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When I first saw that Jest was running sl so many times, my first thought was to ask my colleague if sl is a valid command on his Mac, and of course it is not. After all, which serious engineer would stuff their machine full of silly commands like sl, gti, cowsay, or toilet ? The next thing I tried was to rename sl to something else, and sure enough all my problems disappeared: yarn test started working perfectly.
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So what does Jest have to do with Steam Locomotives?
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Nothing, that’s what. The whole affair is an unfortunate naming clash between sl the Steam Locomotive and sl the Sapling CLI. Jest wanted sl the source control system, but ended up getting steam-rolled by sl the Steam Locomotive.
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Fortunately the devs took it in good humor, and made a (still unreleased) fix. Check out the train memes!
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At this point the main story has ended. However, there are still some unresolved nagging questions, like…
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How did the crash arrive at the magic number of a relatively even 27 seconds?
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I don’t know. Actually I’m not sure if a forked child executing sl still has a terminal anymore, but the travel time of the train does depend on the terminal width. The wider it is, the longer it takes:
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🌈 ~ tput cols\n425\n🌈 ~ time sl\nsl 0.19s user 0.06s system 1% cpu 20.629 total\n🌈 ~ tput cols\n58\n🌈 ~ time sl \nsl 0.03s user 0.01s system 0% cpu 5.695 total\n
So the first thing I tried was to run yarn test in a ridiculously narrow terminal and see what happens:
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Determin\ning test\n suites \nto run..\n. \n \n ● Test\n suite f\nailed to\n run \n \nthrown: \n[Error] \n \nerror Co\nmmand fa\niled wit\nh exit c\node 1. \ninfo Vis\nit https\n://yarnp\nkg.com/e\nn/docs/c\nli/run f\nor docum\nentation\n about t\nhis comm\nand. \nyarn tes\nt 1.92s\n user 0.\n67s syst\nem 9% cp\nu 27.088\n total \n🌈 back\nstage [m\naster] t\nput cols\n \n8\n
Alas, the terminal width doesn’t affect jest at all. Jest calls sl via execa so let’s mock that up locally:
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🌈 choochoo cat runSl.mjs \nimport {execa} from 'execa';\nconst { stdout } = await execa('tput', ['cols']);\nconsole.log('terminal colwidth:', stdout);\nawait execa('sl', ['root']);\n🌈 choochoo time node runSl.mjs\nterminal colwidth: 80\nnode runSl.mjs 0.21s user 0.06s system 4% cpu 6.730 total\n
So execa uses the default terminal width of 80, which takes the train 6.7 seconds to cross. And 27 seconds divided by 6.7 is awfully close to 4. So is Jest running sl 4 times? Let’s do a poor man’s bpftrace by hooking into sl like so:
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#!/bin/bash\n\nuniqid=$RANDOM\necho "$(date --utc +"%Y-%m-%d %H:%M:%S.%N") $uniqid started" >> /home/yew/executed.log\n/usr/games/sl.actual "$@"\necho "$(date --utc +"%Y-%m-%d %H:%M:%S.%N") $uniqid ended" >> /home/yew/executed.log\n
And if we check executed.log, sl is indeed executed in 4 waves, albeit by 5 workers simultaneously in each wave:
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#wave1\n2025-03-20 13:23:57.125482563 21049 started\n2025-03-20 13:23:57.127526987 21666 started\n2025-03-20 13:23:57.131099388 4897 started\n2025-03-20 13:23:57.134237754 102 started\n2025-03-20 13:23:57.137091737 15733 started\n#wave1 ends, wave2 starts\n2025-03-20 13:24:03.704588580 21666 ended\n2025-03-20 13:24:03.704621737 21049 ended\n2025-03-20 13:24:03.707780748 4897 ended\n2025-03-20 13:24:03.712086346 15733 ended\n2025-03-20 13:24:03.711953000 102 ended\n2025-03-20 13:24:03.714831149 18018 started\n2025-03-20 13:24:03.721293279 23293 started\n2025-03-20 13:24:03.724600164 27918 started\n2025-03-20 13:24:03.729763900 15091 started\n2025-03-20 13:24:03.733176122 18473 started\n#wave2 ends, wave3 starts\n2025-03-20 13:24:10.294286746 18018 ended\n2025-03-20 13:24:10.297261754 23293 ended\n2025-03-20 13:24:10.300925031 27918 ended\n2025-03-20 13:24:10.300950334 15091 ended\n2025-03-20 13:24:10.303498710 24873 started\n2025-03-20 13:24:10.303980494 18473 ended\n2025-03-20 13:24:10.308560194 31825 started\n2025-03-20 13:24:10.310595182 18452 started\n2025-03-20 13:24:10.314222848 16121 started\n2025-03-20 13:24:10.317875812 30892 started\n#wave3 ends, wave4 starts\n2025-03-20 13:24:16.883609316 24873 ended\n2025-03-20 13:24:16.886708598 18452 ended\n2025-03-20 13:24:16.886867725 31825 ended\n2025-03-20 13:24:16.890735338 16121 ended\n2025-03-20 13:24:16.893661911 21975 started\n2025-03-20 13:24:16.898525968 30892 ended\n#crash imminent! wave4 ending, wave5 starting...\n2025-03-20 13:24:23.474925807 21975 ended\n
The logs were emitted for about 26.35 seconds, which is close to 27. It probably crashed just as wave4 was reporting back. And each wave lasts about 6.7 seconds, right on the money with manual measurement.
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So why is Jest running sl in 4 waves? Why did it crash at the start of the 5th wave?
