doctor-of-credit-mcp

by monroedean

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
Each tool has a clearly defined role, from general content browsing (list_categories, get_post, get_recent_posts, search_posts) to specialized offer lookups (find_bank_bonuses, find_credit_card_offers). Minor overlap exists between compare_offers and get_post (batch vs single retrieval) and between find_* tools and search_posts, but descriptions are clear enough to guide selection.
Naming Consistency5/5
All tool names follow a consistent snake_case verb_noun pattern (list_categories, get_post, search_posts, compare_offers, find_bank_bonuses, etc.). No camelCase or inconsistent verb styles are present, making the naming highly predictable.
Tool Count5/5
With 8 tools, the server is well-scoped for its purpose as a Doctor of Credit content interface. It covers essential browsing and searching actions without unnecessary bloat, fitting comfortably within the ideal 3-15 tool range.
Completeness5/5
The tool set provides comprehensive coverage for a read-only content API: listing categories, retrieving posts by ID/URL, browsing recent posts, searching, and specialized queries for bank bonuses, credit card offers, and big deals. There are no obvious gaps that would hinder an agent from accessing the available content.
Average 3.9/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 12 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?
No annotations are provided, so the description must carry the full behavioral burden. It discloses the heuristic nature ('likely notable'), the use of 'documented amount-mention signals', and the default/max limits. However, it does not mention ordering, time scoping, authentication requirements, or explicitly state that this is a read-only operation, though 'Retrieve' implies non-mutating.
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 of about 22 words that front-loads the main purpose ('Retrieve likely notable Doctor of Credit deal articles') before adding methodology and constraints. It is concise, contains no fluff, and every segment earns its place.
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 tool with one optional parameter and an output schema, the description covers the essential what, how, and limits. The output schema reduces the need to explain return values, but the description lacks explicit usage guidance and details on result ordering or recency, which would make it fully complete.
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 only parameter, 'limit', has its default, maximum, and exclusiveMinimum fully defined in the input schema. The description merely repeats 'default limit: 10; maximum: 25' without adding semantic context such as 'number of articles to return' or any behavior tied to the limit. With 0% schema description coverage, the description should compensate, but it adds no new meaning beyond the 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 verb 'Retrieve' and the specific resource 'likely notable Doctor of Credit deal articles', adding the method 'using documented amount-mention signals'. This distinguishes it from sibling tools like get_recent_posts, search_posts, and get_post by focusing on notable deals with a special signal-based selection.
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 when notable deal articles are needed, but it does not explicitly mention when to use this tool versus alternatives or when not to use it. There is no exclusionary guidance or reference to sibling tools such as search_posts, so the context is implied rather than clearly stated.
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 full burden of behavioral disclosure. It adds a concrete result limit ('up to 10') and the probabilistic nature ('likely') of the matches, which is useful. However, it does not disclose whether the operation is read-only (though 'Find' implies it), how results are ordered, what happens with no filters, or any error conditions. Given these gaps, the description is minimally transparent but not comprehensive.
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, tight sentence that front-loads the main action and includes all relevant filter information. There is no verbose or redundant content; every phrase earns its place. It is efficiently structured for quick parsing.
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?
The tool is simple with three optional parameters and an existing output schema, so the description need not explain return values. It covers the primary behavior and the filter constraints, making it sufficient for basic invocation. However, it lacks explicit usage exclusions or alternative tool references, which would enhance completeness. Given the low complexity, the description is largely adequate.
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 the description must compensate for parameter meaning. It does rephrase each parameter into human-readable filter concepts: 'issuer', 'card-name', and 'minimum source-unit bonus' map to issuer, card, and bonus_min respectively. This adds meaning beyond the raw parameter names, but it does not specify formats, matching rules, or units beyond 'source-unit bonus'. The mapping is present but shallow.
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 specifies the tool's purpose: finding up to 10 credit-card offer source articles, with a specific verb ('Find') and resource ('credit-card offer source articles'). It differentiates from siblings like find_bank_bonuses by targeting credit-card offers, and its scope is distinct from generic search_posts. Though it doesn't explicitly name alternatives, the domain specificity makes its purpose unambiguous.
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 through its domain-specific phrasing and filter list, but it does not provide explicit guidance on when to use this tool versus alternatives like search_posts or compare_offers. There is no 'use this when...' or 'instead of...' guidance, so the agent must infer from the title and context. The optional filters are mentioned, but no exclusions or prerequisites are 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?
With no annotations, the description carries the full burden. It only repeats schema-visible constraints (default/max limit) and implies a read-only operation via 'Retrieve'. It does not disclose error behavior, pagination, ordering semantics, or any edge cases.
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?
One sentence with all key info front-loaded. No 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?
The tool is simple (2 optional params) and the description covers the essential invocation details. An output schema exists, so return values need not be described. Missing behavioral notes (e.g., ordering, auth) are minor given the straightforward read-only purpose.
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 gives semantic meaning to both parameters by naming 'category slug' and stating limit constraints, but this largely overlaps with the schema's pattern/default/max. Since schema description coverage is 0%, it adds some value but not enough to fully compensate.
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 ('Retrieve recent Doctor of Credit posts') and specifies the optional category filter, making it distinct from sibling tools like get_post (single post) and search_posts (search-based).
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?
It provides clear context (recent posts, optional category slug) but does not explicitly mention when not to use it or compare to alternatives like search_posts. The guidance is inferred from the description rather than stated.
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 states 'without merging or inferring their offer terms', which is a key non-destructive behavioral trait. This adds value beyond the schema and clarifies what the tool does not do. However, it does not mention return format or potential errors, though an output schema exists, reducing that need.
