Skip to main content
Glama

get_activity_streams

Retrieve time-series data for a Garmin activity, including heart rate, speed, altitude, and more, with optional field selection and bucketed averaging.

Instructions

Time series for one activity — heart rate, pace, altitude and so on.

Args: activity_id: The activity's id. fields: Which series to return. Defaults to heart_rate, speed and altitude. Available: heart_rate, speed, altitude, cadence, power, distance, temperature, grade, lat, lon, vertical_oscillation, stance_time, step_length, respiration_rate. max_points: How many points per series (default 200, capped at 2000).

Series are averaged into buckets rather than returned raw — a three-hour ride holds around 11 000 samples per channel. Output is columnar: {"heart_rate": [...], "elapsed_s": [...]}.

Because the series is smoothed, its own highest and lowest values understate the real ones. Read peaks from true_range, which is computed over every sample.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsNo
max_pointsNo
activity_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

No annotations are provided, so the description fully carries the burden of behavioral disclosure. It explains that series are averaged into buckets, output is columnar, smoothed values understate real peaks, and true_range provides the real extremes. This is thorough and actionable.

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 header, parameter list, and behavioral notes. Every sentence adds value—the example about samples per channel helps justify max_points. No fluff or redundancy.

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?

Despite having an output schema, the description also details the return format and data processing, making it complete for a tool of this complexity. It covers both parameter semantics and edge-case behavior (smoothing, true_range) without requiring additional external knowledge.

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 schema has zero description coverage, so the description must explain all parameters. It does so comprehensively: activity_id, fields with available options, and max_points with defaults and caps, adding meaning beyond the raw 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 returns time series data for a single activity, listing the data types (heart rate, pace, altitude). It distinguishes from siblings by specifying 'one activity' and the columnar output format.

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 clearly scopes the tool to retrieving time series for a single activity, which implies when to use it. It does not explicitly name alternative tools for other use cases, but the context is clear enough for a user to decide.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/NoaMatout/garmin-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server