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458,095 tools. Updated 2026-08-14 22:15

"Strava" matching MCP tools:

  • Generate a segment-evidence USRProf runner profile artifact from uploaded runner evidence or an existing .usrprof source. Before using this tool, ask what profile the user wants: target race/course, target distance/elevation range, general trail profile, or insights-only profile. Do not silently use every local file or arbitrary folders; if many evidence files are available, summarize candidates and ask the user to approve a selection strategy. A USRProf is not just average pace: CourseProfiler uses segment evidence to estimate climbs, descents, runnable grades, fatigue/durability, terrain fit, uphill running limits, and pacing confidence. Evidence choice affects race-plan times and standalone athlete insights. Use this when the user does not already have an already-converted usrprof_artifact_id. Accepted evidence includes GPX/FIT/CRSProf activity files, ZIP/TAR/TAR.GZ/TGZ/TAR.XZ/TXZ archives containing those files, and .usrprof files passed as source_file artifacts from POST /api/artifact-uploads, raw_file inline content/base64, or fetchable HTTPS URLs. Archives must use purpose runner_evidence, are expanded server-side, and report skipped nested archives, duplicate contents, unsupported entries, and parse failures by filename/path. For Strava, ask the user to authenticate in the CourseProfiler browser app, use its activity filters (date, distance, elevation gain, and elapsed time) to fetch relevant Run/TrailRun activities, select activities matching the profile intent, and export/download the .usrprof; do not ask for Strava credentials in MCP. Once the browser Strava flow has produced a downloaded .usrprof, the profile is already created: do not call generate_runner_profile merely to recreate/repackage it. If the user only asked to create/download a profile, stop there. If the user wants to use that .usrprof for a race plan through MCP, upload/pass it as runner input. After this tool succeeds, pass the returned usrprof artifact ID to create_race_plan as runner.usrprof_artifact_id.
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  • Primary CourseProfiler tool for creating a personalized race plan and optional PDF. Use this after obtaining both a course input and runner input. Course input may be course_file, course.source with kind=url/artifact/raw_file, or course.crsprof_artifact_id. Do not use raw_json or reconstruct/synthesize a course from roadbooks, checkpoint tables, elevation profiles, aid-station lists, or screenshots; those are enrichment/context only and are not valid course geometry. Runner input may be runner_profile_file, runner.sources, or runner.usrprof_artifact_id. Prefer generate_runner_profile first when the user has GPX/FIT/CRSProf activity evidence or an uploaded .usrprof source but no already-converted usrprof_artifact_id; then call create_race_plan with runner.usrprof_artifact_id. Before generating a runner profile for a race plan, resolve the target course if possible and ask the user whether the profile should be target-race-specific, target-distance/elevation-specific, general trail, or insights-only; select evidence that matches the intended distance, elevation gain/loss, terrain/technicality, altitude, duration, and recency. Do not silently use all files in a local folder. Use runner.usrprof_artifact_id only for an already-converted USRProf artifact; uploaded .usrprof/source_file artifacts from POST /api/artifact-uploads must be passed through runner.sources[{kind:'artifact'}] or through generate_runner_profile. Bare local filesystem paths never work in hosted MCP clients; send inline content/base64 when the MCP client can read the file, or use the REST POST /api/artifact-uploads flow outside MCP, complete the upload, then pass the returned source_file artifact ID. There is no raw-byte MCP upload tool; get_artifact_upload_requirements only explains the REST flow. Use get_runner_profile_requirements when the user needs instructions for creating/exporting a USRProf, using Strava/browser import, or uploading GPX/FIT/CRSProf evidence. If the user provides only a race name, check the CourseProfiler race catalog manifest first, but do not rely on uniqueness alone: confirm the catalog match is the same event/course/location before using its assetPath CRSProf URL. Auto-resolution only uses exact/strong catalog matches; weak matches require explicit confirmation or an explicit course.source URL/artifact. Use search_race_catalog first when the user may need to choose among multiple matching catalog courses or when the match confidence is not clearly exact/strong. If no catalog match exists, try to resolve it to a fetchable official GPX/FIT/CRSProf URL or ask the user to upload/provide the course file or URL; do not stop at the race name. Third-party route hosts such as Wikiloc may return 403 to server fetches. If an official or third-party GPX/FIT/CRSProf URL cannot be fetched or is blocked, stop and ask the user to download the official file and upload it through POST /api/artifact-uploads, then continue with the returned source_file artifact ID. Do not create a race plan until a real route file/trusted CRSProf is available. Use import_course to create a CRSProf, enrich_course_waypoints to add structured aid stations/resources/cutoffs, then generate_course_segments before creating the race plan. Catalog CRSProf files may already include official waypoints/resources/cutoffs; if they do not, call enrich_course_waypoints or ask the user for structured aid/resource/cutoff data before segmentation. If official pages and regulation PDFs disagree, or exact aid locations are not fully listed in machine-readable form, ask the user to confirm and include only confirmed aid stations; do not invent missing locations. Route-only plans are incomplete unless the user explicitly accepts missing aid/resource details. If browsing/search is available, prefer the catalog first, then official race sources and direct GPX links over generic home pages; course-only pacing is incomplete without waypoint/resource enrichment. If runner data is missing, ask for a USRProf file/artifact or runner evidence, explain that the profile drives estimated times plus insights such as uphill running limit, durability/fatigue tendencies, downhill sensitivity, and terrain strengths/weaknesses, generate a segment-evidence runner profile with generate_runner_profile after user-approved evidence selection, and do not invent personalized fitness data. This race-plan flow creates a personalized plan/PDF only; it does not submit the course to the public catalog and does not need to. Only call submit_course when the user explicitly asks to submit/add/update a course for catalog review. Returns a top-level job with artifact role metadata; use get_job to poll and get_artifact to fetch outputs.
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  • Get Authenticated Athlete - Returns the currently authenticated athlete. Tokens with profile:read_all scope will receive a detailed athlete representation; all others will receive a summary representation.
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  • List Club Activities - Retrieve recent activities from members of a specific club. The authenticated athlete must belong to the requested club in order to hit this endpoint. Pagination is supported. Athlete profile visibility is respected for all activities.
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  • Compose a builder URL with a dedication pre-filled — the name shows on the runner's GPS watch and in the Strava activity title. Use after the user picks a route (find/generate) and decides who the heart is for. Pure URL builder, no server-side state.
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  • Convert a GPS track/route file (GPX — from Garmin, Strava exports, hiking/cycling apps, waypoints) to GeoJSON (e.g. "convert my GPS track to GeoJSON", "GPX to GeoJSON", "import my Strava route"). Returns the GeoJSON FeatureCollection as a JSON string.
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Matching MCP Servers

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    An MCP server that integrates Strava OAuth for remote connections, enabling users to authenticate with their Strava account and access Strava data through the MCP protocol.
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    MIT

Matching MCP Connectors

  • Hosted Strava MCP server that gives each user a personal URL to paste into Claude or ChatGPT. Ask about your training in plain English — pace, heart rate, overtraining, trends. More info and sign-up at https://askyourdata.health

  • Strava MCP tools for AI: athletes, activities, segments, clubs, routes. Powered by HAPI MCP server.