agentmemo-mcp

Server Quality Checklist

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Latest release: v0.1.1
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: check_approval and request_approval handle approval workflows, while forget, list_memories, recall, and remember manage memory operations. The descriptions make it easy to differentiate between approval and memory tools, and within each category, the actions are well-defined (e.g., recall vs. remember).
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern (e.g., check_approval, list_memories, request_approval) with no deviations in style or casing. This uniformity makes the tool set predictable and easy for an agent to navigate, enhancing usability.
Tool Count5/5
With 6 tools, the server is well-scoped for its memory and approval management domain. Each tool serves a specific, necessary function without redundancy, making the count appropriate and efficient for handling core workflows like storing, retrieving, and managing memories, along with human-in-the-loop approvals.
Completeness5/5
The tool set provides complete coverage for the memory and approval domain: it includes create (remember), read (recall, list_memories), delete (forget), and approval lifecycle (request_approval, check_approval). There are no obvious gaps, ensuring agents can perform all essential operations without dead ends.
Average 3.4/5 across 6 of 6 tools scored. Lowest: 2.8/5.
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?
No annotations are provided, so the description carries full burden. It mentions 'recent' but doesn't define the timeframe or sort order. It fails to disclose what gets returned (memory IDs? full content? timestamps?) or namespace isolation behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence of six words is efficient and front-loaded, but arguably too terse given the lack of annotations and output schema. No wasted words, but insufficient information density for the context.
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?
With no output schema and no annotations, the description should explain return values and behavioral constraints. It fails to do so, leaving critical gaps in the contract despite the simple 2-parameter schema.
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%, documenting both 'namespace' and 'limit' parameters. The description mentions 'namespace' aligning with the parameter, but adds no semantic details beyond the schema (e.g., what constitutes a valid namespace). Baseline 3 appropriate given schema completeness.
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?
States a specific verb (List) and resource (memories) with scoping (in a namespace). The word 'recent' helps implicitly distinguish from the sibling 'recall' tool, though it doesn't explicitly name alternatives.
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?
Provides no guidance on when to use this versus siblings like 'recall' (likely for specific retrieval) or 'remember'. No prerequisites or exclusion criteria mentioned.
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 provided, so description must carry full burden. It implies a read-only operation ('Check') but fails to disclose return format, possible status values (pending/approved/rejected), error behaviors, or rate limiting constraints.
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?
Single sentence of 7 words with no redundancy. Action verb leads immediately, making it efficiently scannable.
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?
Adequate for a single-parameter tool with complete schema coverage, but gaps remain regarding output structure, possible approval states, and integration with the approval workflow (sibling tools). No output schema exists to compensate.
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 has 100% description coverage ('The approval ID to check'), so the description appropriately relies on the schema. No additional parameter context (e.g., where to obtain the ID) is provided, warranting baseline score.
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?
Clear verb ('Check') and resource ('status of a human approval request'). Distinguishes implicitly from sibling 'request_approval' by focusing on status retrieval rather than creation, though explicit differentiation is absent.
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?
No explicit guidance on when to use this tool versus 'request_approval', nor does it mention the typical polling workflow after requesting approval. Lacks prerequisites or conditions.
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 full burden of behavioral disclosure. While 'Delete' implies destruction, the description fails to clarify whether this is permanent, irreversible, or has side effects on related memories. For a destructive operation, this omission is significant.
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 single sentence is immediately front-loaded with the action and resource. No wasted words or redundant phrases. Appropriate length for the tool's simplicity.
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?
For a single-parameter deletion tool without output schema, the description covers the basic operation but is incomplete regarding safety implications. Given the lack of annotations and the destructive nature, it should explicitly warn about permanence or data loss risks.
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 the 'id' parameter fully described as 'The memory ID to delete'. The description mentions 'by ID' which aligns with the schema but adds no additional semantic value such as ID format, where to obtain valid IDs, or validation rules. Baseline 3 is appropriate given complete schema coverage.