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Let’s again modify the poor man’s bpftrace to also log the args and working directory:
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echo "$(date --utc +"%Y-%m-%d %H:%M:%S.%N") $uniqid started: $@ at $PWD" >> /home/yew/executed.log\n
From the results we can see that the 5 workers are busy executing sl root, which corresponds to the getRoot() function in jest-change-files/sl.ts
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2025-03-21 05:50:22.663263304 started: root at /home/yew/cloudflare/repos/backstage/packages/app/src\n2025-03-21 05:50:22.665550470 started: root at /home/yew/cloudflare/repos/backstage/packages/backend/src\n2025-03-21 05:50:22.667988509 started: root at /home/yew/cloudflare/repos/backstage/plugins/access/src\n2025-03-21 05:50:22.671781519 started: root at /home/yew/cloudflare/repos/backstage/plugins/backstage-components/src\n2025-03-21 05:50:22.673690514 started: root at /home/yew/cloudflare/repos/backstage/plugins/backstage-entities/src\n2025-03-21 05:50:29.247573899 started: root at /home/yew/cloudflare/repos/backstage/plugins/catalog-types-common/src\n2025-03-21 05:50:29.251173536 started: root at /home/yew/cloudflare/repos/backstage/plugins/cross-connects/src\n2025-03-21 05:50:29.255263605 started: root at /home/yew/cloudflare/repos/backstage/plugins/cross-connects-backend/src\n2025-03-21 05:50:29.257293780 started: root at /home/yew/cloudflare/repos/backstage/plugins/pingboard-backend/src\n2025-03-21 05:50:29.260285783 started: root at /home/yew/cloudflare/repos/backstage/plugins/resource-insights/src\n2025-03-21 05:50:35.823374079 started: root at /home/yew/cloudflare/repos/backstage/plugins/scaffolder-backend-module-gaia/src\n2025-03-21 05:50:35.825418386 started: root at /home/yew/cloudflare/repos/backstage/plugins/scaffolder-backend-module-r2/src\n2025-03-21 05:50:35.829963172 started: root at /home/yew/cloudflare/repos/backstage/plugins/security-scorecard-dash/src\n2025-03-21 05:50:35.832597778 started: root at /home/yew/cloudflare/repos/backstage/plugins/slo-directory/src\n2025-03-21 05:50:35.834631869 started: root at /home/yew/cloudflare/repos/backstage/plugins/software-excellence-dashboard/src\n2025-03-21 05:50:42.404063080 started: root at /home/yew/cloudflare/repos/backstage/plugins/teamcity/src\n
The 16 entries here correspond neatly to the 16 rootDirs configured in Jest for Cloudflare’s backstage. We have 5 trains, and we want to visit 16 stations so let’s do some simple math. 16/5.0 = 3.2 which means our trains need to go back and forth 4 times at a minimum to cover them all.
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Final mystery: Why did it crash?
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Let’s go back to the very start of our journey. The original [Error] thrown was actually from here and after modifying node_modules/jest-changed-files/index.js, I found that the error is shortMessage: 'Command failed with ENAMETOOLONG: sl status...‘ and the reason why became clear when I interrogated Jest about what it thinks the repos are.
While the git repo is what you’d expect, the sl “repo” looks amazingly like a train wreck in motion:
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got repos.git as Set(1) { '/home/yew/cloudflare/repos/backstage' }\ngot repos.sl as Set(1) {\n '\\x1B[?1049h\\x1B[1;24r\\x1B[m\\x1B(B\\x1B[4l\\x1B[?7h\\x1B[?25l\\x1B[H\\x1B[2J\\x1B[15;80H_\\x1B[15;79H_\\x1B[16d|\\x1B[9;80H_\\x1B[12;80H|\\x1B[13;80H|\\x1B[14;80H|\\x1B[15;78H__/\\x1B[16;79H|/\\x1B[17;80H\\\\\\x1B[9;\n 79H_D\\x1B[10;80H|\\x1B[11;80H/\\x1B[12;79H|\\x1B[K\\x1B[13d\\b|\\x1B[K\\x1B[14d\\b|/\\x1B[15;1H\\x1B[1P\\x1B[16;78H|/-\\x1B[17;79H\\\\_\\x1B[9;1H\\x1B[1P\\x1B[10;79H|(\\x1B[11;79H/\\x1B[K\\x1B[12d\\b\\b|\\x1B[K\\x1B[13d\\b|\n _\\x1B[14;1H\\x1B[1P\\x1B[15;76H__/ =\\x1B[16;77H|/-=\\x1B[17;78H\\\\_/\\x1B[9;77H_D _\\x1B[10;78H|(_\\x1B[11;78H/\\x1B[K\\x1B[12d\\b\\b|\\x1B[K\\x1B[13d\\b| _\\x1B[14;77H"https://blog.cloudflare.com/"\\x1B[15;75H__/\n =|\\x1B[16;76H|/-=|\\x1B[17;1H\\x1B[1P\\x1B[8;80H=\\x1B[9;76H_D _|\\x1B[10;77H|(_)\\x1B[11;77H/\\x1B[K\\x1B[12d\\b\\b|\\x1B[K\\x1B[13d\\b|\n _\\r\\x1B[14d\\x1B[1P\\x1B[15d\\x1B[1P\\x1B[16;75H|/-=|_\\x1B[17;1H\\x1B[1P\\x1B[8;79H=\\r\\x1B[9d\\x1B[1P\\x1B[10;76H|(_)-\\x1B[11;76H/\\x1B[K\\x1B[12d\\b\\b|\\x1B[K\\x1B[13d\\b| _\\r\\x1B[14d\\x1B[1P\\x1B[15;73H__/ =|\n o\\x1B[16;74H|/-=|_\\r\\x1B[17d\\x1B[1P\\x1B[8;78H=\\r\\x1B[9d\\x1B[1P\\x1B[10;75H|(_)-\\x1B[11;75H/\\x1B[K\\x1B[12d\\b\\b|\\x1B[K\\x1B[13d\\b|\n _\\r\\x1B[14d\\x1B[1P\\x1B[15d\\x1B[1P\\x1B[16;73H|/-=|_\\r\\x1B[17d\\x1B[1P\\x1B[8;77H=\\x1B[9;73H_D _| |\\x1B[10;74H|(_)-\\x1B[11;74H/ |\\x1B[12;73H| |\\x1B[13;73H| _\\x1B[14;73H"https://blog.cloudflare.com/" |\\x1B[15;71H__/\n =| o |\\x1B[16;72H|/-=|___|\\x1B[17;1H\\x1B[1P\\x 1B[5;79H(@\\x1B[7;77H(\\r\\x1B[8d\\x1B[1P\\x1B[9;72H_D _| |_\\x1B[10;1H\\x1B[1P\\x1B[11d\\x1B[1P\\x1B[12d\\x1B[1P\\x1B[13;72H| _\\x1B[14;72H"https://blog.cloudflare.com/" |-\\x1B[15;70H__/\n =| o |=\\x1B[16;71H|/-=|___|=\\x1B[17;1H\\x1B[1P\\x1B[8d\\x1B[1P\\x1B[9;71H_D _| |_\\r\\x1B[10d\\x1B[1P\\x1B[11d\\x1B[1P\\x1B[12d\\x1B[1P\\x1B[13;71H| _\\x1B[14;71H"https://blog.cloudflare.com/" |-\\x1B[15;69H__/ =| o\n |=-\\x1B[16;70H|/-=|___|=O\\x1B[17;71H\\\\_/ \\\\\\x1B[8;1H\\x1B[1P\\x1B[9;70H_D _| |_\\x1B[10;71H|(_)--- |\\x1B[11;71H/ | |\\x1B[12;70H| | |\\x1B[13;70H| _\\x1B[80G|\\x1B[14;70H"https://blog.cloudflare.com/"\n |-\\x1B[15;68H__/ =| o |=-~\\x1B[16;69H|/-=|___|=\\x1B[K\\x1B[17;70H\\\\_/ \\\\O\\x1B[8;1H\\x1B[1P\\x1B[9;69H_D _| |_\\r\\x1B[10d\\x1B[1P\\x1B[11d\\x1B[1P\\x1B[12d\\x1B[1P\\x1B[13;69H| _\\x1B[79G|_\\x1B[14;69H"https://blog.cloudflare.com/"\n |-\\x1B[15;67H__/ =| o |=-~\\r\\x1B[16d\\x1B[1P\\x1B[17;69H\\\\_/ \\\\_\\x1B[4d\\b\\b(@@\\x1B[5;75H( )\\x1B[7;73H(@@@)\\r\\x1B[8d\\x1B[1P\\x1B[9;68H_D _|\n |_\\r\\x1B[10d\\x1B[1P\\x1B[11d\\x1B[1P\\x1B[12d\\x1B[1P\\x1B[13;68H| _\\x1B[78G|_\\x1B[14;68H"https://blog.cloudflare.com/" |-\\x1B[15;66H__/ =| o |=-~~\\\\\\x1B[16;67H|/-=|___|= O\\x1B[17;68H\\\\_/ \\\\__/\\x1B[8;1H\\x1B[1P\\x1B[9;67H_D _|\n |_\\r\\x1B[10d\\x1B[1P\\x1B[11d\\x1B[1P\\x1B[12d\\x1B[1P\\x1B[13;67H| _\\x1B[77G|_\\x1B[14;67H"https://blog.cloudflare.com/" |-\\x1B[15;65H__/ =| o |=-~O==\\x1B[16;66H|/-=|___|= |\\x1B[17;1H\\x1B[1P\\x1B[8d\\x1B[1P\\x1B[9;66H_D _|\n |_\\x1B[10;67H|(_)--- | H\\x1B[11;67H/ | | H\\x1B[12;66H| | | H\\x1B[13;66H| _\\x1B[76G|___H\\x1B[14;66H"https://blog.cloudflare.com/" |-\\x1B[15;64H__/ =| o |=-O==\\x1B[16;65H|/-=|___|=\n |\\r\\x1B[17d\\x1B[1P\\x1B[8d\\x1B[1P\\x1B[9;65H_D _| |_\\x1B[80G/\\x1B[10;66H|(_)--- | H\\\\\\x1B[11;1H\\x1B[1P\\x1B[12d\\x1B[1P\\x1B[13;65H| _\\x1B[75G|___H_\\x1B[14;65H"https://blog.cloudflare.com/" |-\\x1B[15;63H__/ =| o |=-~~\\\\\n /\\x1B[16;64H|/-=|___|=O=====O\\x1B[17;65H\\\\_/ \\\\__/ \\\\\\x1B[1;4r\\x1B[4;1H\\n' + '\\x1B[1;24r\\x1B[4;74H( )\\x1B[5;71H(@@@@)\\x1B[K\\x1B[7;69H( )\\x1B[K\\x1B[8;68H====\n \\x1B[80G_\\x1B[9;1H\\x1B[1P\\x1B[10;65H|(_)--- | H\\\\_\\x1B[11;1H\\x1B[1P\\x1B[12d\\x1B[1P\\x1B[13;64H| _\\x1B[74G|___H_\\x1B[14;64H"https://blog.cloudflare.com/" |-\\x1B[15;62H__/ =| o |=-~~\\\\ /~\\x1B[16;63H|/-=|___|=\n ||\\x1B[K\\x1B[17;64H\\\\_/ \\\\O=====O\\x1B[8;67H==== \\x1B[79G_\\r\\x1B[9d\\x1B[1P\\x1B[10;64H|(_)--- | H\\\\_\\x1B[11;64H/ | | H |\\x1B[12;63H| | | H |\\x1B[13;63H|\n _\\x1B[73G|___H__/\\x1B[14;63H"https://blog.cloudflare.com/" |-\\x1B[15;61H__/ =| o |=-~~\\\\ /~\\r\\x1B[16d\\x1B[1P\\x1B[17;63H\\\\_/ \\\\_\\x1B[8;66H==== \\x1B[78G_\\r\\x1B[9d\\x1B[1P\\x1B[10;63H|(_)--- |\n H\\\\_\\r\\x1B[11d\\x1B[1P\\x1B[12;62H| | | H |_\\x1B[13;62H| _\\x1B[72G|___H__/_\\x1B[14;62H"https://blog.cloudflare.com/" |-\\x1B[15;60H__/ =| o |=-~~\\\\ /~~\\\\\\x1B[16;61H|/-=|___|= O=====O\\x1B[17;62H\\\\_/ \\\\__/\n \\\\__/\\x1B[8;65H==== \\x1B[77G_\\r\\x1B[9d\\x1B[1P\\x1B[10;62H|(_)--- | H\\\\_\\r\\x1B[11d\\x1B[1P\\x1B[12;61H| | | H |_\\x1B[13;61H| _\\x1B[71G|___H__/_\\x1B[14;61H"https://blog.cloudflare.com/" |-\\x1B[80GI\\x1B[15;59H__/ =|\n o |=-~O=====O==\\x1B[16;60H|/-=|___|= || |\\x1B[17;1H\\x1B[1P\\x1B[2;79H(@\\x1B[3;74H( )\\x1B[K\\x1B[4;70H(@@@@)\\x1B[K\\x1B[5;67H( )\\x1B[K\\x1B[7;65H(@@@)\\x1B[K\\x1B[8;64H====\n \\x1B[76G_\\r\\x1B[9d\\x1B[1P\\x1B[10;61H|(_)--- | H\\\\_\\x1B[11;61H/ | | H | |\\x1B[12;60H| | | H |__-\\x1B[13;60H| _\\x1B[70G|___H__/__|\\x1B[14;60H"https://blog.cloudflare.com/" |-\\x1B[79GI_\\x1B[15;58H__/ =| o\n |=-O=====O==\\x1B[16;59H|/-=|___|= || |\\r\\x1B[17d\\x1B[1P\\x1B[8;63H==== \\x1B[75G_\\r\\x1B[9d\\x1B[1P\\x1B[10;60H|(_)--- | H\\\\_\\r\\x1B[11d\\x1B[1P\\x1B[12;59H| | | H |__-\\x1B[13;59H|\n _\\x1B[69G|___H__/__|_\\x1B[14;59H"https://blog.cloudflare.com/" |-\\x1B[78GI_\\x1B[15;57H__/ =| o |=-~~\\\\ /~~\\\\ /\\x1B[16;58H|/-=|___|=O=====O=====O\\x1B[17;59H\\\\_/ \\\\__/ \\\\__/ \\\\\\x1B[8;62H====\n \\x1B[74G_\\r\\x1B[9d\\x1B[1P\\x1B[10;59H|(_)--- | H\\\\_\\r\\x1B | | H |__-\\x1B[13;58H| _\\x1B[68G|___H__/__|_\\x1B[14;58H"https://blog.cloudflare.com/" |-\\x1B[77GI_\\x1B[15;56H__/ =| o |=-~~\\\\ /~~\\\\ /~\\x1B[16;57H|/-=|___|=\n || ||\\x1B[K\\x1B[17;58H\\\\_/ \\\\O=====O=====O\\x1B[8;61H==== \\x1B[73G_\\r\\x1B[9d\\x1B[1P\\x1B[10;58H|(_)--- _\\x1B[67G|___H__/__|_\\x1B[14;57H"https://blog.cloudflare.com/" |-\\x1B[76GI_\\x1B[15;55H__/ =| o |=-~~\\\\ /~~\\\\\n /~\\r\\x1B[16d\\x1B[1P\\x1B[17;57H\\\\_/ \\\\_\\x1B[2;75H( ) (\\x1B[3;70H(@@@)\\x1B[K\\x1B[4;66H()\\x1B[K\\x1B[5;63H(@@@@)\\x1B[\n \n
