hyperspell-mcp

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by hyperspell

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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose: adding content (files/memories), retrieving collections/documents, and searching. No overlap exists, as tools target specific resources and actions like 'Add File' vs. 'Add Memory' or 'Get Collection' vs. 'Get Document'.
Naming Consistency3/5
Naming is mixed with inconsistent patterns: 'Add File' and 'Add Memory' use verb-noun but with capital letters, while 'Get Collection', 'Get Document', 'List Collections', and 'Search Hyperspell' use verb-noun with varying capitalization and one tool including the server name. This makes it readable but lacks a uniform convention.
Tool Count5/5
With 6 tools, the count is well-scoped for a document management server, covering core operations like adding, retrieving, listing, and searching without being too sparse or bloated. Each tool earns its place in the workflow.
Completeness4/5
The toolset covers essential CRUD-like operations for a document repository: adding content, retrieving collections/documents, and searching. Minor gaps exist, such as no update or delete tools, but agents can likely work around this for basic usage without significant failures.
Average 2.8/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
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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?
No annotations are provided, so the description carries the full burden. It states the action ('Get a document') but doesn't disclose behavioral traits such as whether it's a read-only operation, requires authentication, has rate limits, or what happens on errors (e.g., if the document doesn't exist). The description is minimal and lacks essential context for safe and effective use.
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 with no wasted words. It's front-loaded and appropriately sized for a simple tool, making it easy to parse quickly.
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 the tool's complexity (simple retrieval), lack of annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't explain return values, error handling, or operational context, leaving significant gaps for an AI agent to understand how to invoke it correctly.
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?
The input schema has 1 parameter with 0% description coverage, and the tool description doesn't add any meaning beyond the schema. It mentions 'document_id' indirectly but doesn't explain its format, constraints, or how to obtain it. With low schema coverage, the description fails to compensate, leaving the parameter poorly documented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get a document from a collection' clearly states the action (get) and resource (document), but it's vague about what 'get' entails (e.g., retrieve, fetch, read) and doesn't distinguish it from sibling tools like 'Get Collection' or 'Search Hyperspell'. It's not tautological but lacks specificity.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a document ID), exclusions, or comparisons to siblings like 'Get Collection' (for collections) or 'Search Hyperspell' (for searching). Usage is implied by the name but not explicitly stated.
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 states the tool searches but doesn't disclose behavioral traits such as whether it's read-only or destructive, authentication needs, rate limits, or what the search results look like. This is a significant gap for a search tool with no annotation coverage.
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 with no wasted words. It's appropriately sized and front-loaded, clearly stating the tool's purpose without unnecessary elaboration.
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 the complexity of a search tool with no annotations, 0% schema coverage, and no output schema, the description is incomplete. It lacks details on behavior, parameters, and expected results, making it inadequate for the agent to use the tool effectively without additional context.
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%, and the description doesn't add any meaning beyond the input schema. It doesn't explain what the 'query' parameter should contain (e.g., keywords, filters, syntax) or how it affects the search, leaving the parameter undocumented in both schema and description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool searches for documents and data in Hyperspell, which is a clear purpose. However, it's somewhat vague about what 'documents and data' specifically means and doesn't differentiate from sibling tools like Get Document or List Collections, which might retrieve similar resources.
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 is provided on when to use this tool versus alternatives like Get Document or List Collections. The description doesn't mention any context, prerequisites, or exclusions for usage, leaving the agent to infer based on tool names alone.
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 carries the full burden of behavioral disclosure. It states the action ('Add') but doesn't explain what 'Add' entails—e.g., whether it uploads, links, or imports, what permissions are needed, if it's idempotent, or what happens on failure. This leaves significant gaps for a mutation tool.
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 with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly.
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 mutation tool with no annotations, 0% schema coverage, and no output schema, the description is inadequate. It lacks details on behavior, error handling, return values, and how it differs from siblings, failing to provide a complete picture for safe and effective use.
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?
The input schema has 1 parameter with 0% description coverage, so the description must compensate. It mentions 'from a URL' which implies the 'url' parameter is for a web address, but doesn't specify format constraints, supported protocols, or size limits. This adds minimal value beyond the schema's basic type.
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 the action ('Add a file or website') and the target system ('to Hyperspell'), which is specific and unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'Add Memory' or 'Search Hyperspell', which might have overlapping functionality for adding content.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, exclusions, or compare it to sibling tools like 'Add Memory' or 'Search Hyperspell', leaving the agent to infer usage context.
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 states the tool adds content but doesn't disclose behavioral traits like permissions needed, whether it's idempotent, rate limits, or what happens on success/failure. This is a significant gap for a mutation tool.
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 with no wasted words. It's appropriately sized and front-loaded, making it easy to parse quickly.
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 the tool's mutation nature, lack of annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't cover key aspects like return values, error handling, or detailed parameter usage, leaving the agent with insufficient context.
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 schema provides no parameter details. The description mentions 'plain text document or memory' but doesn't explain the 'text' or 'title' parameters, their formats, or constraints. It adds minimal value beyond the schema.
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 the action ('Add') and resource ('a plain text document or memory to Hyperspell'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'Add File' or 'Search Hyperspell', which could involve similar resources or actions.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context, or exclusions, leaving the agent to infer usage based on tool names alone.
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 carries the full burden of behavioral disclosure. It states it 'Get[s] a list', implying a read-only operation, but doesn't mention permissions, rate limits, pagination, error handling, or what format the list returns. This leaves significant gaps for a tool that presumably accesses data.
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 with zero wasted words. It's appropriately sized for a simple tool and front-loaded with the core action, making it efficient and easy to parse.
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 the tool's simplicity (1 parameter, no output schema, no annotations), the description is incomplete. It doesn't cover behavioral aspects like response format or error cases, and with low schema coverage, it fails to fully explain the parameter. For a data retrieval tool, this leaves the agent with insufficient context.
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?
The input schema has 1 parameter with 0% description coverage, so the description must compensate. It mentions 'collection_name' implicitly via 'collection', but doesn't explain what a collection is, valid values, or constraints. This adds minimal semantic value beyond the schema's basic structure.
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 the verb ('Get') and resource ('list of all documents in a collection'), making the purpose understandable. However, it doesn't explicitly distinguish this tool from its sibling 'Get Document', which likely retrieves a single document rather than all documents in a collection.
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?
The description provides no guidance on when to use this tool versus alternatives like 'Get Document' or 'List Collections'. It mentions 'all documents in a collection', but doesn't clarify prerequisites, exclusions, or specific contexts for usage.
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 carries full burden for behavioral disclosure. It mentions retrieving a list but doesn't specify whether this is paginated, sorted, or includes metadata. For a list operation with zero annotation coverage, this leaves significant behavioral questions unanswered.
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 states exactly what the tool does without any wasted words. It's appropriately sized for a simple list operation and front-loads the key 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?
For a simple list tool with no parameters and no output schema, the description is adequate but has clear gaps. It doesn't explain what format the list returns (e.g., array of names vs. full objects) or any behavioral aspects like ordering or limits, which would be helpful given the lack of annotations and output schema.
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 has zero parameters with 100% schema description coverage, so the schema already fully documents the input structure. The description appropriately doesn't discuss parameters, maintaining focus on the tool's purpose. Baseline for zero parameters is 4.
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 the action ('Get a list') and resource ('all collections on Hyperspell'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'Get Collection' or 'Search Hyperspell', which prevents a perfect score.
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?
The description provides no guidance on when to use this tool versus alternatives like 'Get Collection' (for single collection) or 'Search Hyperspell' (for filtered searches). It simply states what the tool does without context about appropriate use cases.
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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