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mem.ai MCP Server

by hskksk

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.2.0

  • Disambiguation3/5

    mem_it and create_note both handle saving content, creating ambiguity in which to use. list_notes and search_notes have overlapping filtering and query capabilities, though descriptions help differentiate. Overall, most tools target distinct operations.

    Naming Consistency4/5

    Most tools follow a consistent verb_noun pattern with pluralization for listing/searching. The exception is 'mem_it', which breaks the convention and uses an imperative phrase instead of a clear verb_noun structure.

    Tool Count5/5

    11 tools cover two main resources (notes and collections) with a full set of CRUD-like operations plus search and a special save capability. This is well-scoped and appropriate for the server's purpose.

    Completeness3/5

    The tool set provides create, get, delete, list, and search for both notes and collections, but lacks update operations for either resource, which is a notable gap for a note-taking service. This prevents agents from modifying existing notes or collections.

  • Average 3.4/5 across 11 of 11 tools scored. Lowest: 2.7/5.

    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.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

    Then . Browse examples.

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How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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

  • Behavior1/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations are provided, so the description carries the full burden for disclosing behavioral traits. It only says 'Search' and mentions optional query/configuration, without describing read-only nature, return format, pagination, or effects of the config option. This is a minimal, non-disclosing description.

    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 with no filler words, making it easy to parse. However, the term 'configuration' is vague and the description is borderline under-specified, so it is concise but not perfectly crafted.

    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 needed to explain return values and broader behavior, but it does not. It only states the basic search capability and optional parameters, leaving significant contextual gaps for a tool with a nested config object.

    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%, with both 'query' and 'config' described in the schema. The description adds no additional meaning beyond restating 'optional query and configuration', so the baseline of 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 uses the specific verb 'Search' with the resource 'all collections in mem.ai', making the core purpose clear. However, it does not explicitly distinguish this from sibling tools like list_collections or search_notes, so it is clear but not fully differentiating.

    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 alternatives. It only states what the tool does and mentions optional inputs, with no exclusions, prerequisites, or comparison to sibling tools like search_notes or list_collections.

    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 a create action, which implies mutation, but provides no additional behavioral details such as authentication requirements, side effects, duplicate handling, or return value. This is minimal and does not enrich the agent's understanding beyond the obvious.

    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 directly states the tool's purpose. There is no fluff, and it is appropriately sized for the simplicity of the operation.

    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 lack of annotations and output schema, the description is quite sparse. It does not mention return values, potential errors, or any constraints. While the schema covers parameter semantics, the description alone is insufficient for an agent to fully understand the context of a mutating operation, especially without any sibling 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 has 100% description coverage for both parameters (title and description), so the baseline is 3. The description itself only says 'Create a new collection' and adds no extra meaning beyond what the schema already provides. It does not compensate for any gaps because there are none.

    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 clearly states the action (create) and the resource (collection) within the specific context (mem.ai). It is unambiguous and distinguishes itself from sibling tools like get_collection, delete_collection, and list_collections.

    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 prerequisites, conflicts, or when a different tool might be more appropriate. The sibling tools are listed, but the description does not reference them or explain selection criteria.

    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. It does not disclose whether deleting a collection has side effects on contained notes, whether deletion is permanent, or any other non-obvious behavioral traits beyond the literal action.

    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 clear sentence with no filler. It is appropriately sized for the tool's simplicity.

    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 no annotations and no output schema, the description is incomplete for a destructive operation. It does not explain what happens to notes in the collection, return values, or any prerequisites, leaving significant gaps for an agent.

    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 schema has 100% coverage for the single parameter collection_id, which includes a description. The tool description adds no additional meaning beyond what the schema already provides, so baseline 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 clearly states a specific verb ('Delete') and resource ('collection from mem.ai'), which distinguishes it from sibling tools like delete_note and collection-related operations.

    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 is provided on when to use this tool vs alternatives. The description only states what it does and does not mention exclusions or relationships to other tools.

    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 only states 'Delete a note from mem.ai.' It fails to disclose whether the deletion is permanent, reversible, or requires confirmation. No side effects or consequences are described, making it insufficient for a destructive action.

    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 sentence with no redundant words. It is front-loaded and appropriately sized for the tool's simplicity.