Acknowledgements
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Thank you to my colleagues Mengnan Gong and Shuhao Zhang, whose ideas and perspectives helped narrow down the root causes of this mystery.
If you enjoy troubleshooting weird and tricky production issues, our engineering teams are hiring.
“],”published_at”:[0,”2025-04-02T14:00+01:00″],”updated_at”:[0,”2025-04-02T13:00:03.425Z”],”feature_image”:[0,”https://cf-assets.www.cloudflare.com/zkvhlag99gkb/1yA1TgNlIUZwtZ4bIL39EJ/0bfc765dae00213eca7e48a337c8178e/image1.png”],”tags”:[1,[[0,{“id”:[0,”2UVIYusJwlvsmPYl2AvSuR”],”name”:[0,”Deep Dive”],”slug”:[0,”deep-dive”]}],[0,{“id”:[0,”383iv0UQ6Lp0GZwOAxGq2p”],”name”:[0,”Linux”],”slug”:[0,”linux”]}],[0,{“id”:[0,”3JAY3z7p7An94s6ScuSQPf”],”name”:[0,”Developer Platform”],”slug”:[0,”developer-platform”]}],[0,{“id”:[0,”4HIPcb68qM0e26fIxyfzwQ”],”name”:[0,”Developers”],”slug”:[0,”developers”]}]]],”relatedTags”:[0],”authors”:[1,[[0,{“name”:[0,”Yew Leong”],”slug”:[0,”yew-leong”],”bio”:[0],”profile_image”:[0,”https://cf-assets.www.cloudflare.com/zkvhlag99gkb/658l52gIu4kyDjwnJCelUt/d0a7c86def68692d50d9b4a0d6fc2f18/_tmp_mini_magick20221116-43-2dcplr.jpg”],”location”:[0],”website”:[0],”twitter”:[0],”facebook”:[0]}]]],”meta_description”:[0,”Yarn tests fail consistently at the 27-second mark. The usual suspects are swiftly eliminated to no avail. A deep dive is taken to comb through traces, only to be derailed into an unexpected crash investigation.”],”primary_author”:[0,{}],”localeList”:[0,{“name”:[0,”blog-english-only”],”enUS”:[0,”English for Locale”],”zhCN”:[0,”No Page for Locale”],”zhHansCN”:[0,”No Page for Locale”],”zhTW”:[0,”No Page for Locale”],”frFR”:[0,”No Page for Locale”],”deDE”:[0,”No Page for Locale”],”itIT”:[0,”No Page for Locale”],”jaJP”:[0,”No Page for Locale”],”koKR”:[0,”No Page for Locale”],”ptBR”:[0,”No Page for Locale”],”esLA”:[0,”No Page for Locale”],”esES”:[0,”No Page for Locale”],”enAU”:[0,”No Page for Locale”],”enCA”:[0,”No Page for Locale”],”enIN”:[0,”No Page for Locale”],”enGB”:[0,”No Page for Locale”],”idID”:[0,”No Page for Locale”],”ruRU”:[0,”No Page for Locale”],”svSE”:[0,”No Page for Locale”],”viVN”:[0,”No Page for Locale”],”plPL”:[0,”No Page for Locale”],”arAR”:[0,”No Page for Locale”],”nlNL”:[0,”No Page for Locale”],”thTH”:[0,”No Page for Locale”],”trTR”:[0,”No Page for Locale”],”heIL”:[0,”No Page for Locale”],”lvLV”:[0,”No Page for Locale”],”etEE”:[0,”No Page for Locale”],”ltLT”:[0,”No Page for Locale”]}],”url”:[0,”https://blog.cloudflare.com/yarn-test-suffers-strange-derailment”],”metadata”:[0,{“title”:[0,”A steam locomotive from 1993 broke my yarn test”],”description”:[0,”Yarn tests fail consistently at the 27-second mark. The usual suspects are swiftly eliminated to no avail. A deep dive is taken to comb through traces, only to be derailed into an unexpected crash investigation.”],”imgPreview”:[0,”https://cf-assets.www.cloudflare.com/zkvhlag99gkb/4y36mkMs8GlYflk6MMmLnh/42840cf34748ac9b6619c5d47704db10/A_steam_locomotive_from_1993_broke_my_yarn_test-OG.png”]}]}],[0,{“id”:[0,”4e3J8mxEIN24iNKfw9ToEH”],”title”:[0,”Build and deploy Remote Model Context Protocol (MCP) servers to Cloudflare”],”slug”:[0,”remote-model-context-protocol-servers-mcp”],”excerpt”:[0,”You can now build and deploy remote MCP servers to Cloudflare, and we handle the hard parts of building remote MCP servers for you.”],”featured”:[0,false],”html”:[0,”
It feels like almost everyone building AI applications and agents is talking about the Model Context Protocol (MCP), as well as building MCP servers that you install and run locally on your own computer.
You can now build and deploy remote MCP servers to Cloudflare. We’ve added four things to Cloudflare that handle the hard parts of building remote MCP servers for you:
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workers-oauth-provider — an OAuth Provider that makes authorization easy
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McpAgent — a class built into the Cloudflare Agents SDK that handles remote transport
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mcp-remote — an adapter that lets MCP clients that otherwise only support local connections work with remote MCP servers
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AI playground as a remote MCP client — a chat interface that allows you to connect to remote MCP servers, with the authentication check included