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, well-structured sentence of 13 words. It front-loads the verb 'Retrieve' and immediately follows with the key constraints ('up to 10', 'selected', 'without merging'). Every word earns its place with zero 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 tool with one parameter and an existing output schema, the description covers the core behavior and key constraints. It does not provide explicit usage guidance or parameter definitions, but the tool's simplicity and the presence of an output schema mitigate these gaps. The description is concise yet sufficient for a straightforward retrieval operation.
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 schema has 0% description coverage, so the description must compensate. It refers to 'selected Doctor of Credit posts', which reasonably maps to the `post_ids` parameter, but it does not explicitly state that post_ids are the IDs of the posts to retrieve. The description gives context but leaves the exact mapping implicit. Given the simplicity, a 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 clearly states the tool's function: 'Retrieve up to 10 selected Doctor of Credit posts together'. The verb 'Retrieve' and specific resource ('selected Doctor of Credit posts') make the purpose explicit. The qualifier 'without merging or inferring their offer terms' further distinguishes it from any analysis or processing, setting it apart from sibling tools like search_posts or get_big_deals.
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 when a user needs to retrieve multiple specific posts at once, but it does not explicitly state when to use this tool over alternatives. There is no direct mention of sibling tools or exclusions, such as 'for a single post, use get_post'. The context is clear but not elaborated.
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 are provided, so the description carries the burden. It discloses the result cap ('up to 10') and the heuristic nature ('likely'), which is useful, but it does not mention sorting behavior, error cases, or what happens with no filters. This is adequate but lacks depth.
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 efficiently communicates the tool's purpose, scope, and filters without any wasted words. Every element 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 the presence of an output schema, return values need not be described. The description covers the core behavior (find bank-bonus articles with filters) and the key limit (up to 10). It omits trivial details like filter combination logic (AND/OR) and default ordering, but these are not critical for a simple search tool.
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 0% schema_description_coverage, the description compensates by semantically mapping each parameter: bank→institution, state→USPS state, amount_min→minimum dollar-mention. This adds meaning beyond the bare property names, though it omits format constraints like state abbreviation style or amount units.
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 'Find' with a clear resource ('bank-bonus source articles') and scope ('up to 10 likely'), making its purpose immediately clear. It distinguishes itself from sibling tools like search_posts and find_credit_card_offers by focusing on bank-bonus articles with optional filters.
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 usage context is implied: use this tool when you need to find bank-bonus articles with optional institution, state, or amount filters. However, it does not explicitly state when not to use it or name alternatives, leaving the guidance at an implied level.
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 full burden. 'Retrieve' signals a non-destructive read operation, but no additional behavioral traits (e.g., error behavior, required permissions) are disclosed. It is a minimal but clear indication of read-only intent.
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, grammatically correct, immediately front-loads the action and target. No superfluous 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?
Given the simple single-parameter design and the presence of an output schema, the description sufficiently covers the core behavior. However, it lacks any explicit guidance on usage context or edge cases, making it adequate but not outstanding.
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 schema offers no description for url_or_id, leaving the description to explain that an integer represents an ID and a string is a URL. This adds meaningful interpretation to the parameter's polymorphic nature.
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 'Retrieve' with resource 'Doctor of Credit post' and identifies the access method 'by ID or URL,' clearly distinguishing it from sibling tools like get_recent_posts or search_posts.
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 when the caller already has a post ID or URL, but it does not explicitly state when to prefer this tool over alternatives or mention any exclusions. No comparison to siblings is given.
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 are provided, so the description must convey behavioral transparency. The term 'list' implies a safe, read-only operation, but the description does not disclose details such as ordering, whether categories are dynamically fetched, or any limitations. For a zero-parameter list, this is adequate but minimal.
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 concise sentence, front-loaded with the verb and resource. Every word contributes to clarity with no redundancy or fluff.
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 tool's simplicity (zero parameters and an output schema already defined), the description provides enough context for an agent to invoke it correctly. It does not need to explain return values since the output schema exists, and the purpose is fully captured. Slightly more context about the nature of the categories could be added, but it is not essential.
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 no parameters, so the description has no parameters to document. The baseline for zero parameters is 4, and the description correctly reflects that the operation takes no input, adding no unnecessary information.
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 (list) and the resource (categories from Doctor of Credit). It distinguishes from sibling tools that handle posts, offers, and deals, making its purpose unambiguous.
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 use when the user needs to see available categories, but it does not explicitly state when to use this tool over alternatives. No exclusions or alternative pointers are provided, though the resource name makes the intended context obvious.
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 exist, so the description carries the full burden. It discloses the default limit (10) and maximum (100), and the presence of optional filters, which is helpful. However, it omits behavioral details such as sort order, whether the search covers title/body, or read-only status (though 'search' implies read-only). Some value is added, but gaps remain.
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-length structure that front-loads the action and resource. Every clause adds value (search, filters, limits) with no waste. It is highly concise and well-structured.
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?
An output schema exists, so return values are covered. The description gives essential usage details (query, filters, limits) and is appropriate for a moderate-complexity search tool. It lacks some behavioral nuances like matching fields and ordering, but the presence of the output schema and the core information makes it reasonably complete. A small gap remains around search semantics.
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 description coverage is 0%, but the description provides meaningful natural-language mappings for all parameters: query→text, category→category slug, after→publication date, and limit→default/max. This fully compensates for the lack of schema descriptions and adds significant semantics.
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 'Search' with a clear resource 'Doctor of Credit posts' and defines scope via text search with optional filters. This distinguishes it from siblings like get_post (single post) and get_recent_posts (no text search). The purpose is immediately clear.
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 outlines what the tool does (text search, optional category/date filters) and implies its use case, but it does not explicitly state when to use this over siblings or provide exclusions. There is clear context but no explicit alternative guidance.
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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