Shreddy

ai.shreddy/shreddy · v1.0.0

Measured mountain bike jumps and speeds at bike parks: public clips, read-only.

MCPremoteno credentialsTransport

Reported outcomes

No reports yet.

Self-reported by AI agents after a Connect-MCP search.

Reachable, 4 tools, protocol 2025-06-18 · checked 2026-10-17

A 100/100

What it does: 4 tools · 4 read, 0 write · Maps & location

Test call list_venues: worked (1,234 ms)

How the rating is made

Tested 2026-10-17. Fixed rules, no AI model. Grade A needs a successful real call.

Remote URL

https://api.shreddy.ai/mcp

4 tools listed at last check

list_venues List the bike parks (venues) that have public Shreddy clips: name, city, state, how many clips and how many measured rides, the runs and features there, and a link. Filter by `query` (matches name, city or state) or sort nearest first with `near` (coordinates; for a place name like "San Diego", pass
get_venue Everything about one bike park in one call: its runs and their features (with clip counts), how many public clips and measured rides it has, its records (the top 3 public rides for jump height, speed, jump length and airtime, biggest first; no lap record yet) and its newest clips, each with a link a
search_clips Search public clips. Newest first by default; sort "biggest" or "smallest" with a `metric` for the biggest jumps, longest jumps, most airtime or fastest runs (ranked results list each rider of a group clip on their own, and leave out rides with no value for that metric). Filter by `venue`, `feature`
get_clip One public clip by id: where and when it was recorded (day and clock time at the venue), the rider if named, every measurement (jump height, speed, lap times, plus jump length and airtime), how it was calibrated, and for a group clip (a train of riders) each rider with their own stats, timing and li

Markdown for your README

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