AI Memory MCP
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool targets a distinct operation: recall for querying memories, sync for updating the index, and status for health checks. There is no overlap or ambiguity between these tools.
Naming Consistency5/5All tool names follow the same 'memory_' prefix followed by a verb (recall, sync, status). This consistent pattern makes the tool roles predictable and easy to use.
Tool Count5/5With 3 tools, the server is well-scoped and covers the core lifecycle of memory management (query, update, monitor). Each tool earns its place without unnecessary bloat.
Completeness3/5The set lacks direct creation/deletion of memories and does not offer search or listing capabilities. While sync indirectly handles updates from Markdown, recall is limited to cited memories, creating notable gaps in a full memory lifecycle.
Average 3.9/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 7 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
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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?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds context about returning 'applicable relationships,' which is not captured by annotations, but it does not disclose return format or any additional behavioral details such as result ordering or potential empty results. This is minimally adequate given annotation coverage.
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 entire description is one concise sentence: 'Recall cited memory and its applicable relationships.' It is front-loaded, contains no filler, and directly states the core action. Every word adds meaning, achieving high efficiency without unnecessary elaboration.
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?
The tool has an output schema, comprehensive parameter descriptions, and safety annotations, shifting the burden from the description to these structured fields. The description leaves some ambiguity around what 'applicable relationships' means, but given the rich schema and annotations, the description is sufficiently complete for its context. A brief note on typical use cases would improve it further.
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%, with every parameter including a meaningful description. The tool description adds no additional parameter semantics beyond the schema, so the baseline of 3 applies. The description's mention of 'applicable relationships' implies the query parameter relates to memory retrieval, but it does not clarify parameter interplay or defaults.
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 provides a specific verb ('Recall') and resource ('memory'), and adds 'applicable relationships' to distinguish the scope. It clearly identifies a retrieval operation, though 'cited memory' is somewhat ambiguous and does not fully distinguish from sibling tools like memory_status or memory_sync.
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 gives no explicit guidance on when to use this tool versus alternatives such as memory_sync or memory_status. The intended use is implied by the name, but the description does not state when to prefer this over the sibling tools or mention any contexts that would make this the right choice.
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?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, establishing the safe read-only nature. The description adds value by disclosing exactly which status areas are covered (source, index, Graphify, runtime), providing useful context beyond the structured annotations. Given the presence of an output schema, return format is already documented, so the description's additional scope detail is adequate.
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 states the tool's function without any unnecessary words or repetition. It is front-loaded and easily parsed.
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?
The tool has no parameters, a rich output schema, and clear annotations covering safety and idempotency. The description succinctly captures the essential scope of the status report. There is no missing critical information for an agent to select and invoke it correctly.
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 tool has zero parameters, so no parameter explanations are needed. Per the rubric, a baseline of 4 is appropriate for no parameters. The schema's 100% coverage (trivially) means there is no gap to compensate for.
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 'Report' and identifies the resource as status, breaking down four distinct components: source, index, Graphify, and runtime. This clearly distinguishes it from sibling tools like memory_recall and memory_sync, which imply different operations (retrieval and synchronization respectively).
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 about when to use this tool instead of memory_recall or memory_sync. The description only states what the tool does, without mentioning appropriate conditions, exclusions, or alternatives.
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?
Annotations (readOnlyHint=false, destructiveHint=false) already indicate the tool modifies state without being destructive. The description adds meaningful context by specifying the target ('derived index') and the source ('canonical Markdown'), providing domain-specific behavior not captured by annotations.
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, compact sentence (7 words) that immediately states the tool's purpose. Every word earns its place, with no wasted text or repetition of schema details.
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 zero-parameter synchronization tool with an output schema (as indicated in context signals), the description is largely complete. It clearly communicates the operation and source. Minor gaps include not defining what 'derived index' means or when a sync is necessary, but the simplicity of the tool mitigates this.
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 tool has zero parameters, so the input schema is essentially empty. With no parameters to document, the description carries the full semantic load by indicating what the tool acts upon ('canonical Markdown'), which clarifies that the input comes from elsewhere rather than explicit arguments.
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 'Update the derived index from canonical Markdown' clearly states a specific action (update) on a specific resource (derived index) with a clear source (canonical Markdown). This distinguishes it from sibling tools like memory_recall and memory_status, which suggest reading and status operations.
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 should be used to sync/update the derived index when canonical Markdown changes, but it does not explicitly mention when to use it versus alternatives, nor does it provide exclusion criteria. Usage is implied rather than directly stated.
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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