mem-universe

by H1an1

Overview Schema Related Servers Score Discussions

Python

Remote

Server Quality Checklist

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Latest release: v0.0.1
Disambiguation5/5
Each tool serves a distinct purpose: file operations (delete, read, write), skill management (get_skill, put_skill, list_skills), and discovery (list, search). No two tools have overlapping functionality.
Naming Consistency4/5
Names are lowercase with underscores for multi-word tools (e.g., get_skill), but single-word names like delete and read break the pattern slightly. Still, the naming is predictable and readable.
Tool Count5/5
8 tools cover core operations for memory files and skills without bloat. The set is well-scoped for the stated purpose.
Completeness4/5
Covers create/read/delete for files and CRUD for skills except delete_skill. Write presumably overwrites, acting as update. Minor gap: no dedicated skill deletion tool.
Average 3.5/5 across 8 of 8 tools scored. Lowest: 2.7/5.
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 MIT License.
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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{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
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  ]
}
```
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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?
With no annotations, the description partially discloses behavior: 'Git keeps history, so it's recoverable' indicates non-permanence, but doesn't specify side effects, authorization needs, or return format details beyond the stated return object.
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 extremely concise (two short sentences) with no extraneous text. However, it may be too minimal, missing critical details, but within the conciseness dimension it scores well for brevity.
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 three parameters, no output schema, and no annotations, the description is incomplete. It fails to explain the 'reason' and 'author_agent' parameters, and doesn't specify behavior for non-existent files or confirmation requirements.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% parameter description coverage, and the description adds no information about the three parameters (path, reason, author_agent). The agent must rely solely on parameter names, which is insufficient for correct invocation.
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 'Delete a memory file.' which identifies the verb and resource. It distinguishes from siblings like read, write, list by indicating a destructive action, though not explicitly contrasting them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like write or search. The description lacks context about prerequisites or conditions, leaving the agent to infer.
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?
No annotations provided, and the description lacks behavioral details like read-only nature, pagination, or rate limits. It does not disclose if it is limited or has 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence of 11 words, front-loaded with key action and resource. Efficient but could be more structured with explicit sections.
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?
With no parameter descriptions in schema, the description does not fully cover return value semantics, pagination, or data format. Output schema exists but is not referenced, leaving gaps.
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 explains that 'layer' is the container and 'prefix' is an optional filter, adding meaning beyond the schema, but does not elaborate on parameter formats or constraints.
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?
Description clearly states the verb 'list' and resource 'entries under a layer', with optional prefix. It distinguishes from sibling tools like 'list_skills' which lists skills.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as 'read' or 'search'. The description only states what it does without context for selection.
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 must convey behavior. It discloses the BM25 ranking algorithm and return structure but omits details on idempotency, side effects, or permissions.
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?
Single sentence with no unnecessary words, though it could include more detail without being verbose.
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?
Despite having an output schema, the description is too minimal to fully guide usage for a tool with 3 parameters and no parameter explanations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the query, layer, or limit parameters, relying entirely on the schema which lacks textual 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?
Description clearly states it performs BM25 search and returns ranked results with specific fields (path, score, snippet, type), distinguishing it from sibling tools like list or read.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like list or read. It implicitly suggests searching but lacks explicit when-to-use or when-not-to-use instructions.
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?
No annotations are provided, and the description only states it is a read operation without confirming idempotency, error conditions, or return format. It implies non-destructiveness but offers minimal behavioral detail beyond the obvious.
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 that is front-loaded with the action and resource. Every word is functional, and there is no redundancy or filler.
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?
For a simple read operation with one parameter and no output schema, the description lacks key details such as what is returned (file content, metadata, etc.) and any constraints on the path. An agent would need to infer the return value, which is a significant gap.
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 adds the qualifier 'store-relative' to the 'path' parameter, which gives semantic context beyond the schema's basic type string. However, it does not describe format constraints, examples, or the relationship to the store root. Schema coverage is 0%, so the description partially compensates.
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 'Read', the resource 'single memory file', and the method 'by store-relative path'. It is concise and distinguishes from siblings like 'search' or 'list' which involve multiple files or content-based retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as 'search', 'list', or 'get_skill'. The description does not mention prerequisites, context, or exclusion criteria.
