agami-deploy
EARLY ACCESS (in testing) — usable today, but newer than the local single-player path; feedback welcome via a GitHub issue. Prepares a ready-to-run, self-hosted agami deploy bundle ON THE USER'S MACHINE so a team can stand up a shareable MCP server their Claude connects to. Conve
Install
npx skills add https://github.com/AgamiAI/agami-core/tree/main/plugins/agami/skills/agami-deploy
claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install agamiai-agami-core@llmmart
git clone https://github.com/AgamiAI/agami-core.git
The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole agamiai/agami-core collection as a plugin from our marketplace. Git is the plain clone.
Skill manifest
agami deploy — prepare a self-host bundle the user ships to their own host
You are preparing a deploy bundle on the user's machine so they can stand up the multi-user agami
server (the HTTP MCP server with OAuth + admin) that their team's Claude connects to. The bundle pulls
the published image (ghcr.io/agamiai/agami-core) — there is no repo to clone and nothing to
build. You gather a few inputs, write the bundle locally, and hand off the cloud steps you can't do.
The local mirror of this (single-player, no network, no auth) is agami-serve — if the user only wants
agami in their own Claude Desktop, point them there instead.
HARD RULES (load-bearing — a deploy handles secrets)
- Never ask for the admin password (or any secret) in chat — not even temporarily. The password is
typed by the user directly into the
agami.envfile (Phase 2 hand-off), exactly likeagami-connectdoes for DB credentials. You never see it. - Never put a secret on a Bash command line.
prepare_deploy.pytakes only non-secret values;deploy_preflightgenerates the signing secret into the file. Hosts render Bash calls in chat. - Username/password is the only auth this skill sets up. Do not collect Google/Microsoft client
id/secret. Social login ships free but is a manual
agami.envstep — point the user at the in-repo deploy README if they ask, and move on. - No signup, no license key, no LLM/embedding key. None are required; don't ask for any.
Conversation style
Tight and oriented. Print one-line progress markers (✓ Bundle written to …, ✓ agami.env validated).
Be honest about what's the user's clicks (provision the VM, point DNS) vs what you automate.
Phase −1: Plan-mode preflight
Run the detection logic from shared/plan-mode-check.md. This skill
writes files and may run Docker. If plan mode is active, refuse with: "I can't prepare a deploy bundle
in plan mode — it writes the bundle + your agami.env and may run Docker. Switch to Auto or Edit
Automatically mode (Shift+Tab) and re-invoke me." DO NOT write a plan file or call ExitPlanMode.
Phase 0: Preflight
- Resolve the environment —
python3 "$AGAMI_PLUGIN_ROOT/scripts/connect_resolve.py"prints JSON; readdata.artifacts_dir(the local model dir) anddata.interpreter.python3(call it$PY— the interpreter that has the agami-core package; use it fordeploy_preflight). - Model present —
<artifacts_dir>/<active_profile>/datasource.yamlmust exist. If there's no model yet, stop and invoke/agami-connectfirst — the deployed server has nothing to serve without one.
Phase 1: Gather the hard floor, then write the bundle
Ask only these (everything else is defaulted or generated). Prefer one compact exchange:
- Hostname — "What address will your team connect to?" It must be a hostname, not a bare IP
(TLS + OAuth need a DNS name). →
PUBLIC_BASE_URL=https://<host>.- If they have no domain / can't open ports, offer the Cloudflare tunnel path (profiles
bundled-db,tunnel; they'll addCLOUDFLARE_TUNNEL_TOKENtoagami.env). The tunnel still needs a domain on Cloudflare — it removes the public IP, not the name.
- If they have no domain / can't open ports, offer the Cloudflare tunnel path (profiles
- Admin — first name, last name, work email (the email is the admin identity).
- (only if they bring their own Postgres) note it → use profiles
edge(drops the bundled DB). The managedpostgresql://…URL is a credential, so do not collect it in chat — after the bundle is written, the user setsAPP_DATABASE_URLinagami.envthemselves (the same hand-off as the password). - Which datasource(s)? — list the models in the artifacts dir (one per profile:
<artifacts_dir>/<profile>/datasource.yaml). If there's exactly one, use it silently. If there's more than one, ask: "You have N datasources —<names>. Deploy all, or pick?" Pass the chosen set as--datasources a,b(omit to deploy all). The server serves every datasource you stage, and each needs its own DSN (Phase 2).
