
agentsync (remote)
io.github.jarmstrong158由 GitHub 帳號 jarmstrong158 發布v0.2.0更新於 Oct 24, 2026
Cloudflare Worker remote transport for agentsync. MCP 2026-07-28, dual-era, stateless.
概覽
一個 Cloudflare Worker 形式的 MCP 端點,讓手機端助理加入 agentsync 協作網路,在共享 claims 檔案中認領並追蹤工作。
- 可以做什麼
- 檢視協作看板:各對等端的認領、你的衝突與信箱留言,以及協作分支上的近期歷史,並可針對對等端重新檢查衝突(可限定單一分支)。認領工作並在與活躍對等端重疊時被阻擋,將認領在 planning、in-progress、done 之間推進,完成後釋放。張貼人工介入的信箱留言,從手機向桌面端對等端提問。所有寫入都以比較並交換方式作用於本機 agentsync 傳輸使用的同一份 claims 檔案。
- 適用情境
- 當你需要協調執行本機 agentsync 的筆記型電腦與手機上的 claude.ai 之間的平行工作,並希望兩端針對同一份共享 claims 檔案認領任務、而手機上無需 git 複製時使用。它是疊加在既有 agentsync 設定之上的第二種傳輸方式,並非獨立的工作追蹤器。
- 執行需求
- 需要在你自己的 Cloudflare 帳戶中自架此 Worker(透過專案的一鍵部署流程),並在 REPO 變數中指定 GitHub 協作儲存庫。需要兩個 Worker 密鑰:AUTH_TOKEN(鎖定端點)與 GH_PAT(對該儲存庫具有 Contents 讀寫權限的細粒度 GitHub 權杖)。連接器 URL 會將權杖嵌入路徑中。本機 agentsync 必須指向相同的儲存庫、分支與 claims 路徑。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 agentsync (remote),將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
agentsync-remote
Part of the xylem stack.
A Cloudflare Worker MCP server that makes claude.ai on your phone a peer in
the agentsync coordination mesh —
the same claims.json, the same agentsync branch, the same overlap and
compare-and-swap rules as local agentsync, with no git and no local clone.
Your laptop's Claude Code (local agentsync) and your phone's claude.ai
(agentsync-remote) claim work against the one shared claims.json. Two
transports, one mesh. A local peer and this remote peer are indistinguishable in
claims.json except by their agent id.
Sibling, not a fork. This is a second transport onto the same coordination file as local agentsync — not a variant of it. See
DESIGN.mdfor howgit push-as-CAS becomes GitHub-contents-API-as-CAS.
What it gives you
Seven tools over Streamable HTTP MCP:
Deploy your own (one click, no command line)
Self-host this Worker in your own Cloudflare account. Every step is a click path — you never touch a terminal.
1. Click Deploy to Cloudflare
Click the button above. Cloudflare will:
- fork
agentsync-remoteinto your GitHub account, - create the Worker in your Cloudflare account, and
- connect Workers Builds so future pushes to your fork redeploy automatically.
There are no databases or other resources to provision — this Worker keeps no state of its own (everything lives in your GitHub repo), so the deploy is just the Worker itself.
During the deploy dialog Cloudflare shows the Worker's variables. Set:
Finish the deploy. (If you skipped setting REPO here, you can set it later in
the dashboard — see below.)
2. Make a GitHub token, then add the two Worker secrets
The Worker reads two secrets. These are not part of the deploy dialog — you add them once in the dashboard after the first deploy.
First, make the GitHub token (this is the GH_PAT value):
GitHub → Settings → Developer settings → Fine-grained personal access tokens → Generate new token:
- Repository access: Only select repositories → pick only your
coordination repo (the one you put in
REPO). - Permissions → Repository permissions → Contents: Read and write.
- Nothing else. Generate it and copy the token.
Then add both secrets to the Worker:
Cloudflare dashboard → Workers & Pages → your Worker → Settings → Variables and Secrets → Add → type Secret → add each, then Deploy:
While you're on this screen, confirm the REPO variable points at your
coordination repo (set it here if you skipped it in the deploy dialog).
