Oura MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation3/5
The tools have clear distinctions between readiness, resilience, and sleep data types, but there is significant overlap between the 'get_X_data' and 'get_today_X_data' pairs. An agent might confuse which tool to use for today's data versus a date range, though the descriptions clarify the difference.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern with 'get_' prefix and descriptive suffixes (e.g., 'get_readiness_data', 'get_today_sleep_data'). The naming is predictable and uniform across all six tools.
Tool Count4/5
Six tools are reasonable for a health/fitness data server, covering three data types with both date-range and today-specific variants. It's slightly over-scoped as the 'today' tools could be handled by the date-range tools with default parameters, but it's still well within an appropriate range.
Completeness3/5
The server provides read-only access to readiness, resilience, and sleep data, which aligns with Oura's typical API capabilities. However, there are notable gaps: no tools for writing or updating data (e.g., setting goals or annotations), and no coverage of other Oura metrics like activity or heart rate, limiting the surface for comprehensive health tracking.
Average 3.1/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed 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
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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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 tool returns a dictionary but lacks details on behavioral traits such as data freshness, error handling, authentication needs, or rate limits. For a read operation with zero annotation coverage, this is inadequate.
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 brief and front-loaded with the main purpose, but the 'Returns:' section is redundant as it restates the purpose without adding value. It could be more concise by omitting the second sentence or integrating it better.
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 no annotations and no output schema, the description is incomplete. It lacks details on the return format (e.g., structure of the dictionary), error conditions, or dependencies. For a tool with siblings and no structured support, more context is needed to be fully helpful.
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 0 parameters with 100% schema description coverage, so no parameter information is needed. The description doesn't add param semantics beyond the schema, but since there are no parameters, a baseline of 4 is appropriate as it doesn't need to compensate for gaps.
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 ('resilience data for today'), making the purpose understandable. It distinguishes from the sibling 'get_resilience_data' by specifying 'today', but doesn't explicitly differentiate from 'get_today_readiness_data' or 'get_today_sleep_data' beyond the resource type.
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_resilience_data' (which might fetch broader date ranges) or other 'today' tools for different data types. The description implies usage for today's resilience data but offers no explicit context or exclusions.
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 of behavioral disclosure. It states the tool 'Returns: Dictionary containing readiness data for today,' which hints at output format but lacks details on data structure, error handling, rate limits, authentication needs, or side effects. For a tool with zero annotation coverage, this is insufficient.
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 concise and front-loaded, with the core purpose stated first ('Get readiness data for today.') and a brief return note. Both sentences earn their place by clarifying scope and output. However, it could be slightly more structured (e.g., separating usage notes).
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 (0 parameters, no output schema, no annotations), the description is incomplete. It lacks context on data format, error cases, or how it differs from siblings. Without annotations or output schema, the description should provide more behavioral and usage details to be fully helpful.
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 0 parameters, and schema description coverage is 100% (though trivial). The description doesn't need to add parameter semantics, as there are none to explain. A baseline of 4 is appropriate for zero-parameter tools, as no compensation is required.
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's purpose: 'Get readiness data for today.' It specifies the verb ('Get') and resource ('readiness data') with temporal scope ('for today'). However, it doesn't explicitly differentiate from sibling tools like 'get_readiness_data' (which likely lacks the 'today' filter) or 'get_today_resilience_data' (which targets a different data type).
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 sibling tools like 'get_readiness_data' (for broader date ranges) or 'get_today_resilience_data' (for different metrics), nor does it specify prerequisites, exclusions, or contextual triggers 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 the full burden of behavioral disclosure. It states this is a read operation ('Get'), but doesn't mention authentication requirements, rate limits, error conditions, or what 'resilience data' actually contains. The return format description ('Dictionary containing resilience data') is too vague to be helpful.
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 appropriately sized and well-structured with clear sections (Args, Returns). Each sentence adds value, though the return description could be more specific. It's front-loaded with the core purpose statement.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 required parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and parameters but lacks details about what resilience data includes, how results are structured, or behavioral constraints. The absence of output schema means the return description should be more informative.
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 description adds significant value beyond the input schema, which has 0% description coverage. It specifies that both parameters are dates in ISO format (YYYY-MM-DD), clarifies they're required, and explains their purpose (defining a date range). This fully compensates for the schema's lack of descriptions.
