abrufen) and resource (Erdbeben near coordinates), distinguishing it from siblings like recent or significant earthquakes. This is a precise, non-tautological purpose.
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 no guidance on when to use this tool versus alternatives such as search_earthquakes or get_recent_earthquakes. It lacks any mention of appropriate contexts, exclusions, or preferred alternatives.
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 of behavioral disclosure. It only states the high-level retrieval of a count; it does not explain how optional parameters like end_date or min_magnitude affect the query, whether the time range is inclusive, or what the response shape will be.
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 one short, front-loaded sentence that communicates the core purpose without filler or redundancy. For a simple count endpoint, this is appropriately sized.
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 has a rich schema and an output schema, so returning value details are covered. However, the description lacks usage context and does not differentiate from the seven sibling tools, leaving moderate gaps in decision-making support.
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 clear descriptions for start_date, end_date, and min_magnitude. The tool description adds no additional meaning beyond the schema, so the baseline of 3 applies.
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 'Anzahl der Erdbeben fuer einen Zeitraum abrufen' specifies a clear action (abrufen/retrieve), a concrete resource (Anzahl der Erdbeben/count of earthquakes), and a time-period scope. It is distinct from sibling listing/search tools because it emphasizes the count rather than returning individual earthquakes.
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 no guidance on when to use this tool instead of alternatives such as tool_search_earthquakes or tool_get_seismic_summary. There are no explicit contexts, exclusions, or alternative recommendations.
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 the full burden. It discloses the time window (24h), aggregation by magnitude class, and global scope, but does not explicitly state read-only safety, data source, or update frequency. It is adequate but not rich.
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—three short segments—and front-loaded with the action verb. Every line earns its place without unnecessary 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?
For a zero-parameter tool with an existing output schema, the description sufficiently explains what the tool does and what it returns. It could mention data freshness or whether it is real-time, but given the simple nature, it is complete enough.
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 zero parameters, so the description naturally adds no parameter-specific detail. Per the rubric, a baseline of 4 is appropriate when there are no parameters to document.
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 is specific: it retrieves a seismic summary for the last 24 hours, showing activity levels by magnitude class. This clearly distinguishes it from sibling tools like tool_get_recent_earthquakes, which likely lists individual events rather than an aggregated summary.
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 a summary-use case but does not explicitly state when to use it over alternatives like tool_get_recent_earthquakes or tool_search_earthquakes. No exclusions or alternative mentions are provided, so usage guidance 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?
There are no annotations, so the description carries the full transparency burden. It discloses that the tool returns an explanation of magnitude classes and their effects, but does not mention the nature of the content (e.g., static, source, format). This is moderate transparency for a simple informational tool.
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 three sentences, front-loaded with the core purpose, then provides educational context, and ends with a return summary. It is concise and well-structured, though it slightly repeats the term 'Erklaerung'.
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 (no parameters, output schema present), the description sufficiently covers what it does and returns. It lacks detail about the depth of educational content or format, but the output schema likely handles the return structure, making the description adequate.
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 zero parameters, and the schema coverage is 100% (empty). The description does not need to explain parameters, and the baseline of 4 applies. It appropriately focuses on the returned content.
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 the specific verb 'abrufen' (retrieve) and clearly identifies the resource: explanation of the Richter scale and magnitude classes. It also distinguishes itself from sibling tools that focus on earthquake data queries by stating this is educational content ('Bildungsinhalt').
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 implies usage for obtaining educational information about earthquake magnitudes, as opposed to the data-focused sibling tools. It does not explicitly name alternatives or exclusions, but the context is clear enough for an agent to select it appropriately.
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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