Until
AUTH_TOKENis set the Worker answers every request with404(it fails closed). UntilGH_PATis set the tools return a clear error naming the missing secret. This is by design — an unconfigured endpoint looks like it doesn't exist.
3. Add the connector in claude.ai
Find your Worker's URL: Workers & Pages → your Worker shows it, in the form
https://<your-worker-name>.<your-subdomain>.workers.dev.
claude.ai (web) → Settings → Connectors → Add custom connector. Paste your
Worker URL with /mcp/ and your AUTH_TOKEN appended:
The token in the path is the auth — there is no separate login.
4. Test it
Ask Claude: "call survey". You should get the coordination board back (empty
claims on a fresh mesh — the Worker bootstraps the branch and file for you, so
a brand-new empty repo needs no manual setup).
🔒 Security — the connector URL is a credential
The connector URL embeds your AUTH_TOKEN in the path
(…/mcp/<AUTH_TOKEN>). Anyone who has that URL can call your Worker and
read/write your coordination file. Treat the whole URL like a password:
- Don't paste it into screenshots, issues, chats, or commits.
- Anyone with the URL is a peer in your mesh — share it only with agents/people you trust.
- Rotating the token invalidates old URLs. To revoke access, change
AUTH_TOKENin Settings → Variables and Secrets and redeploy; every old…/mcp/<old-token>URL immediately returns404. Update the connector in claude.ai with the new URL.
GH_PAT is likewise a credential — scope it to only your coordination repo
with only Contents: Read and write, so a leak can't reach anything else.
Why the token is in the URL path, and what that costs you
This is a deliberate design choice, not an oversight. claude.ai custom
connectors do not reliably send custom headers, so an Authorization: header —
the obvious alternative — cannot be depended on. Putting the credential in the
path is what makes the connector work at all.
Be clear about the price, because it is not the same as a header:
- URLs get recorded in places request bodies never do. Browser history, shell history, proxy and CDN access logs, crash reports, bug reports, screenshots, "copy link" buttons, and agent session transcripts. During the audit that produced this section, the connector URLs for these Workers were found in ~54 occurrences across 13 local session transcripts on a single machine — none pasted deliberately; they were simply part of the tool configuration an agent echoed back.
- The Worker itself does not log it. Every log line records the route as
/mcp/***. The leak surface is everything around the Worker, which is exactly what you cannot audit. - A leaked token makes the holder a full peer in your mesh — able to claim, force-claim over you, release your claims, and post to the mailbox — with no second factor and no per-caller identity. There is nothing to revoke except the token, and no log that will tell you who used it.
Practical guidance:
- Rotate on a schedule, not just on suspicion — assume the URL has been
recorded somewhere you don't control. Rotation is cheap: change
AUTH_TOKEN, update the connector. - Rotate immediately if you've shared a terminal recording, a transcript, a screen capture, or a bug report from a machine where the connector is configured.
- Use a long random token (32+ bytes, e.g.
openssl rand -hex 32). The comparison is constant-time in both content and length, so length is not observable — but entropy is still your only defence against guessing. - If you ever get the chance to use a header or OAuth instead, take it. This tradeoff is forced by the client, not preferred.
Cross-transport walkthrough — two transports, one mesh
This is the whole point. The laptop and the phone coordinate through one file.
On the PC (local agentsync, Claude Code):
On the phone (claude.ai + agentsync-remote):
Back on the PC, the desktop agent (or you) reads the note via survey /
mailbox, answers it, and releases:
⚠️ Known gap: the mailbox is currently WRITE-ONLY across tiers
The "Back on the PC" step above does not work yet. This Worker's
mailbox()writes a top-levelnotes[]array intoclaims.json, and the local Python agentsync server has no concept ofnotes— it exposes nomailboxtool, and itssurvey()returns onlyme,branch,partnersandstale_claims. A note posted from the phone lands in the file correctly and is simply never surfaced to a desktop peer.That matters more than a missing feature normally would, because the repository-level agent instructions tell agents to raise judgment calls through this mailbox. An escape hatch that silently swallows the question is worse than no escape hatch: the agent believes it has asked and waits, or proceeds, on a question nobody will ever see.