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's purpose with a specific verb ('Get') and resource ('resilience data'), and specifies the date range scope. However, it doesn't differentiate from sibling tools like 'get_today_resilience_data' or explain what distinguishes resilience data from readiness or sleep data.
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_today_resilience_data' (which presumably fetches today's data without date parameters) or other sibling tools. There's no mention of prerequisites, constraints, or comparative 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?
No annotations are provided, so the description carries full burden. It states it 'Returns: Dictionary containing sleep data for today', which adds some behavioral context about the output format. However, it lacks details on error handling, data freshness, authentication needs, or rate limits, which are important for a data-fetching tool.
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 very concise with two short sentences, front-loading the purpose and then specifying the return format. There's no wasted text, though the structure could be slightly improved by integrating the return info more seamlessly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It covers the purpose and return format, but lacks context on data sources, update frequency, or error cases, which could help the agent use it more effectively.
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 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add parameter info, but that's appropriate here. A baseline of 4 is applied as it adequately addresses the lack of parameters.
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 ('sleep data for today'), making the purpose immediately understandable. It distinguishes from the sibling 'get_sleep_data' by specifying 'today', though it doesn't explicitly contrast with other siblings like 'get_today_readiness_data'.
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. It doesn't mention its sibling tools (e.g., 'get_sleep_data' for other date ranges or 'get_today_readiness_data' for different data types), 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?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a 'Get' operation which implies read-only, but doesn't mention authentication requirements, rate limits, error conditions, or what 'readiness data' actually contains. The return format is vaguely described as a 'Dictionary' without structure details.
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 efficiently structured with a clear purpose statement followed by well-organized Args and Returns sections. Every sentence serves a purpose with zero 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?
For a 2-parameter read operation with no output schema, the description covers the basic purpose and parameter formats adequately. However, it lacks details about what 'readiness data' contains, how results are structured, and doesn't differentiate from sibling tools, leaving gaps in contextual understanding.
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 description adds significant value beyond the schema, which has 0% description coverage. It specifies the date format (ISO format YYYY-MM-DD) and clarifies that these are start and end dates for a range. This compensates well for the schema's lack of descriptions.
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's purpose with a specific verb ('Get') and resource ('readiness data'), and specifies a date range constraint. However, it doesn't differentiate from sibling tools like 'get_today_readiness_data' which presumably serves a similar purpose for today's data only.
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_today_readiness_data' or other sibling tools. It mentions a date range but doesn't explain when date-range queries are appropriate versus single-day queries.
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 burden. It states the tool 'Get[s] sleep data' which implies a read-only operation, but doesn't disclose behavioral traits like authentication requirements, rate limits, data format details, or error handling. The description is minimal and doesn't add meaningful context beyond the basic operation.
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 appropriately sized and front-loaded with the main purpose in the first sentence. The 'Args' and 'Returns' sections are structured but slightly redundant since the schema already defines parameters. Every sentence earns its place by clarifying parameter formats and return type, though it could be more concise by integrating 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?
Given the tool's moderate complexity (2 parameters, no annotations, no output schema), the description is minimally complete. It covers the purpose and parameters adequately but lacks details on return value structure, error cases, or integration with sibling tools. Without an output schema, the 'Returns' statement is vague ('Dictionary containing sleep data'), leaving gaps in understanding the response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides clear semantics for both parameters: 'start_date' and 'end_date' are explained with format ('ISO format YYYY-MM-DD') and purpose. Since there are only 2 parameters and both are fully documented in the description, this effectively compensates for the schema gap. The baseline would be 3 with high coverage, but here the description adds significant value.
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's purpose with a specific verb ('Get') and resource ('sleep data'), and specifies the scope ('for a specific date range'). It distinguishes from siblings like 'get_today_sleep_data' by indicating date range capability rather than just today's data. However, it doesn't explicitly differentiate from other siblings like 'get_readiness_data' or 'get_resilience_data' beyond the resource type.
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 context through the date range requirement, suggesting it's for historical data retrieval. It doesn't provide explicit guidance on when to use this tool versus alternatives like 'get_today_sleep_data' for current data, or when not to use it. The context is clear but lacks specific alternatives or 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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