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JavaScript
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strava_routes

Fetch paginated public route recommendations for a chosen sport, country, and region—covering hiking, road/mountain/gravel biking, and trail running.

Instructions

Strava route-index listing for a sport, country, and region. Returns a page of Strava's public route recommendations for a sport, country, and region (state, or state/city). sport values: hiking, road-biking, mountain-biking, trail-running, gravel-biking. Public data, sourced from Strava's own server-rendered route pages.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number, starting at 1
sportYesRoute sport. Allowed values: hiking, road-biking, mountain-biking, trail-running, gravel-biking
regionYesRegion slug: a state (colorado) or state/city (colorado/boulder)
countryYesCountry slug, e.g. usa

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.17.5
    • addedInput schema / properties / sport / enum
      Added value: +[
+  "hiking",
+  "road-biking",
+  "mountain-biking",
+  "trail-running",
+  "gravel-biking"
+]
  2. Added

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the transparency burden. It discloses that data is public and sourced from server-rendered pages, implying no auth and a scraping-based read. However, it does not detail pagination behavior, error handling, or output characteristics, so it adds some value but is not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, front-loading the main purpose and including the sport enum. It is efficient with no fluff, though the enum list duplicates the schema—minor redundancy but not problematic.

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

Completeness3/5

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

For a simple listing tool with no output schema, the description covers input semantics but not what the returned page contains (e.g., route fields, sorting). With no output schema provided, the description should compensate, but it leaves the agent guessing about the response structure, making it adequate but incomplete.

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 coverage is 100% — all parameters have descriptions in the schema. The description repeats the sport enum and region format (state vs state/city) but adds no new meaning beyond the schema, meeting the baseline for high schema coverage.

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?

The description states a specific purpose: listing public route recommendations for a sport, country, and region. It identifies the resource (route-index listing) and scope. However, it does not explicitly differentiate from sibling tools like strava_route_detail or strava_challenges, so it's clear but not fully distinguishing.

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?

The description implies usage when you need public routes for a sport and region, but it does not specify when to use this over other Strava tools or provide any exclusions. No alternative guidance is given, leaving the agent to infer context.

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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