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wyh0626

evermemos-mcp-server

by wyh0626

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a clear, distinct purpose: store, get, search, and delete. No overlap between them.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case: store_memory, get_memories, search_memory, delete_memory.

    Tool Count5/5

    Four tools is appropriate for a memory management system, covering core CRUD operations plus search without being excessive.

    Completeness4/5

    Covers create, read, search, and delete. Missing an explicit update tool, but store_memory may be used for overwriting; still a minor gap.

  • Average 4.2/5 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
    • 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.

  • Add related servers to improve discoverability.

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.

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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?

    States 'This performs a soft delete,' which is key behavioral info, but no other details on reversibility, permissions, or side effects. With no annotations, the description carries full burden but is minimal.

    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?

    Compact three sentences plus a bullet list, no redundant text. Front-loaded with purpose and usage context, well-organized parameter details.

    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?

    Covers purpose, usage, behavioral detail, and parameters. Output schema exists, so missing return value info is acceptable. Lacks error conditions or idempotency, but adequate for a simple delete.

    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 0%, so description must compensate. It adds meaning by explaining defaults and optional filters (user_id, group_id, memory_type), but lacks examples or allowed values, leaving gaps.

    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 'Delete memories from EverMemOS' with a specific verb and resource. It distinguishes from siblings like get_memories, search_memory, and store_memory by being the only delete operation.

    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?

    Explicitly says 'Use this tool when the user explicitly asks to forget or remove certain memories.' Provides clear context, though lacks explicit 'when not to use' or alternative recommendations.

    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?

    No annotations provided, so description carries full burden. It explains retrieve_method options but does not disclose behavioral traits like read-only nature, rate limits, result ordering, or whether it modifies state.

    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?

    Well-structured with a clear header and Args section, but some introductory sentences could be more concise. Overall, it is efficient and front-loaded.

    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 has 5 parameters and an output schema exists, the description adequately covers parameter usage and defaults. It is complete enough for an agent to use correctly.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 0%, but the tool description provides detailed explanations for all 5 parameters, including the various retrieve_method strategies and default values, adding significant meaning beyond 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?

    Description clearly states 'Search EverMemOS for relevant memories based on a natural language query' and lists specific use cases like project setup and user preferences, distinguishing it from sibling tools (delete, get, store).

    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?

    Explicitly says 'Use this tool when you need to recall past context' and provides examples, but does not explicitly mention when not to use it or suggest alternatives. However, sibling tools are clearly different operations.

    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?

    Without annotations, the description must disclose behaviors. It explains the flush parameter's effect on memory extraction timing and implies persistence across sessions. However, it does not discuss idempotency, duplicate handling, or whether the tool modifies existing memories, leaving gaps 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 concise and well-structured: a one-sentence purpose, a bulleted list of use cases, and a clear Args section. Every sentence is informative, and the most critical information is front-loaded. No redundant text.

    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 presence of an output schema (though not shown), the description adequately covers purpose, usage, and parameters. It lacks some behavioral specifics (e.g., side effects) but is otherwise comprehensive for a straightforward storage tool. Slight deduction for missing behavioral clarity.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Despite the context indicating 0% schema description coverage, the description's Args section thoroughly explains each parameter: content includes advice to be specific, role clarifies acceptable values, sender and group_id specify defaults and purposes, and flush describes its effect. This adds substantial meaning beyond the schema's titles and defaults.

    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 verb 'Save' and resource 'conversation message into EverMemOS long-term memory'. It distinguishes from siblings (delete, get, search) by focusing on storing new information, and provides specific examples of when to use.

    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 says 'Use this tool when the user shares important information...' and gives concrete examples, which is strong guidance. However, it does not explicitly contrast with siblings or state when not to use it, slightly lowering the score.

    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?

    No annotations are provided, so the description must carry the burden of behavioral disclosure. It explains default values (user_id defaults to env var, memory_type defaults to episodic_memory) and limit range (1-50). However, it does not mention read-only nature, auth requirements, or any side effects. Since the tool name suggests read-only, the description is adequate but not comprehensive.

    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 very concise: two short sentences for purpose/guidelines, followed by a bullet-like list of parameters. Every sentence is informative, and there is no redundancy or unnecessary text.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the tool has 4 parameters (none required), no enums, and an output schema, the description fully covers the necessary context. It explains each parameter's role, default behaviors, and distinguishes from siblings. The presence of an output schema means return values need not be described.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 0%, but the description compensates by explaining all four parameters. It provides semantic meaning for each: user_id (with env var default), memory_type (with explicit list of types), group_id (optional filter), and limit (with range). This adds significant value beyond the schema's bare property definitions.

    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 stored memories') and the primary filters (user ID and type). It explicitly distinguishes from the sibling tool 'search_memory' by mentioning 'without a specific search query', which helps an agent differentiate when to use this tool.

    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 provides a clear usage context: 'Use this tool to browse a user's memory collection without a specific search query.' This implies when to use it, but it does not explicitly mention alternatives like 'search_memory' or conditions to avoid using this tool. The guidance is present but could be more explicit.

    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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