Skip to main content
Glama

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.4.0

  • Disambiguation5/5

    Each tool targets a distinct aspect of memory management: search, retrieval by ID or batch, listing recent or stale, forgetting, updating with lineage, and tracing lineage. There is no ambiguity between tools.

    Naming Consistency5/5

    Tool names follow a consistent verb_noun pattern in snake_case (search_memory, get_memories, list_recent, update_memory, etc.), with 'list_' and 'get_' prefixes clearly indicating the action.

    Tool Count5/5

    Eight tools cover the core memory operations without being excessive or insufficient. Each tool serves a clear purpose in the memory lifecycle.

    Completeness4/5

    The surface covers most operations (search, retrieve, list, forget, update, lineage). The only noticeable gap is the lack of a dedicated create_memory tool, though update_memory might double as creation in some contexts.

  • Average 4.2/5 across 8 of 8 tools scored. Lowest: 3.4/5.

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

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is failing
  • 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.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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 indicate readOnlyHint=true and destructiveHint=false, so the description correctly reflects read-only behavior. However, no additional behavioral details are provided beyond what's in annotations.

    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?

    Single sentence, no wasted words, efficiently communicates the core function.

    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 presence of an output schema and annotations, the description is minimally sufficient for a simple retrieval tool. But it lacks context relative to siblings like get_lineage.

    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 coverage is 0% for the single parameter 'id', and the description only adds 'by its ID' without specifying format or constraints. More detail is needed.

    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 the verb 'Retrieve' and resource 'memory' with a specific method 'by its ID'. It distinguishes from sibling tools like search_memory and list_recent.

    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 vs alternatives like search_memory or list_recent. Missing explicit context 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?

    Annotations indicate non-readonly and non-destructive. The description adds that the old memory is soft-deleted (consistent with non-destructive) and a new memory is created with distilled content. This provides behavioral context beyond annotations, though the term 'distilled' is somewhat vague.

    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, front-loaded with the core action, and contains no extraneous information. Every word contributes to meaning.

    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 covers the main process, but lacks details on edge cases (e.g., invalid id, empty content), prerequisites, or what 'distilled' means. Given low complexity and presence of output schema, it is adequate but has gaps.

    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?

    With 0% schema description coverage, the description must compensate. It mentions 'the provided content' (mapping to 'content' parameter) and 'existing memory' (mapping to 'id'), but does not explicitly describe the parameters' semantics. This is insufficient for an agent to understand the parameters without schema 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 the tool re-distills and supersedes an existing memory, with explicit mention of soft-deleting the old memory and creating a new one. This differentiates it from sibling tools like 'forget' (plain deletion) and get/retrieval tools.

    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 updating an existing memory with new content, but does not specify when to use versus alternatives (e.g., 'forget' vs 'update_memory') or any prerequisites. The guidance is implicit, not explicit.

    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 indicate read-only and non-destructive behavior. The description adds context about Weibull survival scores and access patterns, enhancing understanding beyond annotations.

    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 short paragraphs. The first sentence states the purpose, and the second adds details and recommended action. No wasted 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?

    With an output schema present and annotations covering safety, the description is mostly adequate but misses parameter explanations. The core purpose and usage context are conveyed, but the omission of parameter details reduces completeness.

    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 coverage is 0% and the description does not mention the repo or limit parameters, leaving the agent to infer their meaning from the schema alone. While parameters are intuitive, the description should ideally clarify them.

    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 lists stale memories based on age and access patterns. It distinguishes from siblings like list_recent and search_memory by focusing on staleness.

    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 explains when to use the tool (to list stale memories) and suggests next action (use forget()). It lacks explicit contrast with alternatives but provides a clear workflow.

    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 mark the tool as read-only and non-destructive. The description adds that it returns both predecessors and successors ordered oldest to newest, which is useful behavioral context.

    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 the main purpose front-loaded. No wasted words; each 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?

    Given a simple tool with one parameter, annotations, and an output schema, the description covers purpose, output structure, and use case adequately. Could elaborate slightly on response format.

    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 is 'id', and the description does not elaborate on its meaning beyond implying it's a memory ID. With 0% schema description coverage, the description could add more details about the ID format or constraints.

