Polar MCP

Polar Training Targets

polar_list_training_targets

Read-onlyIdempotent

List calendar training targets within a date range to review scheduled workouts, using Polar training_targets:read access.

Instructions

List calendar training targets in a date range. Requires training_targets:read.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`page`	No	Polar page number.
`after`	No	Inclusive start date. Serialized as a Polar date or date-time according to the endpoint contract.
`limit`	No	Local page-size hint used for pagination safety.
`before`	No	Exclusive end date. Serialized as a Polar date or date-time according to the endpoint contract.
`features`	No	Optional Polar v4 feature flags. Values are validated per endpoint; feature ranges that require one day are hydrated safely.
`all_pages`	No	Fetch multiple pages up to max_pages.
`max_pages`	No	Maximum pages to fetch when all_pages is true.
`privacy_mode`	No	Optional per-call privacy override. Defaults to POLAR_PRIVACY_MODE or structured. raw returns upstream Polar JSON. summary removes GPS/map details.
`response_format`	No		markdown
`explicit_user_intent`	No	Required true when privacy_mode=raw or include_gps=true (agent escalation of redaction).

Output Schema

TableJSON Schema

Name	Required	Description	Default
`count`	Yes
`records`	Yes
`endpoint`	Yes
`has_more`	Yes
`next_page`	No
`privacy_mode`	Yes
`pages_fetched`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed7 schema fields changedv0.5.4Oct 4, 2026

changedInput schema / $schema

Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"

changedInput schema / properties / after / description

Previous value: -"Only return Polar records after this time. Converted to Polar's inclusive from query parameter."New value: +"Inclusive start date. Serialized as a Polar date or date-time according to the endpoint contract."

changedInput schema / properties / before / description

Previous value: -"Only return Polar records before this time. Converted to Polar's exclusive to query parameter."New value: +"Exclusive end date. Serialized as a Polar date or date-time according to the endpoint contract."

addedInput schema / properties / explicit_user_intent

Added value: +{
+  "description": "Required true when privacy_mode=raw or include_gps=true (agent escalation of redaction).",
+  "type": "boolean"
+}

addedInput schema / properties / features

Added value: +{
+  "description": "Optional Polar v4 feature flags. Values are validated per endpoint; feature ranges that require one day are hydrated safely.",
+  "items": {
+    "minLength": 1,
+    "type": "string"
+  },
+  "type": "array"
+}

changedInput schema / properties / privacy_mode / description

Previous value: -"Optional per-call privacy override. Defaults to POLAR_PRIVACY_MODE or structured. raw returns upstream Polar JSON. summary minimizes sensitive health and profile details."New value: +"Optional per-call privacy override. Defaults to POLAR_PRIVACY_MODE or structured. raw returns upstream Polar JSON. summary removes GPS/map details."

changedOutput schema / $schema

Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"

First observedv0.3.6Jul 9, 2026

TDQS

A3.6/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint, so the safety profile is covered. The description adds the auth scope requirement, which is useful, but says nothing about pagination behavior across the 10 params or what the read returns.

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?

Two short sentences, zero filler, with the core action front-loaded before the prerequisite. Nothing in it is redundant with structured fields.

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 rich annotations, a 90%-covered schema, and an output schema present, the description only needs to anchor purpose and prerequisites, which it does. It falls short only on sibling differentiation and pagination context, which are minor given the structured coverage.

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 90%, so the schema already documents page, after, before, limit, features, privacy_mode, and the rest. The description adds no parameter-level meaning (e.g. that before is exclusive or how all_pages/max_pages interact), so baseline 3 applies.

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?

States a specific verb ('List'), resource ('calendar training targets'), and scope ('in a date range'). It is clear on its own, though it does not distinguish itself from the nearby sibling polar_list_training_target_favorites, which an agent could easily confuse it with.

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?

Gives a hard prerequisite ('Requires training_targets:read'), which is genuinely actionable. However, it offers no when-to-use guidance versus alternatives such as polar_list_training_target_favorites or polar_list_training_sessions, so selection still requires inference.

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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