Hospital Data MCP Server

by Nniol

Overview Schema Related Servers Score Discussions

Python

Hybrid

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
Most tools target distinct data types (drug info, vital signs, patient info, medical info). The only overlap is wxoGetPatient360, which explicitly aggregates the individual patient-related getters, but its purpose as a composite view is clear from the description.
Naming Consistency5/5
All tools follow the exact same 'wxoGet' + PascalCase noun pattern, creating a predictable and uniform naming convention. The minor typo in 'DrugInterations' does not affect the consistent structure.
Tool Count5/5
With 8 tools, the server is well-scoped for a hospital data access API. The number is within the ideal 3-15 range and each tool serves a clear query purpose.
Completeness3/5
The tool set covers core patient, medical, vital signs, and drug-related queries, but lacks search/list operations (e.g., find patients, search drugs) and any write capabilities. While likely read-only, the absence of basic lookup endpoints creates notable gaps for general hospital data exploration.
Average 3.3/5 across 8 of 8 tools scored. Lowest: 2.7/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of disclosing behavior. It only states that it 'retrieves information,' implying a read-only operation, but does not mention return format, error behavior, or whether 'None' means no results. The phrase 'or None' hints at a possible return value but is not elaborated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no fluff, making it highly concise. However, the placement of 'or None' creates an awkward grammatical structure that slightly harms readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no usage guidance and minimal behavioral disclosure, the description is incomplete for a tool that has multiple siblings and an ambiguous return statement. It does not explain what constitutes an 'alternative treatment' or how results are presented, making it insufficient for an agent to confidently invoke this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description says 'for a given drug,' which clarifies that the drug_name parameter refers to the drug for which alternatives are sought. This adds some meaning beyond the schema, but it does not detail expected format or behavior when the drug is not found. Since schema coverage is 0%, this minimal clarification gives a baseline score of 3.
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 identifies the tool's function: 'Retrieves information about alternative treatments for a given drug.' This distinguishes it from sibling tools like wxoGetDrugInterations and wxoGetDrugContraindications. However, the suffix 'or None' is ambiguous and could confuse readers about whether the tool returns None or accepts None.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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. With multiple drug-related siblings, the description should clarify that this is for alternative treatment options, but it does not. There is no mention of prerequisites or expected use cases.
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 of behavioral disclosure. It mentions the return content and the possibility of 'None', but lacks detail on error handling, permissions, or output structure. The behavior is minimally transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence and fairly concise, but contains a typo ('inforamation') and awkward phrasing ('or None'). It is not fully polished but avoids unnecessary 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?
For a simple one-param tool with an output schema, the description gives a basic overview of what is returned. However, it does not explain when 'None' is returned, nor does it address potential errors or access considerations. Adequate but with clear 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?
Schema coverage is 0%, so the description should compensate, but it says nothing about the patient_id parameter. The parameter name is inferable, but no format, validation, or meaning is provided 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 tool returns comprehensive patient medical information covering diagnosis, allergies, and prescriptions, which distinguishes it from sibling tools like vital signs or drug information. However, the phrase 'or None' is slightly ambiguous, and 'comprehensive' is vague.
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 explicit guidance is given on when to use this tool versus siblings like wxoGetPatientInformation or wxoGetVitalSignsInformation. The context is implied by the description, but no exclusions or alternatives are mentioned.
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 full responsibility. It discloses that it may return None when the drug is not found, but does not state read-only behavior, error handling, or the scope of 'comprehensive' information.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence and front-loaded. It is concise, though the typo 'inforamation' and redundancy of 'drug medical' are minor flaws.
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?
An output schema exists, so return values need not be described. However, the description is vague about what 'comprehensive' includes and lacks usage context, though it covers a simple single-parameter lookup adequately.
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%, so the description needed to compensate. It only mentions 'for a given drug', which restates the drug_name parameter, and does not add details like whether generic or brand names are accepted.
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 uses a clear verb 'Returns' and identifies the resource as 'comprehensive drug medical information', with a note about returning None. However, it does not differentiate this from sibling tools like wxoGetDrugInterations or wxoGetDrugContraindications, which also return drug-related information.
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 sibling tools. It lacks any mention of use cases, prerequisites, or when to choose an alternative.
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 of disclosing behavior. It only discloses that it returns information or None, which suggests a read-only query. It does not specify conditions for None, error handling, authentication, or rate limits. This is minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence, front-loaded, and contains no fluff. It includes a typo ('inforamation') and the word 'comprehensive' adds little but does not detract significantly. Overall, it is appropriately concise.
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 tool is simple with one parameter and an output schema. The description covers the core purpose and return possibility, but lacks usage distinction from siblings and behavioral details. It is adequate for a basic query but leaves the agent to infer when to use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for documenting the parameter. It only says 'for a given drug', which refers to drug_name but does not define format, accepted values, or required syntax. It adds little beyond the schema's property title.
