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jgauffin

Relax Memory MCP

by jgauffin

Server Quality Checklist

67%
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  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: add/update, retrieve, delete, and list. No overlap or ambiguity exists.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun snake_case pattern (add_memory, get_memory, delete_memory, list_memories). The pluralization of 'list_memories' is a minor stylistic variance but does not break the pattern.

    Tool Count5/5

    With only 4 tools, the set is well-scoped and perfectly sized for a simple memory storage service. Each tool serves a necessary CRUD function.

    Completeness5/5

    The tool surface covers the complete lifecycle of memories: create/update, read, delete, and list. No obvious gaps exist for the stated domain.

  • Average 3.8/5 across 4 of 4 tools scored.

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

  • This repository is archived. Archived repositories automatically receive an F maintenance tier.

  • This repository is licensed under AGPL 3.0.

  • This repository includes a README.md file.

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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

  • Behavior2/5

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

    With no annotations, the description carries the full burden. It only says 'delete' without mentioning irreversibility, whether the operation is destructive, or what happens if the memory does not exist. The verb implies destruction but lacks explicit disclosure of side effects.

    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 waste, front-loaded with the verb 'Delete'. It is appropriately concise 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 should provide more context. It omits return behavior, error handling, and whether the deletion is permanent. For a destructive tool, this is a significant gap.

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

    Parameters2/5

    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 merely restates the parameter names ('category and name') without explaining their meaning, valid values, or constraints. This adds minimal value beyond the schema's property names.

    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 ('Delete'), the resource ('a memory'), and the scope ('by category and name'). It inherently distinguishes itself from sibling tools (add/get/list) by specifying the 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?

    The description implies the tool is for removing memories, which is clear context. However, it does not explicitly mention alternatives or when not to use it, so it misses the 'exclusions' level of 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 must disclose safety and behavioral traits. It only says 'Retrieve', which implies read-only but does not explicitly state that it has no side effects, what happens if the memory does not exist, or return format. This is a significant gap 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 clear sentence, directly stating the action and the key parameters. It is efficient and easy to parse, with no redundant 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?

    Given no output schema and no annotations, the description should at least mention return value or error behavior. It covers the basic purpose but lacks information about what the tool returns on success or failure, which is important for a retrieval operation. As a simple tool, it is minimally viable but incomplete.

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

    Parameters2/5

    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 mentions 'by category and name' but adds no extra meaning beyond rephrasing the schema property names. No details on format, constraints, or how these parameters are used in the lookup.

    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 'Retrieve' and identifies the resource 'memory' with scope 'specific memory by category and name'. This clearly distinguishes the tool from siblings like list_memories (which lists) and add/delete_memory (which modify).

    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 phrase 'specific memory' implies this is for fetching a single, known memory rather than listing all, providing clear context for use. However, it does not explicitly state when not to use it or name list_memories as an alternative, so a small deduction applies.

    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 provided, the description carries the burden of disclosing behavior. It states the output is a hierarchical index grouped by category, implying a read-only operation, but doesn't explicitly confirm no side effects or describe any return format details beyond grouping. It's adequate but not rich.

    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 directly states the purpose and key output characteristics without any filler or 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?

    For a low-complexity tool with one optional parameter and no output schema, the description adequately conveys what the tool returns (hierarchical index) and its scope (all memories). It could mention more about the structure of entries, but the available information covers the essential expectations.

    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 only parameter, include_description, is fully documented in the schema with a clear description and default value. The tool description adds no additional meaning, 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 uses the specific verb 'List' with the resource 'memories' and clarifies scope as 'all memories' with a 'hierarchical index grouped by category.' This clearly distinguishes it from sibling tools like add_memory, get_memory, and delete_memory, which perform different actions.

    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 tool is for retrieving a full overview of all memories, contrasting with get_memory for individual retrieval. While it doesn't explicitly name alternatives or exclusions, the context makes the appropriate use case clear.

    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?

    With no annotations, the description carries the transparency burden. It discloses a key behavioral trait: overwriting when the same category+name exists. This is non-obvious and important for an upsert operation. However, it doesn't mention return values or error conditions, leaving some gaps.

    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 long, front-loaded with the main purpose, and includes only necessary information. There is no redundancy or filler.

    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 simplicity of the tool and the absence of an output schema, the description covers the core behavior adequately. It explains the upsert semantics and the overwrite key. However, it omits any mention of return type or success indicators, which would be helpful for a write operation.

    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%, so the baseline is 3. The description adds meaningful semantics by specifying that the combination of 'category+name' is the uniqueness key for overwriting, which is not directly stated in the schema. This clarifies how the parameters interact.

    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 function with a specific verb ('Store or update') and identifies the resource ('a memory'). It also distinguishes itself from siblings (get/delete/list) by focusing on write operations. The overwrite behavior adds precision.

    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 or updating memories, but it does not explicitly state when to use this tool versus alternatives like 'get_memory' or 'delete_memory'. There are no stated exclusions or preferences, so guidance is minimal.

    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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