The button below, or the developer docs, will get you up and running in production with this example MCP server in less than two minutes:
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Unlike the local MCP servers you may have previously used, remote MCP servers are accessible on the Internet. People simply sign in and grant permissions to MCP clients using familiar authorization flows. We think this is going to be a massive deal — connecting coding agents to MCP servers has blown developers’ minds over the past few months, and remote MCP servers have the same potential to open up similar new ways of working with LLMs and agents to a much wider audience, including more everyday consumer use cases.
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From local to remote — bringing MCP to the masses
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MCP is quickly becoming the common protocol that enables LLMs to go beyond inference and RAG, and take actions that require access beyond the AI application itself (like sending an email, deploying a code change, publishing blog posts, you name it). It enables AI agents (MCP clients) to access tools and resources from external services (MCP servers).
To date, MCP has been limited to running locally on your own machine — if you want to access a tool on the web using MCP, it’s up to you to set up the server locally. You haven’t been able to use MCP from web-based interfaces or mobile apps, and there hasn’t been a way to let people authenticate and grant the MCP client permission. Effectively, MCP servers haven’t yet been brought online.
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Support for remote MCP connections changes this. It creates the opportunity to reach a wider audience of Internet users who aren’t going to install and run MCP servers locally for use with desktop apps. Remote MCP support is like the transition from desktop software to web-based software. People expect to continue tasks across devices and to login and have things just work. Local MCP is great for developers, but remote MCP connections are the missing piece to reach everyone on the Internet.
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Making authentication and authorization just work with MCP
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Beyond just changing the transport layer — from stdio to streamable HTTP — when you build a remote MCP server that uses information from the end user’s account, you need authentication and authorization. You need a way to allow users to login and prove who they are (authentication) and a way for users to control what the AI agent will be able to access when using a service (authorization).
MCP does this with OAuth, which has been the standard protocol that allows users to grant applications to access their information or services, without sharing passwords. Here, the MCP Server itself acts as the OAuth Provider. However, OAuth with MCP is hard to implement yourself, so when you build MCP servers on Cloudflare we provide it for you.
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workers-oauth-provider — an OAuth 2.1 Provider library for Cloudflare Workers
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When you deploy an MCP Server to Cloudflare, your Worker acts as an OAuth Provider, using workers-oauth-provider, a new TypeScript library that wraps your Worker’s code, adding authorization to API endpoints, including (but not limited to) MCP server API endpoints.
Your MCP server will receive the already-authenticated user details as a parameter. You don’t need to perform any checks of your own, or directly manage tokens. You can still fully control how you authenticate users: from what UI they see when they log in, to which provider they use to log in. You can choose to bring your own third-party authentication and authorization providers like Google or GitHub, or integrate with your own.
The complete MCP OAuth flow looks like this:
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Here, your MCP server acts as both an OAuth client to your upstream service, and as an OAuth server (also referred to as an OAuth “provider”) to MCP clients. You can use any upstream authentication flow you want, but workers-oauth-provider guarantees that your MCP server is spec-compliant and able to work with the full range of client apps & websites. This includes support for Dynamic Client Registration (RFC 7591) and Authorization Server Metadata (RFC 8414).
