Memory Cache MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: clear_cache removes entries, get_cache_stats provides metrics, retrieve_data fetches data, and store_data saves data. There is no overlap or ambiguity between these four operations.
Naming Consistency3/5The naming is mixed: clear_cache and get_cache_stats follow a verb_noun pattern, but retrieve_data and store_data use a verb_object pattern. While readable, this inconsistency in structure (cache vs. data as the object) deviates from a uniform convention.
Tool Count5/5With 4 tools, this is well-scoped for a memory cache server. It covers the essential operations (store, retrieve, clear, stats) without being overly sparse or bloated, making each tool necessary and focused.
Completeness4/5The toolset covers core cache operations: storing, retrieving, clearing, and monitoring. A minor gap is the lack of an update or delete specific entry tool, but agents can work around this by using clear_cache for deletion and store_data for updates, so it's mostly complete.
Average 2.7/5 across 4 of 4 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
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- No high-severity vulnerability alerts
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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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Get cache statistics' implies a read-only operation, but it doesn't specify what the statistics include, whether they're real-time or aggregated, if there are rate limits, or what permissions might be required. The description lacks details on return format, potential side effects, or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise ('Get cache statistics'), which could be efficient if it were more informative. However, it's under-specified rather than appropriately concise—it lacks necessary details about what statistics are retrieved. While it's front-loaded, it doesn't earn its place by adding sufficient value beyond the tool name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete for a tool that likely returns complex statistical data. It doesn't explain what the cache statistics include, how they're formatted, or any behavioral nuances. For a tool with no structured metadata, the description should provide more context to help an agent understand its functionality and output.
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 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter information, which is appropriate here. A baseline of 4 is applied for zero-parameter tools, as the description doesn't need to compensate for any gaps in schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get cache statistics' is a tautology that essentially restates the tool name 'get_cache_stats' without adding meaningful specificity. It doesn't distinguish what kind of statistics are retrieved (e.g., hit rates, memory usage, entry counts) or how they differ from what might be available through sibling tools like retrieve_data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 doesn't mention when it's appropriate to get cache statistics (e.g., for monitoring, debugging, or performance analysis) or how it relates to sibling tools like clear_cache, retrieve_data, or store_data. There's no indication of prerequisites or exclusions.
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. It states the tool retrieves data, implying a read-only operation, but doesn't disclose behavioral traits like error handling (e.g., what happens if the key doesn't exist), performance aspects, or any side effects. The description is minimal and lacks critical operational details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words, making it front-loaded and easy to parse. However, it's overly concise to the point of under-specification, which slightly reduces its effectiveness. Every word earns its place, but more detail could improve clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no annotations and no output schema, the description is incomplete. It doesn't explain what the retrieved data looks like, potential return values, or error conditions. For a retrieval tool with one parameter, more context is needed to guide effective use, making this description inadequate.
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 has 100% description coverage, with the 'key' parameter clearly documented. The description adds no additional meaning beyond the schema, such as examples of key formats or constraints. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action ('retrieve') and resource ('data from the cache'), which is clear but basic. It doesn't distinguish this tool from its sibling 'get_cache_stats', which might also retrieve cache-related information. The purpose is understandable but lacks specificity about what type of data or scope is involved.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 like 'store_data' or 'clear_cache'. It doesn't mention prerequisites, such as needing data to be cached first, or context for when retrieval is appropriate versus other cache operations. Usage is implied but not explicitly stated.
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, the description carries full burden but provides minimal behavioral insight. It implies a destructive action ('clear') but doesn't disclose permanence, side effects (e.g., performance impact), permissions required, or error handling. For a mutation tool, this leaves critical gaps in understanding its behavior.
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, efficient sentence with zero waste. It's front-loaded with the core action and scope, making it easy to parse quickly. No extraneous details or repetition are present.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive tool with no annotations and no output schema, the description is incomplete. It lacks information on permissions, side effects, return values, or error cases. Given the complexity of cache operations and the absence of structured safety hints, more context is needed for safe and effective use.
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 description coverage is 100%, so the schema already documents the optional 'key' parameter. The description adds marginal value by implying the scope ('specific or all'), but doesn't explain key formats, validation, or default behavior beyond what's in the schema. Baseline 3 is appropriate given high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('clear') and resource ('cache entries'), specifying it can target 'specific or all' entries. It distinguishes from siblings like 'get_cache_stats' (read-only) and 'retrieve_data' (data access), but doesn't explicitly differentiate from 'store_data' (which might involve cache updates).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives is provided. The description doesn't mention prerequisites (e.g., admin rights), typical scenarios (e.g., after data updates), or when to avoid it (e.g., during high traffic). It merely states what it does without contextual usage advice.
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 full burden for behavioral disclosure. It mentions 'optional TTL' which hints at expiration behavior, but doesn't describe what happens when data is stored (e.g., overwrites existing keys, requires specific permissions, has size limits, or returns confirmation). For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
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 extremely concise with a single sentence that communicates the core purpose and one key feature (optional TTL). Every word earns its place with no redundancy or unnecessary elaboration. It's front-loaded with the main action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what happens after storage (success/failure indicators), whether the operation is idempotent, what errors might occur, or how it interacts with sibling tools. The 100% schema coverage helps with parameters, but behavioral context is lacking.
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 description coverage is 100%, so the schema already documents all three parameters thoroughly. The description adds minimal value beyond the schema by mentioning 'optional TTL', but doesn't provide additional context about parameter usage, constraints, or best practices. This 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.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Store data') and target ('in the cache'), which is specific and unambiguous. It distinguishes from sibling tools like 'retrieve_data' (read vs. write) and 'clear_cache' (store vs. delete). However, it doesn't explicitly mention what type of cache or differentiate from 'get_cache_stats' beyond the basic verb distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 like 'retrieve_data' or 'clear_cache'. It mentions optional TTL but doesn't explain when TTL should be applied or any prerequisites for usage. There's no context about when this tool is appropriate versus other storage methods.
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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