Confirm where to write the bundle. Ask: "Where should I put the deploy bundle? (default ~/agami-deploy)"
and use their answer as --target. It must not be inside the artifacts dir (prepare_deploy rejects that —
it copies the model out of artifacts into the bundle). Then write it:
python3 "$AGAMI_PLUGIN_ROOT/scripts/prepare_deploy.py" \
--target <chosen-dir, default ~/agami-deploy> \
--artifacts-dir "<data.artifacts_dir>" \
--public-base-url "https://<host>" \
--admin-email "<email>" --admin-first "<first>" --admin-last "<last>" \
--profiles "bundled-db,edge"
Append these flags to the command when they apply (add each as another \-continued line): --datasources "a,b" to stage a subset of models; on a version upgrade --image-tag "<version>" to bump it (omit it on a
model-only re-stage so an existing pin isn't changed).
(Use --profiles "bundled-db,tunnel" for the tunnel, or --profiles "edge" for managed Postgres — then
have the user set APP_DATABASE_URL in agami.env by hand, never on the command line.)
Read the status line and branch on the first token:
PREPARED <dir>— a fresh bundle. Go to Phase 2 (fill the secrets).UPGRADED <dir> new_keys=<a,b,…>— an existing bundle upgraded in place: every value the user typed (password, secret, DSN) is kept. Ifnew_keysis non-empty, this version added settings — tell the user exactly which to set (e.g. "this version addedDATASOURCE_URL— set it inagami.envbefore we restart"). If it's empty, nothing new is needed. Existing secrets are already there — don't re-ask; continue to Phase 3 (deploy).
Phase 2: Hand off the secrets (then end the turn)
Open the file for them so they don't have to hunt for it (it's a plain visible file, agami.env, in the
bundle dir): open -t -- "<target>/agami.env" on macOS (opens it in the default text editor; the -- stops a
path that starts with - being read as a flag); on other platforms
just print the absolute path. Then tell the user (do not proceed past this in the same turn). These are
credentials — the user types them by hand; you never see them, they stay in the file on their machine:
Open
<target>/agami.env(I just opened it for you) and set, then save:
AGAMI_ADMIN_PASSWORD=— a strong admin password.- the warehouse DSN(s) — the connection string(s) the model queries (the scheme picks the type:
postgresql://mysql://redshift://snowflake://…). (These live here now — not shipped in the bundle.) Name them per the datasource(s) you deployed:
- one datasource →
DATASOURCE_URL=(e.g.postgresql://<user>:<password>@host:5432/db).- several → one per datasource:
DATASOURCE_URL__<TOKEN>=, where<TOKEN>is the datasource id upper-cased with every non-alphanumeric char turned to_(sosales-pg→DATASOURCE_URL__SALES_PG). (List the exact var names for the datasources they chose in Phase 1.4.) agami only runs read-only SELECTs, so the warehouse user only needs read access — a read-only user is safest. Ask for "the read-only grant" and I'll hand you the SQL (shared/readonly-grants.md).- (only if you chose managed Postgres)
APP_DATABASE_URL=— your Postgres URL.Then tell me to continue.
End the turn here. The user fills the secrets and re-invokes (or says "continue").
Phase 3: Finalize + deploy
- Validate + generate the signing secret:
$PY -m deploy_preflight ~/agami-deploy/agami.env. If it reports missing inputs (e.g. the password still blank, or a non-https URL), relay them and stop. On success it has writtenAGAMI_SIGNING_SECRET+ derivedAGAMI_PUBLIC_HOSTinto the file. - Bring it up:
- Docker present here (the user is on the target host, or testing locally) — run
cd ~/agami-deploy && ./deploy.sh(pulls the image +docker compose up -d). - No Docker / deploying to a remote VM — hand off: have them copy
~/agami-deployto the host (scp -ror a synced folder), then run./deploy.shthere. Give them the cloud checklist below.
- Docker present here (the user is on the target host, or testing locally) — run
- Print the share lines: the connector URL
<PUBLIC_BASE_URL>/mcp(what teammates add in claude.ai → Connectors), and the admin console<PUBLIC_BASE_URL>/admin.
The cloud steps you can't do (👤 — walk them through it)
- A VM (~2 vCPU / 4 GB RAM / 20 GB disk), Ubuntu LTS, only ports 80 + 443 open (or the tunnel).