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A simple, pluggable interface for OAuth
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When you build an MCP server with Cloudflare Workers, you provide an instance of the OAuth Provider paths to your authorization, token, and client registration endpoints, along with handlers for your MCP Server, and for auth:
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import OAuthProvider from "@cloudflare/workers-oauth-provider";\nimport MyMCPServer from "./my-mcp-server";\nimport MyAuthHandler from "./auth-handler";\n\nexport default new OAuthProvider({\n apiRoute: "/sse", // MCP clients connect to your server at this route\n apiHandler: MyMCPServer.mount('/sse'), // Your MCP Server implmentation\n defaultHandler: MyAuthHandler, // Your authentication implementation\n authorizeEndpoint: "/authorize",\n tokenEndpoint: "/token",\n clientRegistrationEndpoint: "/register",\n});\n
This abstraction lets you easily plug in your own authentication. Take a look at this example that uses GitHub as the identity provider for an MCP server, in less than 100 lines of code, by implementing /callback and /authorize routes.
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Why do MCP servers issue their own tokens?
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You may have noticed in the authorization diagram above, and in the authorization section of the MCP spec, that the MCP server issues its own token to the MCP client.
Instead of passing the token it receives from the upstream provider directly to the MCP client, your Worker stores an encrypted access token in Workers KV. It then issues its own token to the client. As shown in the GitHub example above, this is handled on your behalf by the workers-oauth-provider — your code never directly handles writing this token, preventing mistakes. You can see this in the following code snippet from the GitHub example above:
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// When you call completeAuthorization, the accessToken you pass to it\n // is encrypted and stored, and never exposed to the MCP client\n // A new, separate token is generated and provided to the client at the /token endpoint\n const { redirectTo } = await c.env.OAUTH_PROVIDER.completeAuthorization({\n request: oauthReqInfo,\n userId: login,\n metadata: { label: name },\n scope: oauthReqInfo.scope,\n props: {\n accessToken, // Stored encrypted, never sent to MCP client\n },\n })\n\n return Response.redirect(redirectTo)\n
On the surface, this indirection might sound more complicated. Why does it work this way?
By issuing its own token, MCP Servers can restrict access and enforce more granular controls than the upstream provider. If a token you issue to an MCP client is compromised, the attacker only gets the limited permissions you’ve explicitly granted through your MCP tools, not the full access of the original token.
Let’s say your MCP server requests that the user authorize permission to read emails from their Gmail account, using the gmail.readonly scope. The tool that the MCP server exposes is more narrow, and allows reading travel booking notifications from a limited set of senders, to handle a question like “What’s the check-out time for my hotel room tomorrow?” You can enforce this constraint in your MCP server, and if the token you issue to the MCP client is compromised, because the token is to your MCP server — and not the raw token to the upstream provider (Google) — an attacker cannot use it to read arbitrary emails. They can only call the tools your MCP server provides. OWASP calls out “Excessive Agency” as one of the top risk factors for building AI applications, and by issuing its own token to the client and enforcing constraints, your MCP server can limit tools access to only what the client needs.
Or building off the earlier GitHub example, you can enforce that only a specific user is allowed to access a particular tool. In the example below, only users that are part of an allowlist can see or call the generateImage tool, that uses Workers AI to generate an image based on a prompt:
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import { McpAgent } from "agents/mcp";\nimport { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";\nimport { z } from "zod";\n\nconst USER_ALLOWLIST = ["geelen"];\n\nexport class MyMCP extends McpAgent<Props, Env> {\n server = new McpServer({\n name: "Github OAuth Proxy Demo",\n version: "1.0.0",\n });\n\n async init() {\n // Dynamically add tools based on the user's identity\n if (USER_ALLOWLIST.has(this.props.login)) {\n this.server.tool(\n 'generateImage',\n 'Generate an image using the flux-1-schnell model.',\n {\n prompt: z.string().describe('A text description of the image you want to generate.')\n },\n async ({ prompt }) => {\n const response = await this.env.AI.run('@cf/black-forest-labs/flux-1-schnell', { \n prompt, \n steps: 8 \n })\n return {\n content: [{ type: 'image', data: response.image!, mimeType: 'image/jpeg' }],\n }\n }\n )\n }\n }\n}\n\n \n
Introducing McpAgent: remote transport support that works today, and will work with the revision to the MCP spec
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The next step to opening up MCP beyond your local machine is to open up a remote transport layer for communication. MCP servers you run on your local machine just communicate over stdio, but for an MCP server to be callable over the Internet, it must implement remote transport.
The McpAgent class we introduced today as part of our Agents SDK handles this for you, using Durable Objects behind the scenes to hold a persistent connection open, so that the MCP client can send server-sent events (SSE) to your MCP server. You don’t have to write code to deal with transport or serialization yourself. A minimal MCP server in 15 lines of code can look like this:
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import { McpAgent } from "agents/mcp";\nimport { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";\nimport { z } from "zod";\n\nexport class MyMCP extends McpAgent {\n server = new McpServer({\n name: "Demo",\n version: "1.0.0",\n });\n async init() {\n this.server.tool("add", { a: z.number(), b: z.number() }, async ({ a, b }) => ({\n content: [{ type: "text", text: String(a + b) }],\n }));\n }\n}\n
After much discussion, remote transport in the MCP spec is changing, with Streamable HTTP replacing HTTP+SSE This allows for stateless, pure HTTP connections to MCP servers, with an option to upgrade to SSE, and removes the need for the MCP client to send messages to a separate endpoint than the one it first connects to. The McpAgent class will change with it and just work with streamable HTTP, so that you don’t have to start over to support the revision to how transport works.
This applies to future iterations of transport as well. Today, the vast majority of MCP servers only expose tools, which are simple remote procedure call (RPC) methods that can be provided by a stateless transport. But more complex human-in-the-loop and agent-to-agent interactions will need prompts and sampling. We expect these types of chatty, two-way interactions will need to be real-time, which will be challenging to do well without a bidirectional transport layer. When that time comes, Cloudflare, the Agents SDK, and Durable Objects all natively support WebSockets, which enable full-duplex, bidirectional real-time communication.
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Stateful, agentic MCP servers
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When you build MCP servers on Cloudflare, each MCP client session is backed by a Durable Object, via the Agents SDK. This means each session can manage and persist its own state, backed by its own SQL database.
