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Akpughe

ultramem-mcp

by Akpughe

Server Quality Checklist

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

  • Disambiguation5/5

    All four tools have clearly distinct purposes: recall_search for semantic search, recall_timeline for chronological listing, add_memory for writing, and get_profile for fetching user profile. No overlap in functionality.

    Naming Consistency5/5

    Tool names follow a consistent verb_noun pattern in snake_case: recall_search, recall_timeline, add_memory, get_profile. The verbs 'recall', 'add', and 'get' are used uniformly.

    Tool Count5/5

    With 4 tools, the server is well-scoped for a personal memory assistant. Each tool serves a distinct operation (search, timeline, add, profile) without unnecessary bloat or deficiency.

    Completeness4/5

    The core operations for memory management are covered: retrieval (search and timeline), addition, and profile access. However, deletion or updating of memories is absent, which is a minor gap.

  • Average 4.1/5 across 4 of 4 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 1 commit 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 Apache 2.0.

  • This repository includes a README.md file.

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

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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

  • Behavior4/5

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

    With no annotations, the description carries full burden. It discloses that the tool fetches both static and dynamic data, implying a read-only operation. It does not specify permissions or side effects, but the behavior is adequately described for a profile fetch.

    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 with two sentences: one defining the tool's action and content, and one providing immediate usage context. No superfluous information.

    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 description gives a high-level idea of the profile content but lacks specifics on return structure or fields. Given no output schema, more detail could help, but the description is still usable for an AI 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 input schema already defines the optional container_tag parameter with a clear description. The main description adds no additional parameter info, but schema coverage is 100%, so baseline 3 is appropriate.

    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 tool fetches a 'standing profile' combining static facts and dynamic recent activity. It distinguishes its purpose from siblings by focusing on profile retrieval, but does not explicitly contrast with sibling tools like recall_search or recall_timeline.

    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 clear usage guidance: 'Inject this into your system prompt to start a session already knowing the user.' It also explains the optional parameter behavior. However, it does not mention when not to use the tool or alternatives.

    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 bears full responsibility. It discloses that the tool returns 'documents plus standalone facts,' which is useful but does not mention other behavioral traits like rate limits, auth requirements, or side effects. It 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?

    Three sentences with no wasted words. The purpose is front-loaded, and the usage guidance is succinct. Every sentence adds value.

    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 search tool with no output schema, the description adequately explains the return type (documents plus facts). It could mention pagination or result count, but given the limitation parameter is in schema, it's reasonably complete.

    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% (all 3 parameters described in schema). The description does not add extra meaning beyond schema fields; it only states 'in natural language' for query, which is already implied. Baseline score 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 the verb 'search' and the resource 'user's memory' in natural language. It specifies the output: 'most relevant documents plus standalone facts.' This distinguishes it from sibling tools like recall_timeline (likely timeline-based) and add_memory (add 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?

    The description advises to 'Use this first to ground any answer or action in what the user actually knows,' providing clear context for when to invoke. However, it does not explicitly state when not to use or mention alternatives, but the sibling list indirectly helps.

    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, so description carries full burden. Discloses complete enumeration (not ranking) and newest-first order, but does not mention return format, default parameter behavior, or read-only nature. Adequate but incomplete.

    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 concise sentences plus a short note on optional restriction. Front-loaded with key action and purpose. No unnecessary words.

    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?

    No output schema, so description should describe what the tool returns. It says 'list memory items' but does not specify fields or structure. Could be improved by mentioning typical output fields (e.g., timestamp, content, source). Otherwise acceptable for a simple listing tool.

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

    Parameters4/5

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

    Schema coverage is 100% (baseline 3). Description adds default values for days and limit, and clarifies that container_tag is optional with a configured default, adding value beyond 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?

    States exactly what the tool does: list memory items within a recent time window, newest-first, complete enumeration. Distinguishes from sibling recall_search (relevance ranking) and gives example use case.

    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 for 'what did I do/save in the last N days' questions. Mentions optional source restriction. Implicitly says not to use if you need relevance ranking (use recall_search), but could explicitly mention other 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?

    No annotations are provided, so the description carries the full burden. It mentions the distillation and reconciliation lifecycle, which adds some behavioral insight, but does not disclose side effects, required permissions, or idempotency behavior. More explicit transparency would improve confidence 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.

    Conciseness5/5

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

    Two sentences, no waste. The first sentence concisely states purpose and examples; the second adds valuable lifecycle context. Every phrase serves a purpose.

    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 only 3 parameters, no output schema, and no annotations, the description provides sufficient context for typical use. It covers purpose, examples, and processing lifecycle. However, missing return value information and error behavior slightly reduce completeness.

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

    Parameters4/5

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

    Schema coverage is 100% with clear descriptions for each parameter. The description adds value by contextualizing the 'content' parameter (e.g., task outcome, decision), which goes beyond the schema's basic text description. This helps the agent choose appropriate content to store.

    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 writes a memory back to the user's store with specific examples (task outcome, decision, user statement). It is distinct from sibling tools (recall_search, recall_timeline, get_profile) which are all read-oriented.

    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 implies this is the tool for writing memories, but does not explicitly state when not to use it or mention alternatives. The lifecycle hint ('distillation + reconciliation') provides context but lacks explicit usage boundaries.

    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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