    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?

    Without output schema or annotations, the description is minimal and omits critical context such as irreversibility or success/failure responses. Given the destructive nature, this is incomplete.

    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% and the parameter 'note_id' is already described as 'Note ID to delete'. The 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 clearly specifies the verb 'Delete' and the resource 'a note from mem.ai', making the tool's purpose unambiguous. It distinguishes from sibling tools like get_note or create_note by indicating a destructive action on a note.

    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 is provided about when to use this tool versus alternatives, nor any prerequisites or context. The only usage signal is the verb 'Delete', which is implied but not explicitly framed as a conditional or contrasted with other operations.

    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 only states the search capability and mentions 'advanced filtering options' without disclosing behavior such as return format, pagination, result ordering, or any side effects. This is insufficient for a search tool with no 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.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single sentence, 13 words, front-loaded with the action and resource, and contains no filler or redundant information. Every word earns its place.

    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 7 parameters, including a nested config object, and no output schema or annotations, the description is too minimal. It does not explain what the search returns, whether results are paginated, or how the advanced filters behave. The schema covers parameters but leaves operational context missing.

    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%, with each parameter having a description (e.g., query, config, filters). The description adds no additional parameter semantics beyond what the schema already provides, 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 clearly states 'Search across all notes in mem.ai', which is a specific verb (Search) and resource (notes), with optional query and advanced filtering. It distinguishes from siblings like get_note (retrieves a single note), list_notes (lists notes without search), and search_collections (searches collections).

    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 get_note, list_notes, or any exclusions. The word 'Search' implies a distinct use case, but there is no explicit or clear contextual guidance.

    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 behavioral implications. It only restates the core action and does not mention side effects, prerequisites, idempotency, what happens if an ID is provided, or what the response looks like.

    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 sentence of 9 words, direct and front-loaded with the key verb and object. Every word contributes value, with no unnecessary detail or repetition.

    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 lack of annotations and output schema, the description is incomplete. It does not explain return values, optional collection behavior, or any edge cases. For a tool with 6 parameters, the description should provide more context about the creation flow and potential outcomes.

    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 schema already provides descriptions for all 6 parameters (100% coverage), so the baseline is 3. The description adds no extra meaning beyond what the schema contains; mentioning 'markdown content' is redundant with the content parameter description.

    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 clearly states the action ('Create'), the target resource ('a new note'), the platform ('in mem.ai'), and the content format ('with markdown content'). This specific language distinguishes it from sibling tools like get_note, delete_note, and search_notes.

    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 usage for creating notes but does not explicitly state when to use this tool versus alternatives. There is no mention of exclusions or when another tool would be more appropriate, such as for updating or searching.

    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. It tells the agent that the tool retrieves, but it does not specify whether any side effects occur, what happens if the ID does not exist, or whether authentication is required. The verb 'retrieve' implies read-only, but that is not explicitly stated.

    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 directly states the tool's function. There is no wasted wording.

    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 simplicity of the tool (one parameter, no output schema), the description is minimally viable. However, it lacks any mention of return behavior, errors, or permissions, which could be important for the agent to make fully informed decisions. The description is adequate for a simple read operation but not comprehensive.

    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 the parameter, describing collection_id as 'Collection ID to retrieve' with a uuid format. The description adds no additional meaning beyond the schema, so the baseline score 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 clearly states the tool's action ('Retrieve') and resource ('a specific collection'), with the scope 'by its ID.' This distinguishes it from sibling tools like list_collections or search_collections, which operate differently.

    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 usage when you have a collection ID and need the specific collection, but it does not explicitly contrast with sibling tools like list_collections or search_collections. There is no exclusion or alternative guidance.

    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 fully carry the burden of behavioral disclosure. It only states the basic action and does not disclose potential side effects, return value details, error behavior, or permission requirements, which are important 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.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single, focused sentence that conveys the essential purpose without any fluff or redundant information. It is optimally concise and structurally sound.

