Context Memory MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool targets a distinct action: recording failures, recording solutions, searching, and exporting. The descriptions clearly differentiate the purposes, so selection ambiguity is low.
Naming Consistency2/5The tool names use mixed conventions: 'recall' and 'promote' are verbs, while 'mistake' and 'learned' are nouns/past participles. There is no consistent verb_noun pattern, making it harder to predict tool behavior from the name.
Tool Count5/5Four tools is well-scoped for a memory/learning management server, covering the core operations without excessive fragmentation.
Completeness3/5The server covers recording (mistakes/learnings), recall, and promotion to permanent storage, but lacks update and delete operations for managing existing memories. This leaves a notable gap for correcting or removing outdated information.
Average 3/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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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 provided, the description carries the full burden of behavioral disclosure. It only states 'Record' which implies a write operation, but gives no details on side effects, persistence, idempotency, return values, or required permissions. The purpose clause ('so you don't repeat it') is motivational, not behavioral.
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 filler or repetition. Every word contributes meaning. It is appropriately sized for a simple recording tool, though it could benefit from more context without becoming bloated.
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 4 parameters (3 required) and no output schema or annotations, the description is too sparse to provide complete context. It does not mention the required input fields, any side effects, or how this integrates with sibling tools. The agent is left to infer most operational details from the schema alone.
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% parameter description coverage, so the baseline is 3. The tool description does not add any parameter-specific meaning, but it also does not conflict with the schema. The schema already explains 'what', 'why', 'tags', and 'files' adequately.
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 ('Record') and the target resource ('something that failed'), plus the intended benefit ('so you don't repeat it'). It is not a tautology and meaningfully distinguishes from the name. However, it does not explicitly differentiate from sibling tools like 'learned' or 'recall', which could have overlapping purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 alternatives. The description implies a use case (when something fails) but does not state exclusions, prerequisites, or contextual triggers. Sibling tools are listed but not described, so the agent cannot make an informed choice.
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 behavioral disclosure. It states only 'Export a learning to CLAUDE.md' but does not explain whether this appends or overwrites content, whether it creates missing files, or what happens to the source learning. No side effects or permissions are mentioned.
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 sentence, with no redundant words. It immediately states the action and destination, making it efficient and well-structured.
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 mutates a file and has no annotations or output schema, the description is too sparse. It does not clarify important behaviors like idempotency, formatting of the promoted entry, or how 'section' interacts with existing content. Sibling context suggests a workspace but the description doesn't establish how this fits.
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 covers all three parameters with descriptions, so the baseline is 3. The description's mention of 'CLAUDE.md' aligns with the target_file parameter but adds no semantic detail beyond the schema. No extra meaning is provided for 'id' or 'section'.
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 uses the specific verb 'Export' and names the resource 'a learning' and destination 'CLAUDE.md', making the tool's function clear. While it doesn't explicitly contrast with sibling tools, the destination file distinguishes it from 'mistake', 'learned', and 'recall'.
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 offers no guidance on when to use this tool versus siblings like 'learned' or 'recall'. There is no mention of scenarios, prerequisites, or exclusions, leaving usage entirely to inference.
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 the full burden, but it only states a search action without disclosing behavioral traits such as return format, default limits, sorting, or whether results are fuzzy-matched. The schema mentions 'fuzzy matched', but the description itself does not provide this context.
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, concise sentence that front-loads the core action. It avoids unnecessary detail, though it is arguably under-specifying, which is penalized elsewhere. The structure is efficient for its length.
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 tool with no output schema and no annotations, the description is incomplete. It does not explain what the search returns, how results are ordered, or the effect of optional parameters. The agent is left without expectations for the tool's output, making correct invocation harder.
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 baseline is 3. The description adds no parameter-specific meaning beyond what the schema already documents, but the schema is sufficient with clear descriptions for query, tags, and limit.
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 specifies the verb 'Search' and the resource 'mistakes and solutions', making the primary purpose clear. It does not explicitly contrast with siblings, but the search action implies a distinct role among the sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 the sibling tools (mistake, learned, promote). The description implies searching past mistakes, but there are no explicit alternatives or exclusions, leaving the agent without decision support.
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 for behavioral disclosure. It only states 'Cache' without explaining persistence, overwrite semantics, scope, or how cached items are retrieved. This leaves significant ambiguity for an agent.
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?
Single sentence, front-loaded with the verb 'cache', no wasted words. It concisely conveys the action and object.
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?
The tool is a simple cache operation, but the description lacks integration with sibling tools and doesn't explain the lifecycle of cached items (e.g., whether they can be recalled later). Given that the schema is complete but the overall narrative is thin, the description is not fully self-sufficient.
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 covers 100% of parameters with descriptions, so the baseline is 3. The description adds no additional parameter context beyond the schema's own field descriptions.
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 uses the specific verb 'cache' and resource 'problem/solution pair', clearly indicating the action. It does not explicitly distinguish from sibling tools like 'mistake' or 'recall', but the core purpose is unambiguous.
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?
No explicit when-to-use guidance or alternatives are mentioned. The context of sibling tools suggests a memory system, but the description alone only implies caching after a problem is solved, leaving the exact usage scenario implicit.
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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