This opens the door to building stateful MCP servers. Rather than just acting as a stateless layer between a client app and an external API, MCP servers on Cloudflare can themselves be stateful applications — games, a shopping cart plus checkout flow, a persistent knowledge graph, or anything else you can dream up. When you build on Cloudflare, MCP servers can be much more than a layer in front of your REST API.
To understand the basics of how this works, let’s look at a minimal example that increments a counter:
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import { McpAgent } from "agents/mcp";\nimport { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";\nimport { z } from "zod";\n\ntype State = { counter: number }\n\nexport class MyMCP extends McpAgent<Env, State, {}> {\n server = new McpServer({\n name: "Demo",\n version: "1.0.0",\n });\n\n initialState: State = {\n counter: 1,\n }\n\n async init() {\n this.server.resource(`counter`, `mcp://resource/counter`, (uri) => {\n return {\n contents: [{ uri: uri.href, text: String(this.state.counter) }],\n }\n })\n\n this.server.tool('add', 'Add to the counter, stored in the MCP', { a: z.number() }, async ({ a }) => {\n this.setState({ ...this.state, counter: this.state.counter + a })\n\n return {\n content: [{ type: 'text', text: String(`Added ${a}, total is now ${this.state.counter}`) }],\n }\n })\n }\n\n onStateUpdate(state: State) {\n console.log({ stateUpdate: state })\n }\n\n}\n
For a given session, the MCP server above will remember the state of the counter across tool calls.
From within an MCP server, you can use Cloudflare’s whole developer platform, and have your MCP server spin up its own web browser, trigger a Workflow, call AI models, and more. We’re excited to see the MCP ecosystem evolve into more advanced use cases.
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Connect to remote MCP servers from MCP clients that today only support local MCP
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Cloudflare is supporting remote MCP early — before the most prominent MCP client applications support remote, authenticated MCP, and before other platforms support remote MCP. We’re doing this to give you a head start building for where MCP is headed.
But if you build a remote MCP server today, this presents a challenge — how can people start using your MCP server if there aren’t MCP clients that support remote MCP?
We have two new tools that allow you to test your remote MCP server and simulate how users will interact with it in the future:
We updated the Workers AI Playground to be a fully remote MCP client that allows you to connect to any remote MCP server with built-in authentication support. This online chat interface lets you immediately test your remote MCP servers without having to install anything on your device. Instead, just enter the remote MCP server’s URL (e.g. https://remote-server.example.com/sse) and click Connect.
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Once you click Connect, you’ll go through the authentication flow (if you set one up) and after, you will be able to interact with the MCP server tools directly from the chat interface.
If you prefer to use a client like Claude Desktop or Cursor that already supports MCP but doesn’t yet handle remote connections with authentication, you can use mcp-remote. mcp-remote is an adapter that lets MCP clients that otherwise only support local connections to work with remote MCP servers. This gives you and your users the ability to preview what interactions with your remote MCP server will be like from the tools you’re already using today, without having to wait for the client to support remote MCP natively.
We’ve published a guide on how to use mcp-remote with popular MCP clients including Claude Desktop, Cursor, and Windsurf. In Claude Desktop, you add the following to your configuration file:
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{\n "mcpServers": {\n "remote-example": {\n "command": "npx",\n "args": [\n "mcp-remote",\n "https://remote-server.example.com/sse"\n ]\n }\n }\n}\n \n \n
Remote Model Context Protocol (MCP) is coming! When client apps support remote MCP servers, the audience of people who can use them opens up from just us, developers, to the rest of the population — who may never even know what MCP is or stands for.
Building a remote MCP server is the way to bring your service into the AI assistants and tools that millions of people use. We’re excited to see many of the biggest companies on the Internet are busy building MCP servers right now, and we are curious about the businesses that pop-up in an agent-first, MCP-native way.
On Cloudflare, you can start building today. We’re ready for you, and ready to help build with you. Email us at 1800-mcp@cloudflare.com, and we’ll help get you going. There’s lots more to come with MCP, and we’re excited to see what you build.
“],”published_at”:[0,”2025-03-25T13:59+00:00″],”updated_at”:[0,”2025-03-25T15:11:42.693Z”],”feature_image”:[0,”https://cf-assets.www.cloudflare.com/zkvhlag99gkb/6ifiJyB00Saj3K0TtU5QWn/7c552a4795603414457c7c33c4f432a2/image2.png”],”tags”:[1,[[0,{“id”:[0,”6Foe3R8of95cWVnQwe5Toi”],”name”:[0,”AI”],”slug”:[0,”ai”]}],[0,{“id”:[0,”4HIPcb68qM0e26fIxyfzwQ”],”name”:[0,”Developers”],”slug”:[0,”developers”]}],[0,{“id”:[0,”6Lfy7VaNvl5G8gOYMKFiux”],”name”:[0,”MCP”],”slug”:[0,”mcp”]}],[0,{“id”:[0,”22RkiaggH3NV4u6qyMmC42″],”name”:[0,”Agents”],”slug”:[0,”agents”]}]]],”relatedTags”:[0],”authors”:[1,[[0,{“name”:[0,”Brendan Irvine-Broque”],”slug”:[0,”brendan-irvine-broque”],”bio”:[0,”Product Manager, Cloudflare Stream”],”profile_image”:[0,”https://cf-assets.www.cloudflare.com/zkvhlag99gkb/lTJBFKfbqthKbJKPvulre/e8bf53afa7caf1dffeeb55a8c6884959/brendan-irvine-broque.JPG”],”location”:[0,”Oakland, CA”],”website”:[0,”https://www.cloudflare.com/products/cloudflare-stream/”],”twitter”:[0,”@irvinebroque”],”facebook”:[0,null]}],[0,{“name”:[0,”Dina Kozlov”],”slug”:[0,”dina”],”bio”:[0,null],”profile_image”:[0,”https://cf-assets.www.cloudflare.com/zkvhlag99gkb/bY78cK0burCjZbD6jOgAH/a8479b5ea6dd8fb3acb41227c1a4ad0e/dina.jpg”],”location”:[0,null],”website”:[0,null],”twitter”:[0,”@dinasaur_404″],”facebook”:[0,null]}],[0,{“name”:[0,”Glen