    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, the description covers the core function, but it omits important context such as what the response contains, error conditions, or whether any special permissions are needed. Since there is no output schema or annotations, these gaps could impact an agent's ability to use 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 already describes the sole parameter (note_id) with a clear description. The tool description repeats 'by its ID' but adds no extra semantic information beyond what the schema provides, so the baseline score 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 clearly states the action (retrieve), the resource (note), and the method (by ID). It distinguishes itself from sibling tools like list_notes and search_notes by specifying the exact retrieval mechanism.

    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 that this tool should be used when you have a specific note ID, but it does not explicitly state when to prefer it over search_notes or list_notes, nor does it exclude any scenarios. Usage context is implied rather than explicitly articulated.

    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 only says 'Remember any content intelligently' and 'saving information,' but does not disclose whether this creates a record, whether it deduplicates, how 'intelligently' manifests, or what side effects may occur. This is a significant gap for a write operation.

    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 two sentences with no wasted words. It front-loads the primary action ('Remember any content intelligently') and then clarifies the scope ('primary endpoint for saving information to mem.ai'), which is concise and effective.

    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?

    While the schema fully documents parameters and the purpose is clear, the absence of an output schema and annotations leaves unanswered questions about what the tool returns or any constraints (e.g., rate limits). The description is minimally viable but not rich enough to fully orient an agent for a generic save endpoint with no output 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?

    The schema has 100% description coverage for all four parameters, including explanations for 'input', 'context', 'timestamp', and 'instructions'. The description itself adds nothing about parameters, so with the schema already doing the heavy lifting, 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 clearly states the tool's purpose: 'Remember any content intelligently' with the explicit clarification that it is 'the primary endpoint for saving information to mem.ai.' This is a specific verb+resource combination and distinguishes it from sibling tools like get_note and create_note, which operate on notes and collections.

    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 explicitly frames this as 'the primary endpoint for saving information to mem.ai,' which implies this is the go-to tool for general saving, as opposed to siblings that handle categories like notes or collections. However, it stops short of saying when not to use it or naming 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 disclosing behavioral traits. It does not explicitly state that this is a safe, read-only operation, nor does it mention any side effects, authentication needs, or rate limits. The mention of cursor-based pagination is already captured in the schema, adding no additional transparency.

    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, front-loaded sentence that conveys the core function and key options without any wasted words. It is compact and efficient.

    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 simple list tool, the description covers the essential behavior: listing all collections with sorting and pagination. Since there is no output schema, the description does not explain return structure, but the term 'list' implies a collection of results, which is sufficient for most use cases. It also aligns well with the sibling tool set.

    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 baseline is 3. The description mentions sorting and pagination but does not add any meaning beyond what the schema already provides for each parameter. It does not clarify default values or parameter interactions beyond what is in the schema.

    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 clearly states the tool lists collections in mem.ai, which is a specific verb+resource. It also mentions optional sorting and cursor-based pagination, distinguishing it from single-collection tools like get_collection and search_collections.

    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 says 'List all collections' which clearly communicates its primary use case. It does not explicitly exclude alternative tools or mention when not to use it, but the context is clear enough for an agent to select it over get_collection or search_collections.

    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, the description carries the burden of behavioral disclosure. It does mention cursor-based pagination and optional filtering/sorting, but it does not disclose default response behavior (e.g., whether note content is included), response shape, or any rate limits. Still, it accurately conveys that this is a read-style listing operation.

    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, well-structured sentence that front-loads the core purpose and packs meaningful capabilities without unnecessary detail. Every word earns its place.

    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 9 parameters and no output schema, so the description needs to provide a useful overview. It does cover the main purpose and capabilities, but it omits guidance on when to choose this over search_notes, and it does not explain return-value structure or pagination mechanics. The schema compensates for parameter details, but the lack of usage alternatives and behavior specifics leaves some gaps.

    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%, so the description does not need to explain individual parameters. It adds only a high-level mention of filtering, sorting, and pagination, which is already reflected by the schema properties. No additional semantic value beyond the schema is provided.

    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 a specific verb ('List') and resource ('all notes in mem.ai'), clearly distinguishing it from siblings like get_note (single note) and search_notes (search). It also communicates the optional filtering, sorting, and pagination capabilities at a high level.

    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 clearly implies use for enumerating all notes with optional filters, which is distinct from search or single-note retrieval. However, it does not explicitly name alternatives or state when not to use it, so it stops short of full guidance.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
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