Strava MCP vs Sportsdataio

A side-by-side look at the Strava MCP and Sportsdataio MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.

Strava MCP logoStrava MCPSports · Local subprocess (stdio)A Model Context Protocol (MCP) server that connects to Strava API, providing tools to access Strava data through LLMs67GreatAuth: oauth 2.0Sportsdataio logoSportsdataioSports · Local subprocess (stdio)SportsDataIO MCP — wraps SportsDataIO's Big-Six sports data API (sportsdata.io)60GoodAuth: not declared

Verdict: choose Strava MCP for sports work as a local process; choose Sportsdataio for sports as a local process. You can also run both side by side in one mcpServers block.

Which MCP server should you choose?

Strava MCP logoChoose Strava MCP when

  • You need dedicated capabilities in the Sports domain.
  • You prefer a local stdio subprocess transport.
  • Its auth model fits you: OAuth 2.0.
  • You want tools like get-athlete-profile, get-athlete-stats, get-activity-details.
Explore Strava MCP

Sportsdataio logoChoose Sportsdataio when

  • You need dedicated capabilities in the Sports domain.
  • You prefer a local stdio subprocess transport.
  • You want tools like sportsdataio_injuries, sportsdataio_projections, sportsdataio_player_props.
Explore Sportsdataio

Feature & specification comparison

Rows where the two servers differ are marked.

SpecStrava MCP logoStrava MCPSportsdataio logoSportsdataio
CategorySportsSports
Quality signal67/100 · Great60/100 · Good
Install commandConfirmedConfirmed
TransportLocal subprocess (stdio)Local subprocess (stdio)
AuthOAuth 2.0Not declared
PricingBYOK (pay the provider)Not declared
Required env varsNone listedNone listed
Verified ownerCommunity listingCommunity listing
GitHub stars5000
Directory activity 2 views 0 installs 0 upvotes 2 views 0 installs 0 upvotes
Tools243

Tools & capabilities

Strava MCP tools 24

  • get-athlete-profileFetches the profile information for the authenticated athlete, including their unique numeric ID needed for other tools like get-athlete-stats.
  • get-athlete-statsFetches the activity statistics (recent, YTD, all-time) for a specific athlete using their ID. Requires the athleteId obtained from the get-athlete-profile tool.
  • get-activity-detailsFetches detailed information about a specific activity using its ID.
  • get-recent-activitiesFetches the most recent activities for the authenticated athlete.
  • list-athlete-clubsLists the clubs the authenticated athlete is a member of.
  • list-starred-segmentsLists the segments starred by the authenticated athlete.
  • get-segmentFetches detailed information about a specific segment using its ID.
  • explore-segmentsSearches for popular segments within a given geographical area.
  • star-segmentStars or unstars a specific segment for the authenticated athlete.
  • get-segment-effortFetches detailed information about a specific segment effort using its ID.
  • list-segment-effortsLists the authenticated athlete's efforts on a specific segment, optionally filtering by date.
  • list-athlete-routesLists the routes created by the authenticated athlete, with pagination.
  • +12 more on the listing page

Sportsdataio tools 3

  • sportsdataio_injuriesCurrent injuries in the NFL / NBA / MLB / NHL / CFB / CBB — returns each injured player with team, position, status (Out, Questionable, etc.) and the body part affected. Note: a free SportsDataIO trial key returns scrambled sample data, not real injuries. Example: sportsdataio_injuries({ league: "nfl", _apiKey: "your-key" })
  • sportsdataio_projectionsProjected player stats for a slate — fantasy points plus key projected stats per player. Daily sports (NBA / MLB / NHL / CBB) take a `date`; weekly sports (NFL / CFB) take `season` + `week`. Note: a free trial key returns scrambled sample data. Example: sportsdataio_projections({ league: "nba", date: "2026-01-15", _apiKey: "your-key" }) or sportsdataio_projections({ league: "nfl", season: "2025REG", week: 5, _apiKey: "your-key" })
  • sportsdataio_player_propsPlayer prop bets for a date — available betting markets and outcomes (over/under totals, payouts) across NFL / NBA / MLB / NHL / CFB / CBB. Requires a SEPARATE SportsDataIO Odds/Props API key (the Props warehouse is billed apart from Stats/Projections). Note: a free trial key returns scrambled sample data. Example: sportsdataio_player_props({ league: "nba", date: "2026-01-15", _apiKey: "your-odds-key" })

Ready-to-paste client configs

Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.

Strava MCP

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "r-huijts-strava-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@r-huijts/strava-mcp-server"
      ]
    }
  }
}

Sportsdataio

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "sportsdataio": {
      "command": "npx",
      "args": [
        "-y",
        "@pipeworx/mcp-sportsdataio"
      ]
    }
  }
}

Frequently asked questions

Strava MCP is categorized under Sports and uses a local stdio subprocess. Sportsdataio belongs to Sports and uses a local stdio subprocess. Pick Strava MCP for sports work and Sportsdataio for sports.

Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.

Strava MCP is bring-your-own-key: usage is billed by the API provider you supply a key for. Auth: oauth 2.0. Sportsdataio has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.

Yes. MCP clients support multiple servers: add r-huijts-strava-mcp and sportsdataio as separate keys in the same mcpServers object, and your assistant will call tools from either one.

On AllMCPs, Strava MCP has a quality signal of 67/100 (Great) with 2 views, 0 installs and 500 GitHub stars. Sportsdataio has 60/100 (Good) with 2 views, 0 installs and 0 GitHub stars.