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zuneracodes

LocalKeep MCP Server

Server Quality Checklist

75%
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  • Latest release: v0.1.2

  • Disambiguation2/5

    search_memories and get_memories_by_date_range overlap significantly because search_memories already accepts a date range, making the dedicated date-range tool largely redundant. list_banks and get_bank are clearly distinct, but the two retrieval tools create ambiguity in tool selection.

    Naming Consistency5/5

    All tools use clear lowercase snake_case verb_noun names. The pattern is consistent across search_memories, get_memories_by_date_range, list_banks, and get_bank, each following an imperative verb + object structure.

    Tool Count5/5

    With only 4 tools, the server is tightly scoped for its purpose of querying memory banks. Each tool has a distinct role in discovery and retrieval, and there is no bloat.

    Completeness4/5

    The server covers the main retrieval needs: searching across banks, filtering by date, listing banks, and loading a full bank. However, there is no way to search within a specific bank without loading all its memories, and no single-memory fetch by ID, so some workflows require client-side filtering.

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

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

    • No community issues in the last 6 months
    • No commit activity data available
    • 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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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 and openWorldHint=false, so the safety profile is covered. The description adds the event_date filtering behavior and optional entity refinement, but does not disclose pagination, ordering, or missing-date behavior; the openWorldHint is not explained.

    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?

    Two short sentences, with the core operation front-loaded and the use case in the second sentence. The only blemish is the ambiguous 'query/entity' phrase, which could mislead.

    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 four-parameter tool with an output schema, the description gives the main invocation context but omits date format, inclusive/exclusive semantics, and when to prefer search_memories instead. The 'query' mention adds a small inconsistency. Overall adequate but not fully 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 description coverage is 0%, so the description carries the burden. It clarifies date_from/date_to as the date-range bound and entity as a topic/person filter, but does not specify date format or limit behavior, and the phrase 'query/entity' references a 'query' that is not present 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 states a specific action and resource: 'Fetch memories whose event_date falls in a date range.' This clearly distinguishes the tool from the bank-related siblings and suggests a different mode from search_memories by anchoring on date rather than free-text search.

    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?

    It gives explicit trigger conditions: 'USE when the user mentions a month, year, or period, or asks what they were working on during a timeframe.' It lacks explicit when-not-to-use guidance or named alternatives, but the context is clear enough for selection.

    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?

    The readOnlyHint and openWorldHint annotations already establish the read-only, closed-world nature. The description adds useful behavioral detail beyond that: it loads ALL memories and supports exact or partial title matching, which affects how the agent should interpret results.

    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 short sentences with no filler. The core operation is stated first, followed by a focused usage condition, making it easy for an agent to parse quickly.

    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 tool with one parameter, read-only annotations, and an output schema, the description covers the main operational details: what to load and when to use it. The only notable gap is the ambiguity around partial matches resolving to multiple banks, given the claim that it loads from 'one bank.'

    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?

    With 0% schema description coverage, the description must compensate for bank_title. It states that the parameter is a title match with exact or partial matching, but it does not clarify behavior when a partial match returns multiple banks, case sensitivity, or formatting expectations.

    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 and resource: 'Load all memories from one bank by title'. It clearly distinguishes itself from list_banks and get_memories_by_date_range through the title-based, bank-scoped behavior, though it does not explicitly contrast with search_memories.

    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?

    It gives an explicit trigger condition: 'USE when a bank title matches the topic or person the user is asking about.' This clarifies when to call the tool, but it does not state when not to use it or suggest alternatives such as search_memories.

    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 provide readOnlyHint=true and openWorldHint=false, so the tool's safety profile is known. The description adds meaningful context by stating that results are 'titled, dated facts the user wrote' and 'authoritative for their timeline,' which tells the agent about the nature and trustworthiness of the returned data.

    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 core purpose is front-loaded in a single sentence, and the rest of the description is easily scannable. The trigger examples are useful and not redundant, though the middle section could be slightly more condensed without losing value.

    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?

    An output schema exists, so return values are presumably covered. The description offers clear usage triggers and partial parameter guidance. The main gap is the lack of any mention of bank_title and limit, which are relevant for filtering and result control, but overall the description is adequate for a read-only search tool.

    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 the description must compensate. It does explain query ('keywords'), entity ('person or topic tag from memories'), and date range (date_from/date_to). However, it omits any explanation of bank_title and limit, leaving two of six parameters undocumented in both schema and 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 first sentence states a specific verb ('Search') and a specific resource ('the user's curated memory banks (local Hub)'). This clearly distinguishes it from sibling tools like list_banks and get_memories_by_date_range, which focus on listing banks or date-specific retrieval. The trigger examples further reinforce the tool's intended scope.

    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 FIRST when context about the user's own past — personal OR work/research — would help answer the question,' and gives concrete trigger examples. This is strong when-to-use guidance, but it does not explicitly mention when not to use it or directly contrast with the sibling tools, so it falls short of a full 5.

    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?

    Annotations already provide readOnlyHint=true, and the description is consistent with that. It adds that the tool returns only memory bank titles, not full bank content, but it does not disclose other behavioral details such as ordering, limits, or output shape; the output schema handles the return structure.

    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 short, purposeful sentences with no filler. The action and purpose are front-loaded, and the usage guidance is direct.

    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?

    For a zero-parameter, read-only listing tool with an output schema, the description is complete. It states what is listed, why, and when in the workflow to call it relative to get_bank and targeted search.

    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?

    The tool takes zero parameters, so there is no parameter burden for the description to carry. The baseline for zero-parameter tools applies, and the schema coverage is trivially complete.

    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 states a specific verb and resource: 'List memory bank titles' and explains the purpose, 'so you can pick the right timeline.' It clearly distinguishes this discovery tool from get_bank and targeted search by framing it as the precursor action.

    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 to use it 'before get_bank or a targeted search,' which gives clear workflow context. It does not name all sibling alternatives or provide when-not-to-use guidance, so it stops short of a 5.

    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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  • Evaluate tool definition quality.

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