Until the local side lands, read the mailbox from the remote peer (
mailboxwith nomessage, orsurvey), or readclaims.jsonon the coordination branch directly.The local-side change required (in the Python
agentsyncpackage — a separate repo, deliberately not modified here):
- Parse and preserve
notes. The claims-file reader must round-trip the top-levelnoteskey. Today an unrecognised key risks being dropped on the next local write, which would delete remote peers' notes. Preserving unknown top-level keys is the minimum safe change and should land first, independently.- Surface notes in
survey()— add anotesfield alongsidepartners/stale_claims, defaulting to[].- Add a local
mailbox(message=None, to=None)tool mirroring this one: append{from, to, message, at}under the same compare-and-swap the local claim writes already use, and cap retention at the 200 most recent notes (this Worker evicts oldest-first at that bound — the two sides must agree, or they will fight over the file).The on-disk shape is already compatible in both directions: this Worker only emits
noteswhen non-empty, so aclaims.jsonwith no mailbox activity stays byte-shape-identical to pure-local output.
On the phone again:
Every one of those steps was a compare-and-swap against the same
claims.json on the same branch. The laptop never saw a remote peer; the
phone never saw a git repo. Same mesh.
Configuration
Non-secret config lives in wrangler.toml. Every var ships a
default so the Deploy button works with no edits; change REPO to your own repo.
Two secrets are set in the dashboard, never in the repo: AUTH_TOKEN (locks
the endpoint) and GH_PAT (GitHub Contents read/write on the coordination repo).
Point local agentsync and this Worker at the same REPO + BRANCH +
CLAIMS_PATH and they share one mesh.
Reliability
Coordination correctness under contention is measured, not asserted — the full
write-up is docs/RELIABILITY.md, reproducible with the
commands below.
- 49 / 49 automated tests green, covering five distinct CAS race scenarios and all three overlap-detection modes (exact · directory-containment · glob, each in both directions).
- 1000 simulated concurrent races (
test/stress-cas.test.ts, seeded0x5eed): 0 lost claims, 0 double-grants, and every race hit a real 409 retry — so the number isn't inflated by trivially-serialized runs. - Fail-closed auth is tested — wrong token, unset
AUTH_TOKEN, and non-/mcppaths all 404; a missingGH_PATsurfaces a named error, not a silent failure. - The MCP handshake is hardened —
initializemakes no network call, so it answers instantly even on a cold isolate; it negotiates the client's requested protocol version rather than rejecting a slightly-ahead client; and an unexpected throw anywhere becomes a well-formed JSON-RPC error, never a bare500a reconnecting client would read as a hard failure. - Structured logs make failures visible — every request emits one line of
JSON (
request/auth/handshake/tool_call/error, with the path token always redacted), so a dropped handshake or a slow tool call is one filter away in Cloudflare Workers Logs ([observability]is on inwrangler.toml).
Honest caveat: the thousand races are simulated in-process — GitHub's 409
compare-and-swap is reproduced by a fetch-mocked fake (test/helpers.ts),
not exercised over the live API. The results validate the Worker's coordination
logic — which is what runs in production — not GitHub's API, the network, or
real-world latency.
Maintainer / local development
The canonical repo (jarmstrong158/agentsync-remote) deploys via GitHub Actions
→ Wrangler (.github/workflows/deploy.yml):
every push to main runs the suite and only deploys if it's green. That workflow
is guarded to the canonical repo, so a fork you created with the Deploy button
never tries to run it — your fork redeploys through Workers Builds instead.
Local checks (no Cloudflare credentials needed):
See also
- agentsync — the local transport (Claude Code on your machine). Same file, same rules; sibling transport.
DESIGN.md— the CAS translation, overlap semantics, and why the MCP handler is stateless and hand-rolled.docs/RELIABILITY.md— the measured reliability report: 49/49 tests, five CAS race scenarios, and 1000 seeded contention races.- Deploy to Cloudflare buttons — Cloudflare's docs for the one-click deploy flow used above.
Related
來源:README.md,提交 2066617
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0版本歷史
1- v0.2.0最新Sep 16, 2026
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