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?
No annotations are provided, so the description carries the full burden. It mentions the output format but does not disclose any behavioral traits such as ordering, pagination, error states, or side effects. The simplicity of the tool mitigates this somewhat, but more context would be helpful.
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, efficient sentence that conveys the purpose and output format without any redundancy. It is well-structured 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 zero parameters and the presence of an output schema, the description adequately covers the main functionality. However, it could be slightly improved by noting that it returns all packages (no filtering) or mentioning the default order.
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?
There are no parameters, so the schema coverage is 100%. The description does not need to add parameter information. Per guidelines, zero parameters yields a baseline of 4.
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 'List' and the resource 'stored skill packages', specifying the output format as an array of objects with 'name' and 'description'. This distinguishes it from sibling tools like 'get_skill' (single skill) and 'search' (different verb).
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 listing all skill packages, but does not provide when to use this tool over alternatives like 'search' or 'list'. No when-not-to-use or explicit guidance is given.
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 full burden. It discloses key behavioral traits: files stored byte-exact, verbatim, no frontmatter or template check, SKILL.md indexed for search, return format ({name, paths, commit}), and that it's for text files only. It does not explicitly mention whether the operation is destructive (overwrites existing?) or error conditions (e.g., missing SKILL.md), but given the constraints, the coverage is good.
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 concise, about 150 words split into two paragraphs. The first sentence immediately conveys the core action. Every sentence adds value: behavior details, comparison to write, usage instructions. No redundant or filler content. Could be slightly tighter, but overall efficient.
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 the complexity (4 params, nested object, no output schema, no annotations), the description is fairly complete: it explains the required file structure, indexing, return format, and usage steps. However, it fails to cover the 'author_agent' and 'reason' parameters, and does not mention overwrite behavior or error handling. This leaves gaps for an agent to use the tool correctly in all scenarios.
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 add meaning. It does well for 'name' (implied in path) and 'files' (package-relative paths, must include SKILL.md). However, it entirely omits 'author_agent' and 'reason', leaving two out of four parameters unexplained. This significantly reduces the value added over the raw 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 the tool's purpose: storing a runnable skill package (SKILL.md + scripts/templates) verbatim under shared/skills/<name>/. It specifies the required content (must include SKILL.md) and distinguishes it from 'write' which handles single markdown notes. The verb 'Store' and resource 'skill PACKAGE' are specific and unambiguous.
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 usage guidance: it contrasts with 'write' (no frontmatter, no template check), explains the scenario (pushing a local package), and mentions that 'get_skill' can later install it. It also notes 'text files only'. However, it does not cover when to use this over other siblings like 'search' or 'list', which are less related but could be referenced. Still, the differentiation from the most similar sibling is solid.
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?
Returns format details ({name, files: {relpath: content}}) and post-fetch behavior (installation, auto-invocation) despite no annotations. No side-effect or permission disclosure needed for a read-only 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?
Two concise sentences, no redundancy, front-loaded purpose, efficient and clear.
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 return structure, installation steps, and agent-specific behavior. Could mention how to obtain valid skill names, but overall adequate for a simple 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?
Single parameter 'name' has no description in schema (0% coverage) and description adds no further guidance on valid names or sources. However, its purpose is straightforward.
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?
Clearly states 'Fetch a whole skill package' with specific verb and resource. Distinguishes from siblings like list_skills and put_skill by focusing on retrieval.
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?
Provides installation instructions and mentions agent applicability (any agent vs Claude with auto-invocation), giving context for when to use. Lacks explicit exclusion of alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses indexing behavior, shared space semantics, type constraints for skills, and privacy warnings. All behavioral traits are clearly explained.
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?
Every sentence adds value; structured logically from core purpose to layer explanation to parameter details. No wasted words.
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?
Comprehensive for 8 parameters with no output schema. Explains return value, layer inference, type requirements, and sharing model. Minor gaps in tags/reason/source descriptions, but these are optional.
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 0% schema coverage, the description adds meaning for path, layer, type, author_agent, and content. Tags, reason, and source are not described but are optional. Compensates well.
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 'Write a memory file (also indexes it). Returns {ok, path}.' This specifies the action and resource, directly distinguishing from siblings like delete, read, and list.
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?
Explains the two layers (shared/personal) and when each is appropriate, and notes that author_agent is for provenance only. However, does not explicitly contrast with other tools or state when to avoid using it.
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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