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MikSkrzyp

identity-storage-mcp

by MikSkrzyp

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 clearly distinct purpose: memory_recall for browsing by tags/time, memory_search for content search, and memory_store for saving memories. No ambiguity between them.

    Naming Consistency5/5

    All tools follow a consistent 'memory_' prefix with a verb (recall, search, store), making the tool names predictable and easy to understand.

    Tool Count4/5

    With 3 tools, the set feels slightly minimal but appropriate for a targeted memory storage and retrieval system. The count is reasonable for the scope.

    Completeness3/5

    The tool surface covers storing and two retrieval methods, but lacks delete or update operations, which are notable gaps for a complete memory lifecycle.

  • Average 4.4/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 16 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": [
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      ]
    }

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

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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 reveals important behavior: storing one memory per distinct thing, the consequence of forgetting ('permanent loss'), and specific payload keys for episodic type. It does not mention rate limits or auth, but covers key operational traits.

    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 well-structured with a clear lead sentence and bullet points for types. It is somewhat lengthy but every sentence adds value, avoiding redundancy.

    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 complexity of the nested input schema and the presence of an output schema, the description is fairly complete. It explains the types, usage rules, and key parameters. It could briefly mention the return value, but the output schema likely covers that.

    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?

    Despite the context listing 0% schema description coverage (which seems contradicted by the schema itself), the description adds significant meaning: explaining each memory type, when to set confidence below 1.0, and the role of tags. This goes beyond the schema's brief descriptions.

    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 'Store a memory.' and explains when to call it ('after every non-trivial turn'). It distinguishes between memory types (episodic, semantic, procedural) with concrete examples, differentiating from sibling tools like memory_recall and memory_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?

    The description provides explicit guidance on when to use this tool ('after every non-trivial turn'), what types to use, and what to skip ('idle chat, greetings, and trivial responses'). It does not explicitly mention alternatives, but the sibling context is provided separately.

    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?

    No annotations are provided, so the description carries full burden. It discloses that the tool browses memories, returns newest first, and supports filtering. It does not explicitly state it is read-only, but that is implied by 'browse'.

    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 with no superfluous text. The purpose and guidance are 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?

    An output schema exists, so return values are covered. The description provides core usage and differentiation. Missing details on pagination or ordering beyond 'newest first' are minor given schema richness.

    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 description mentions 'filter by tags and time window', which adds some context beyond the schema. However, it does not explain the 'limit' or 'memory_type' parameters beyond 'of one type'. With schema description coverage reported as 0%, the description should compensate more.

    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 the verb 'browse' with the resource 'memories of one type' and specifies ordering ('newest first'). It clearly differentiates from the sibling 'memory_search' by stating this tool is for browsing and not for per-turn recall.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    Explicit usage guidance is provided: use for 'what did I do recently' or 'what happened in this session', and a direct exclusion: 'Not for per-turn recall — use memory_search for that.'

    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?

    No annotations provided, so description carries the burden. It reveals the internal search engine (FTS5) and result interpretation ('If empty, no memory needed'). Could mention that it is read-only, but the description sufficiently conveys search behavior.

    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?

    Four sentences, each serving a purpose: purpose, when to use, result interpretation, alternative tool. No filler, front-loaded with key information.

    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 main use case, alternatives, and result interpretation. However, does not mention the memory_type parameter, which is required and important for correct usage. Output schema exists, so return details are covered.

    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 descriptions cover all parameters (query, memory_type, limit) but the tool description adds only that the user's prompt should be passed as 'query'. With schema descriptions presumably high, the description adds minimal value 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?

    The description clearly states 'Search past memories by content' and distinguishes from sibling memory_recall by specifying that it is for content search, while memory_recall is for browsing by tags or time window.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    Explicitly states when to call (user references past work, examples given), what to do with the query ('Pass the user's prompt as query'), and provides a condition for interpreting empty results. Also specifies when not to use and points to alternative memory_recall.

    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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Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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