Notory MCP server
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation2/5
The generic tools notory_get and notory_request overlap for GET operations, and the specific asset tools (notory_list_assets, notory_get_asset) are thin wrappers over the same endpoints, creating functional redundancy. An agent could easily select the wrong tool for simple read tasks.
Naming Consistency4/5All tools use the notory_ prefix with underscore-separated snake_case, and specific tools follow a verb_noun pattern (list_endpoints, list_assets, get_asset). The generic notory_get and notory_request deviate slightly from the noun-bearing structure but maintain a consistent style, making the naming mostly predictable.
Tool Count5/5Five tools is an appropriate number for an API wrapper server, providing both generic access methods and convenient specific wrappers without excessive bloat or thinness.
Completeness5/5The generic notory_request tool supports any HTTP method, enabling full CRUD operations on any endpoint, while notory_list_endpoints facilitates API discovery. The specific asset tools are redundant but do not create gaps in the surface.
Average 4/5 across 5 of 5 tools scored. Lowest: 3.2/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 4 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
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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 must disclose behavioral traits. It notes it is a 'thin wrapper over GET /api/v1/assets', implying a read-only operation, but does not detail pagination behavior, defaults, error handling, or any side effects. This provides minimal context but not a complete picture.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at two sentences, front-loaded with the core purpose ('List assets'), and contains no extraneous information. Every word adds value, making it appropriately sized and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 optional parameters, no output schema, and no annotations, the description is too sparse. It does not explain expected return values, pagination specifics (e.g., default page size), valid filter values, or how it differs from sibling tools like notory_get_asset. This leaves significant gaps for an agent trying to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 60%, so some parameters (query, status, asset_type) already have descriptions, while page and page_size rely on names. The description groups these into 'optional filters and pagination', adding minimal semantic context beyond the schema. The baseline of 3 is appropriate, as the description does not clarify the domain-specific meaning or valid values for filters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists assets with optional filters and pagination, using the specific verb 'List' and resource 'assets'. It does not explicitly distinguish from sibling tools like notory_get_asset, which likely fetches a single asset, but the 'list' vs 'get' distinction is implicit. Thus it is clear but not fully differentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is provided on when to use this tool versus alternatives. The description does not mention notory_get_asset or other siblings, nor does it state the intended context (e.g., 'use this to browse multiple assets'). The only implication is that it lists assets, which is a weak signal.
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, the description carries the full burden. It adds useful context that the data comes from the 'live OpenAPI spec of the configured instance' and supports optional substring filtering. However, it does not explicitly state that the tool is read-only or disclose potential limitations like pagination or rate limits, though the listing nature implies safety.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured: the first sentence states the core function, the second gives usage guidance, and the third briefly mentions the optional filter. Every sentence adds value with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema, the description specifies the return fields (method, path, summary) and mentions the live OpenAPI source. It provides enough context for an agent to understand what the tool returns and when to invoke it. It lacks details on edge cases (e.g., unavailable spec) but is complete for a simple discovery tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides 100% coverage with the 'search' parameter described as 'Case-insensitive substring filter on path or summary'. The description only reiterates 'filter by substring' without adding new meaning, so it meets the baseline for high schema coverage but does not exceed it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'List the available Notory API endpoints' with specific output fields (method, path, summary) and source (live OpenAPI spec). This is a specific verb+resource that distinguishes it from siblings like notory_request (which makes calls) and notory_list_assets (which lists assets).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives explicit guidance to use this tool 'before using notory_request' to discover available endpoints. This provides a clear when-to-use context and names an alternative tool, though it does not explicitly state when not to use it (e.g., for actual data retrieval).
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, the description carries the full burden for behavioral disclosure. It discloses a key security requirement ('Writes require a token with the 'write' scope'), which adds value. However, it does not mention response format, error handling, rate limits, or other runtime behaviors, leaving significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the main action, and contains no redundant or filler text. Every sentence adds essential information: what it does, the auth requirement, and the prerequisite workflow.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a generic raw API request tool, the description covers the core workflow: call any endpoint, find the path/payload via list_endpoints, and know that writes need a special token. It does not cover response handling or error cases, but given the generic nature and lack of output schema, it is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes method, path, body, and query. The description adds that payload shape is found via list_endpoints and that writes require a write-scoped token, which gives context but does not deeply explain each parameter. With 50% schema coverage, the description provides some compensation but not enough for a higher score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it can 'Call any Notory endpoint with any HTTP method', listing all supported methods. This is a specific verb+resource combination, and it distinguishes itself from the sibling tools by being a generic raw API caller rather than a specialized helper.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives explicit guidance to 'Use notory_list_endpoints first to find the right path and payload shape', which is a clear prerequisite for correct usage. It also implies this tool is for endpoints not covered by the dedicated sibling tools, though it does not explicitly name alternatives or exclusions.
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 the burden. It discloses the HTTP method (GET), implying a read-only operation, and the endpoint structure. While it doesn't mention errors or auth, the simple read nature makes this sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, self-contained sentence that includes the REST endpoint pattern. It is concise and front-loaded with the core action, with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter get tool with no output schema, the description is largely complete. It explains what it retrieves and how. It lacks explicit return-value details, but the implication is clear, and there are no complex behaviors to disclose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers the single parameter with a description ('The asset id'), and the schema description coverage is 100%. The description adds no extra meaning beyond echoing 'by its id', so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the exact action: 'Fetch a single asset by its id'. It identifies the specific resource (asset) and the operation (fetch by id), which distinguishes it from siblings like notory_list_assets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is clear: fetch one asset when you know its asset_id. It doesn't explicitly name alternatives or exclusions, but the REST endpoint pattern and 'single asset' wording imply the correct context relative to listing tools.
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 provided, the description carries the full burden of behavioral disclosure. It explicitly labels the operation as 'read-only', which is a critical safety trait. It also discloses that paths are rooted at the host and shows how to include resource IDs. This goes beyond the schema, though it does not cover all edge cases like error handling or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, with the primary purpose front-loaded in the first sentence. It efficiently packs essential information: the read-only nature, path anchoring, examples, and query parameter guidance. Every word adds value, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (generic GET, two parameters, no output schema), the description covers the key operational details: what it does, how to construct paths, and how to pass queries. It does not explicitly address when to use this over specific siblings, but for a generic tool with minimal complexity, it is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50% (path has a description, query does not). The description compensates by explaining that 'path' is rooted at the host, providing examples including an ID form, and clarifying that 'query' is for query parameters. This adds practical meaning beyond the raw schema, particularly for the otherwise undocumented 'query' parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'GET' and the resource 'any Notory endpoint', explicitly labeling it as read-only. It provides concrete path examples ('/api/v1/assets' or '/api/v1/assets/{id}'), making the tool's scope unambiguous. This distinguishes it from sibling tools like notory_get_asset, which target a specific endpoint.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this is the generic fallback for any Notory endpoint, contrasting with the more specific sibling tools. It explains how to construct paths and pass query parameters, giving clear usage context. However, it does not explicitly state when to avoid using it or mention alternatives, so it stops short of full exclusions.
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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