Maddern”],”slug”:[0,”glen”],”bio”:[0,null],”profile_image”:[0,”https://cf-assets.www.cloudflare.com/zkvhlag99gkb/7dtWmquDOA3nc27l0f7RwQ/43791027b587018e9003bf83e28b77df/glen.jpg”],”location”:[0,null],”website”:[0,null],”twitter”:[0,”@glenmaddern”],”facebook”:[0,null]}]]],”meta_description”:[0,”You can now build and deploy remote MCP servers to Cloudflare, and we handle the hard parts of building remote MCP servers for you. Unlike local MCP servers you may have previously used, remote MCP servers are Internet-accessible. People simply sign in and grant permissions to MCP clients using familiar authorization flows.”],”primary_author”:[0,{}],”localeList”:[0,{“name”:[0,”blog-english-only”],”enUS”:[0,”English for Locale”],”zhCN”:[0,”No Page for Locale”],”zhHansCN”:[0,”No Page for Locale”],”zhTW”:[0,”No Page for Locale”],”frFR”:[0,”No Page for Locale”],”deDE”:[0,”No Page for Locale”],”itIT”:[0,”No Page for Locale”],”jaJP”:[0,”No Page for Locale”],”koKR”:[0,”No Page for Locale”],”ptBR”:[0,”No Page for Locale”],”esLA”:[0,”No Page for Locale”],”esES”:[0,”No Page for Locale”],”enAU”:[0,”No Page for Locale”],”enCA”:[0,”No Page for Locale”],”enIN”:[0,”No Page for Locale”],”enGB”:[0,”No Page for Locale”],”idID”:[0,”No Page for Locale”],”ruRU”:[0,”No Page for Locale”],”svSE”:[0,”No Page for Locale”],”viVN”:[0,”No Page for Locale”],”plPL”:[0,”No Page for Locale”],”arAR”:[0,”No Page for Locale”],”nlNL”:[0,”No Page for Locale”],”thTH”:[0,”No Page for Locale”],”trTR”:[0,”No Page for Locale”],”heIL”:[0,”No Page for Locale”],”lvLV”:[0,”No Page for Locale”],”etEE”:[0,”No Page for Locale”],”ltLT”:[0,”No Page for Locale”]}],”url”:[0,”https://blog.cloudflare.com/remote-model-context-protocol-servers-mcp”],”metadata”:[0,{“title”:[0,”Build and deploy Remote Model Context Protocol (MCP) servers to Cloudflare”],”description”:[0,”You can now build and deploy remote MCP servers to Cloudflare, and we handle the hard parts of building remote MCP servers for you. Unlike local MCP servers you may have previously used, remote MCP servers are Internet-accessible. 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2025-04-06
3 min read
We’re kicking off Cloudflare’s 2025 Developer Week — our innovation week dedicated to announcements for developers.
It’s an exciting time to be a developer. In fact, as a developer, the past two years might have felt a bit like every week is Developer Week. Starting with the release of ChatGPT, it has felt like each day has brought a new, disruptive announcement, whether it’s new models, hardware, agents, or other tools. From late 2024 and in just the first few months of 2025, we’ve seen the DeepSeek model challenge assumptions about what it takes to train a new state-of-the-art model, MCP introduce a new standard for how LLMs interface with the world, and OpenAI’s o4 model Ghiblify the world.
And while it’s exciting to witness a technological revolution unfold in front of your eyes, it’s even more exciting to partake in it.
One of the marvels of the recent AI revolution is the extent to which the cost of experimentation has gone down. Ideas that would have taken whole weekends, weeks, or months to build can now be turned into working code in a day. You can vibe-code your way through things you might have never even tried before, or the parts of application that just don’t excite you. Whether you’ve spent your career working on frontend, backend, mobile, distributed systems or databases — with AI, you can truly be a full-stack engineer.
AI making it faster to ship more code and expanding the audience of who can write code (anyone!) — in the next 5 years we believe more code will be written than has been in the history of software.
However, for all these seedlings of opportunity to flourish, a platform needs to exist to make it just as easy to deploy and scale the code as it was to write it.
As Andrej Karpathy said in his recent post, on building a web application: “It’s not even code, it’s… configurations, plumbing, orchestration, workflows, best practices.”
The platform for the AI era
That’s Cloudflare’s vision for developers — to provide a comprehensive platform that just works. From experiment, to MVP, to scaling to millions of users.
We started on that vision almost 8 years ago now, with the launch of Cloudflare Workers, and kept chipping away at adding more and more primitives to allow developers to deploy their full-stack in one place.
Today, Cloudflare’s platform offers many of the building blocks you need: from compute, to storage, databases, and AI. With the tools you need to build along every step of the way: from local development to gradually rolling out to production, CI/CD, and observability.
And, everything you build is deployed to Region: Earth, which means you never have to think about servers, scaling, or infrastructure. This is especially important today — when the industry is moving at an unprecedented pace, the opportunity cost of slowing down is the difference between success and failure.
We’re incredibly proud of what we’ve built over the past 8 years, yet our work is nowhere near done. As our co-founder Michelle likes to say, we’re just getting started.
And this Developer Week we’re excited to take another step forward towards our mission. So what can you expect this Developer Week?
We’ll be releasing more tools and products to continue to ensure you have everything you need when building an application, whether it’s a web app, an agent, an MCP server, or anything else you dream up.
As I previously mentioned, though, primitives are just part of the equation. Building a developer platform also means investing in the developer experience. Many of you have been building on our platform for some time, and it’s an honor we don’t take lightly. We’re constantly listening to your feedback and improving the platform based on it. So this week, some of the announcements will be a direct reflection of that.
One of the best, most rewarding parts of getting to work on this platform over the past 8 years has been seeing all that developers built on it. We want to hear your thoughts, feedback and what you’re building, and hope you share it with us whether on X, Discord, or in person at one of our meetups in San Francisco, Austin, and London this week.
Visit 1.1.1.1 from any device to get started with our free app that makes your Internet faster and safer.
To learn more about our mission to help build a better Internet, start here. If you’re looking for a new career direction, check out our open positions.