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 ('Delete') with a clear resource ('stored memory') and qualifier ('by ID'). It effectively distinguishes from siblings like 'remember' (create), 'recall' (retrieve), and 'list_memories' (list) through the destructive verb choice, though it doesn't explicitly name alternatives.
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?
No guidance on when to use this tool versus alternatives, or prerequisites for deletion. Given the existence of 'check_approval' and 'request_approval' siblings, the description misses the critical opportunity to indicate whether deletion requires prior approval or specific conditions.
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 'most relevant' (indicating ranked results) but fails to confirm read-only safety, error handling when no matches exist, or the format/structure of returned memory objects.
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 consists of two efficient sentences with zero redundancy. The first states the action and target, the second clarifies the return value. Every word earns its place and the key verb appears immediately.
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 no output schema exists, the description minimally addresses return values ('Returns the most relevant memories') but lacks detail on memory structure or metadata. For a 3-parameter tool with simple types, this is adequate but leaves gaps in behavioral context due to missing annotations.
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?
Input schema has 100% description coverage ('What to search for', 'Optional namespace', 'Max results'). The description reinforces the query parameter's role but does not add syntax details, validation rules, or semantic context beyond what the schema already provides, warranting the baseline score.
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 specific verb 'Search' with resource 'stored memories' and clarifies the retrieval is by 'query' returning 'most relevant' results. This distinguishes it from sibling 'list_memories' (which implies enumeration) by emphasizing relevance-based retrieval, though it could explicitly name the sibling contrast for full marks.
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 explicit guidance on when to use this tool versus 'list_memories' (both retrieve memories) or prerequisites for searching. While 'by query' implies usage when searching for specific content, it fails to clarify selection criteria between the two retrieval siblings.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It correctly indicates the persistent nature ('across sessions') and mutation ('Store'), but lacks details on return values, idempotency, overwrite behavior, or error conditions that would help an agent predict outcomes.
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 consists of two tightly constructed sentences with zero redundancy. It is front-loaded with the action verb and immediately follows with the value proposition ('across sessions'), making it an exemplar of efficient technical writing.
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 (3 parameters with full schema coverage) and lack of output schema, the description adequately covers the essential function. It could be improved by mentioning the return type or success confirmation, but it provides sufficient context for an agent to invoke the tool correctly.
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 has 100% description coverage, providing a baseline of 3. The description mentions 'Store a memory' which loosely maps to the 'content' parameter, but adds no specific semantic guidance, examples, or format constraints beyond what the schema already provides.
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 action ('Store a memory') and the resource, distinguishing it implicitly from sibling 'recall' by specifying this is for storage 'for later recall'. It effectively communicates the tool's directionality (write vs read).
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 phrase 'Use this to persist information across sessions' provides explicit guidance on when to use the tool (for cross-session persistence). While it doesn't explicitly name alternatives like 'recall' or warn against misuse, it establishes a clear usage context.
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 successfully discloses the human-in-the-loop interaction and the async pattern (returns ID to poll), but omits timeout behavior, idempotency, or what happens when approval is denied.
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?
Two sentences, zero waste. Front-loaded with the core action ('Ask a human') followed immediately by the return value behavior. Every word earns its place.
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 100% schema coverage and lack of annotations, the description adequately covers the core workflow. However, it could strengthen completeness by explicitly referencing the 'check_approval' sibling relationship or describing error scenarios.
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 structured documentation already clearly defines all three parameters (question, context, callback_url). The description doesn't add parameter-specific semantics beyond what's in the schema, which is acceptable given the high coverage.
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?
Description uses specific verbs ('Ask', 'approve or reject') and identifies the resource (human) clearly. It distinguishes from siblings like 'check_approval' by emphasizing the request initiation aspect versus checking status.
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 phrase 'Returns an approval ID to poll' implies an asynchronous workflow and hints at using 'check_approval' for polling, but it doesn't explicitly state when to use this tool versus alternatives or explicitly name the sibling polling tool.
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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