    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 traces the supersedes chain for a memory in both directions, distinguishing it from sibling tools like get_memory or get_memories. The verb 'trace' and resource 'supersedes chain' are specific.

    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 indicates when to use: to understand how a decision evolved over time. It does not explicitly state when not to use or mention alternatives, but the context is 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?

    Annotations already indicate readOnlyHint=true and destructiveHint=false. Description adds behavioral detail: returns a compact index, not full content, and focuses on recent entries. No contradiction.

    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: first states purpose and key alternative; second lists optional filters. Every word is necessary; no 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 presence of an output schema (not shown), description needn't detail return values. Covers purpose, filters, and a sibling distinction. Could mention ordering or recency definition, but adequate.

    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 has 0% description coverage. Description lists optional filters (repo, tag, type, agent_id) by name, providing semantic hints beyond the schema. However, no explanation of the limit parameter or effects of filters.

    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 it lists recent memories as a compact index, distinguishing from get_memories which provides full content. The verb 'list' and resource 'recent memories' are specific.

    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?

    Mentions alternative get_memories for full content, but lacks guidance on when to use list_recent vs siblings like list_stale or search_memory. Optional filters are stated but no context 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 description adds value beyond annotations by clarifying 'soft-delete' (implies reversibility) and the ownership check behavior with agent_id. Annotations indicate destructiveHint=true, which is consistent, and description elaborates on the specific behavioral nuance.

    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 three sentences, front-loaded with the primary action, and every sentence provides essential information without redundancy.

    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?

    Given the presence of an output schema and the tool's straightforward behavior, the description covers all necessary aspects: action, visibility change, conditional behavior, and error case. It is complete for an agent to decide and invoke correctly.

    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?

    With schema description coverage at 0%, the description explains the semantic of agent_id (optional, owner check) and implies id identifies the memory. This compensates for missing schema descriptions, though id's role is obvious.

    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 'soft-delete' and the resource 'memory', and the effect of no longer appearing in search results. This distinguishes it from sibling tools like update_memory and get_memory, which are not destructive.

    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 explains the condition for using agent_id and the error response when ownership mismatch, providing clear context for invocation. However, it does not explicitly state when not to use this tool versus alternatives, though the tool is unique in its purpose.

    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 indicate read-only and non-destructive. Description adds that it returns compact index (~30 tokens/result) and recommends get_memories for full content, providing useful behavioral context beyond annotations.

    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?

    Description is front-loaded with primary use case and well-structured, though slightly verbose. Every sentence adds value.

    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?

    Given presence of output schema, description covers when to use, what it returns, and optional filters. Sibling tools are listed. Complete for its purpose.

    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 0%, but description explains optional parameters (repo, agent_id, after, before) with format example. query and top_k are not described, but top_k has default in schema. Overall compensates well for low coverage.

    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 searches team knowledge and specifies use cases like before proposing architecture or when user says 'we decided'. It distinguishes from siblings by recommending get_memories for full content.

    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 tells when to use (before creating files, refactoring, etc.) and when not to (use get_memories for full content). Also provides optional filter guidance.

    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 declare readOnlyHint=true and destructiveHint=false. Description adds batching behavior info, which is useful. No contradictions. Could mention response format but output schema covers that.

    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 clear, direct sentences with no extraneous words. Purpose and usage guidance front-loaded.

    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?

    Given the tool's simplicity (one required param, output schema exists), description covers all necessary aspects: what it does, how to use it, and when to use it.

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

    Parameters5/5

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

    Schema has 0% description coverage for 'ids'. Description explains it accepts multiple IDs for batching and fetches full memory details, fully compensating for lacking schema 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?

    Explicitly states 'Fetch full memory details by IDs' and distinguishes from siblings by noting batching. Clearly indicates it retrieves content for specific IDs.

    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 advises 'Use after search_memory to get content for relevant results only', providing clear when-to-use and relationship with a sibling tool.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

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.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

distill MCP server

Copy to your README.md:

Score Badge

distill MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/5queezer/distill'

If you have feedback or need assistance with the MCP directory API, please join our Discord server