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 returns drug contraindication information for a given drug. It uses a specific verb ('Returns') and resource, and the mention of 'or None' clarifies the return. It distinguishes from sibling tools like wxoGetDrugInterations and wxoGetDrugInformation by focusing on contraindications specifically.
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 provides no explicit guidance on when to use this tool versus alternatives. 'For a given drug' implies a drug-related query, but there is no mention of alternatives or exclusions. Usage is implied rather than 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 discloses that the tool may return None, which is a behavioral trait, but it does not state permissions, side effects (read-only is implied but not explicit), or error conditions. This minimal disclosure is insufficient for full transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that front-loads the purpose. It is efficient, though it contains a typo ('inforamation') and could be more polished.
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, return value details are likely covered. However, the description does not mention interaction severity levels, required input format, or behavior when a drug is not found (except the implied None). For a simple tool, this is adequate but not 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 schema has no descriptions for the two parameters, and the description only rewords 'two given drugs' without adding specific format requirements (e.g., generic vs brand names) or clarifying edge cases. It adds little beyond the parameter names.
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 returns drug interaction information for two specified drugs. It uses a specific verb ('Returns') and resource ('drug interaction medical information'), and the 'two given drugs' scope distinguishes it from sibling tools like drug information or contraindications.
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 one has two drugs to check for interactions, but it does not explicitly contrast with alternatives or state when not to use. The context is clear but lacks exclusionary guidance that would be valuable given the sibling tools.
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 full transparency burden. It reveals the tool returns patient info, medical data, and recent vital signs, but doesn't disclose read-only status, error handling, or any side effects. The description offers basic behavioral context 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?
A single, front-loaded sentence that clearly states input and output with no redundant words. Every word contributes to understanding the tool's purpose.
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?
With an output schema present, the description doesn't need to explain return values. It provides essential context for the tool's purpose and input, though the exact composition of the '360 view' could be clearer. It suffices for a simple one-parameter tool.
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 schema has 0% description coverage, yet the description merely restates the parameter name ('Given a patient id') without adding format, source, or validation details. It adds no meaningful semantic value beyond the property name itself.
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 'construct' and identifies the resource as a patient, listing the key data categories (information, medical data, vital signs). It clearly differentiates from sibling tools that focus on single aspects like drug info or vital signs by presenting a holistic 360-degree view.
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?
No explicit guidance is given on when to use this tool versus sibling tools, though the description implies it is for a comprehensive patient snapshot. It doesn't name alternatives or provide when-not-to-use scenarios, so usage context is implied rather than 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?
The description adds the behavioral detail that the tool returns 'or None,' indicating a possible absence of data. It also specifies the scope of information returned. However, there is no mention of permissions, security, or error behavior, which is a notable gap given the healthcare context and lack of 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 a single, front-loaded sentence that conveys the core function and key exception return value without redundancy. Every word 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?
Given the tool's simplicity (one parameter, read-like operation) and the existence of an output schema, the description adequately covers the essential aspects: what it returns and the None case. It does not need to detail return structure since the output schema handles that.
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 schema has one parameter, patient_id, with 0% description coverage. The description does not explain the parameter's purpose or format beyond what the schema already provides, so it adds no value to parameter understanding.
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: 'Returns basic patient information from the healthcare database.' It lists specific data categories (personal details, contact information, insurance data), which distinguishes it from sibling tools focused on drugs or vitals.
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?
Usage is implied by listing the type of data returned; when a user needs basic patient info, this tool is appropriate. However, it does not explicitly mention when to use it over alternatives, nor does it state exclusions or prerequisites.
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 full burden. It discloses the data source and the possibility of returning None, which is useful. However, it does not mention permissions, error behavior, or side effects, leaving some gaps for a read operation.
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 that leads with the action and includes a clear list of data types. 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?
The description is adequate for a simple getter but lacks parameter semantics and usage context. The output schema is present, so return values are covered, but the purpose is clear enough to be minimally 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?
Schema description coverage is 0% and the description does not explain any of the three required parameters. Patient_id is somewhat inferable from context, but age and sex are unexplained. The description adds no meaning beyond the schema's field names.
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 returns patient vital signs with a specific list of data types (blood pressure, pulse, etc.), and the verb 'Returns' plus resource 'vital signs' differentiates it from sibling tools that handle drug or medical information.
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 implies usage when vital sign data is needed, and the explicit source ('from the bedside system') gives clear context. It does not mention exclusions or alternatives, but the sibling tools are clearly distinct, so context is sufficient.
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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