Skip to main content
Glama

fitbit_get_exercises

Fetch exercise log entries from Fitbit, filterable by date range and activity type. Uses local cache for speed or live API for current data.

Instructions

Get exercise log entries (individual tracked activities).

Returns exercise sessions from the local cache by default. Use live=True to fetch from Fitbit API. Run fitbit_sync first to populate the cache.

Args: start_date: Start date as "YYYY-MM-DD", "YYYY-MM", or "30d". Default: last 30 days. end_date: End date as "YYYY-MM-DD". Default: today. exercise_type: Filter by activity name (case-insensitive substring match), e.g. "cycling", "walk", "run". Default: all types. live: If true, fetch directly from Fitbit API instead of cache.

Returns exercise entries with name, duration, calories, avg heart rate, distance, and source (auto-detect vs manual). Note: HR data from cycling may be unreliable (optical sensor vs handlebar grip).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
liveNo
end_dateNo
start_dateNo
exercise_typeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations, the description fully carries the burden. It discloses the cache-by-default behavior, the live fetch option, the need for prior sync, return fields including source, and a data-quality caveat about cycling HR. This is rich, honest behavioral context.

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 summary, parameter details, return info, and a caveat. Every sentence serves a purpose, and the length is appropriate for a tool with four parameters.

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?

Even though an output schema exists, the description adds essential behavioral detail: cache vs live source, prerequisite sync, return field list, and a data-quality note. It is fully complete for a cache-backed fetch tool.

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?

Schema description coverage is 0%, so the description must compensate. The Args section thoroughly documents all four parameters with types, formats, defaults, and examples (e.g., 'YYYY-MM-DD', '30d', case-insensitive substring match), adding meaning far beyond the 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 uses a specific verb 'Get' with a clear resource 'exercise log entries' and adds 'individual tracked activities' to clarify scope. This distinguishes it from sibling tools like fitbit_get_activity, which likely returns summary data.

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?

It clearly states when to use the tool (fetching exercise log entries), mentions the cache/default behavior, the live=True alternative, and the prerequisite to run fitbit_sync. It does not explicitly name alternative tools for exclusion, but the context is clear.

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/partymola/fitbit-mcp'

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