Garmin MCP Server

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get_activity_fit_messages

Retrieve and parse an activity's original FIT file, returning decoded messages with units and definition numbers. Filter by message type and paginate through results, including high-frequency records when requested.

Instructions

Retrieve and generically parse an activity's original FIT file.

This is the source-of-truth endpoint for original device activity data. It returns every message and every field emitted by the FIT decoder without applying sport-specific curation. Messages remain in file order, and each field includes its decoded value plus units and definition number when available. Unknown and duplicate fields are retained.

Garmin Connect edits made after upload may be stored only in Garmin's service and are not necessarily written back into the original FIT file. This tool intentionally does not merge those service-side edits.

High-frequency record messages are counted but omitted by default. Other message types occurring more than 100 times are also inventoried but omitted from an unfiltered default response. Request those types explicitly with message_types. All returned messages are bounded by message_offset/message_limit (maximum 5000 per call); follow pagination.next_offset until absent to retrieve the full selected stream.

Use message_types to return only particular FIT message types while message_counts still inventories the complete file. For example, a strength workout can usually be inspected efficiently with ["session", "lap", "set", "exercise_title"]. Message type names are case-insensitive and should use FIT/fitparse snake_case names.

Args: activity_id: Garmin activity ID. message_types: Optional list of FIT message types to return. Omit to return low-frequency non-record message types. include_records: Include the high-frequency record stream (default false). message_offset: Zero-based offset within the selected message stream. message_limit: Maximum messages returned per call, 1-5000 (default 1000).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`activity_id`	Yes
`message_limit`	No
`message_types`	No
`message_offset`	No
`include_records`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 7, 2026

TDQS

A5/5.0

Behavior5/5

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 transparently explains that Garmin Connect edits are not merged, that high-frequency records are omitted by default, that message types are case-insensitive, that pagination is enforced with a 5000 limit, and that unknown fields are retained. These behavioral details are comprehensive and prevent surprising agent behavior.

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 well-structured with a clear opening statement, then dedicated paragraphs for Garmin edits, message stream defaults, and usage examples, followed by an Args list. While it is reasonably long, every sentence serves a purpose—explaining source-of-truth behavior, pagination, case-insensitivity, and parameter details. No redundancy or filler; the length is justified by the tool's complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (pagination, message type filtering, default exclusions) and the absence of an output schema, the description provides all necessary context for correct invocation. It covers pagination steps, parameter constraints, and behavioral nuances. The agent has enough information to call this tool correctly without ambiguity.

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?

The input schema provides no descriptions (0% coverage), so the description fully compensates. It explains each parameter: activity_id, message_types (including FIT naming conventions and default null behavior), include_records (default false), message_offset, and message_limit (with range 1-5000 and default 1000). The parameter semantics are complete and add significant meaning beyond the bare 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 tool's purpose: 'Retrieve and generically parse an activity's original FIT file.' It emphasizes source-of-truth raw data, distinguishes from Garmin Connect edits, and differentiates from related tools like get_activity_fit_data by highlighting it returns every message without sport-specific curation. The purpose is explicit and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool (when raw, unedited FIT data is needed) and includes practical examples like using message_types=['session', 'lap', 'set', 'exercise_title'] for strength workouts. It explains default behaviors (record messages omitted, pagination limits) and how to request specific message types. This gives the agent clear, actionable direction.

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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