This server provides 15 well-named read-only tools for Oura Ring health data. Naming is consistent and action-oriented (all start with 'get_'). However, descriptions are generic and lack LLM-optimized guidance. Input schemas are present but minimal, parameters have types and descriptions but lack format constraints, enums, or validation guidance. No output schemas are documented. Error handling is not visible in the source code. All tools are read-only and follow a repetitive pattern with start_date/end_date parameters, which limits composition complexity. Overall, this is a solid but unremarkable utility server that would benefit from richer descriptions and output documentation.
Descriptions are generic and lack LLM-optimized guidance. Most descriptions (55 - 65 chars) state WHAT the tool does but omit WHEN to use it or what the output contains. Example: 'Get the multiple daily activity for a given date range.' lacks context on what 'activity' means (steps, calories, METs?) or when to call this vs other metrics.
No output schemas documented. Tools return raw API responses from Oura Ring API, but the structure and field names are not visible in tool definitions. LLMs cannot plan downstream calls or extract relevant fields without knowing what the response contains.
Expand every tool description to 150 - 250 chars. Include: (1) WHAT it returns (e.g., 'daily steps, active minutes, and energy burned'), (2) WHEN to use it vs similar tools (e.g., 'Use this for activity summaries; use get_session_routes for detailed workout-by-workout breakdowns'), (3) expected result size ('Typically returns 7 - 90 records for a weekly range'). See pattern:tool-description for examples.
Add JSON Schema format: 'date' to both start_date and end_date parameters. Replace the description text 'Must be in YYYY-MM-DD format' with schema validation. Example: { 'type': 'string', 'format': 'date', 'description': 'Start of the date range (e.g., 2024-01-15).' }. This lets clients and LLMs validate before calling.
Document output schemas for each tool. Extract the Oura Ring API documentation (https://cloud.ouraring.com/docs) and add a 'Returns' section to each tool description listing key response fields. Minimum: 'Returns an array of objects with fields: timestamp (ISO 8601), value (number), source (string).' Helps LLMs understand what data is available.
Add pagination guidance. For tools returning lists, include a note: 'This tool returns up to 50 records per request. For larger date ranges, call multiple times or use start_date/end_date to narrow the range. Pagination via next_token is supported internally but not exposed; contact the server admin if you need bulk exports.' Then, expose next_token as an optional parameter if the Oura API supports it.
Add error messages and recovery hints in tool implementation (src/mcp/mcp.py). When the Oura Ring API returns 401 (unauthorized), catch it and return: 'Authentication failed. Verify that the OURA_API_TOKEN environment variable is set correctly.' When a date range is invalid, return: 'Invalid date range: end_date must not be before start_date. Please retry with start_date ≤ end_date.'
Score history
Overall score trend
↑ 7 points across a rubric change (v1 → v2)
58/100
Scored
Grade
Overall
Spec posture
Rubric
2026-09-22
D
58
2026-07-28+
v2
2026-03-09
D
51
-
v1
auth
source verified
72/100
Get the multiple daily sleep values for a given date range.
Input parameters lack format constraints. Both start_date and end_date are strings with descriptions stating 'Must be in YYYY-MM-DD format' but no regex pattern, format property, or example in the schema. LLMs will pass invalid dates without machine-checkable constraints.
No pagination guidance in tool descriptions or parameters. Many tools operate on date ranges and may return large result sets, but there is no mention of pagination, result limits, or next_token handling in the descriptions.
Repetitive tool design with limited composition. All 14 date-range tools follow an identical pattern: accept start_date, end_date, return raw API data. This monotonous interface offers little opportunity for multi-step agent planning. E.g., no 'summarize_weekly_health' or 'compare_health_metrics' tools.
Consider adding utility tools for multi-tool workflows. E.g., 'get_weekly_health_summary' (accepts a date, returns aggregated metrics from all daily tools) or 'get_health_alerts' (flags abnormal trends). This enables agents to answer complex health questions without manually calling 15 separate tools.
Add next_token parameter to all 14 date-range tools, with description: 'Optional. For large result sets, use the next_token from the previous response to fetch the next batch of records. Omit this for the first request.' This exposes pagination without breaking the simple case.