- DNS: an A-record for their hostname → the VM's public IP. (Skip for the tunnel.)
- Docker on the host:
curl -fsSL https://get.docker.com | sudo sh. - Then
./deploy.shon the host → wait ~30s for Caddy to issue the cert → open<PUBLIC_BASE_URL>/admin.
Re-running later (model update vs version upgrade)
A re-run of /agami-deploy over an existing bundle is non-destructive — it never touches the secrets the
user typed (UPGRADED status); it re-stages the model, appends any settings new in this version, and reports
them as new_keys. Two cases:
- Model update (they changed the semantic model): re-run without
--image-tag(keeps the pinned version), then on the hostdocker compose restart agami— the server re-ingests the model on boot. No rebuild, no DB access. - Version upgrade (a newer agami release): re-run with
--image-tag "<version>"(bumps it), set anynew_keysthe run reports, thencd <target> && ./deploy.sh(pulls the new image + recreates).
Notes
- This is the team path. For a quick local feel of the same tools, that's
agami-serve(stdio, no network). For a fully managed, governed, always-on server, that's the hosted product — seedocs/open-vs-hosted.md. - The bundle is self-contained and re-shippable: the generated signing secret lives in its
agami.env, so a VM rebuild that re-uses the same bundle keeps every connected Claude working (no reconnect).
Files (agami-core)
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bundle
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agami.env.example 3.8 KB · in bundle
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Caddyfile 363 B · in bundle
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deploy.sh 653 B
#!/bin/sh # Bring up the agami stack from this prepared bundle. `/agami-deploy` already validated + filled your # agami.env locally (signing secret generated, host derived), so this just pulls the published image and runs. # `--env-file agami.env` on every call: compose doesn't auto-load it (visible name, not the hidden `.env`). set -e cd "$(dirname "$0")" docker compose --env-file agami.env pull docker compose --env-file agami.env up -d echo "agami is starting. It's live at your PUBLIC_BASE_URL once Caddy issues the certificate (a few seconds)." echo "Share \${PUBLIC_BASE_URL}/mcp with your team; manage users at \${PUBLIC_BASE_URL}/admin" -
docker-compose.yml 3.2 KB
# agami self-host stack. `./deploy.sh` (compose with `--env-file agami.env`, COMPOSE_PROFILES=bundled-db,edge) # brings up the secure VM deployment: Caddy terminates TLS and is the ONLY public service; agami and # Postgres live on the internal network with no published ports. Toggle the profiles for the variants: # bundled-db,edge (default) — Caddy TLS + agami + bundled Postgres on a VM # edge + APP_DATABASE_URL — external/managed Postgres (e.g. Cloud SQL via a plain URL) # tunnel — Cloudflare Tunnel instead of a public IP (no inbound ports) # (none) — agami only, behind the platform's own TLS (e.g. Cloud Run); set APP_DATABASE_URL # # Unlike the in-repo deploy/ stack, this bundle PULLS a pre-built image (no build context, no clone). name: agami # Cap per-container log growth (default json-file is unbounded) so a long-running deploy can't fill the # disk — 3 rotated files × 10 MB per service. Applied to every service via the `*default-logging` anchor. x-logging: &default-logging driver: json-file options: max-size: "10m" max-file: "3" services: caddy: image: caddy:2 profiles: ["edge"] restart: unless-stopped logging: *default-logging ports: - "80:80" - "443:443" environment: AGAMI_PUBLIC_HOST: ${AGAMI_PUBLIC_HOST} # the bare hostname; deploy_preflight derives it from PUBLIC_BASE_URL volumes: - ./Caddyfile:/etc/caddy/Caddyfile:ro - caddy_data:/data - caddy_config:/config agami: image: ghcr.io/agamiai/agami-core:${AGAMI_IMAGE_TAG:-latest} restart: unless-stopped logging: *default-logging env_file: agami.env environment: # Bundled Postgres by default; set APP_DATABASE_URL in agami.env to point at managed Postgres instead. AGAMI_DB_URL: ${APP_DATABASE_URL:-postgresql://agami:${POSTGRES_PASSWORD:-agami-bundled-local}@postgres:5432/agami} AGAMI_ARTIFACTS_DIR: /artifacts HOST: 0.0.0.0 PORT: "8000" volumes: - ${AGAMI_ARTIFACTS_DIR:-./artifacts}:/artifacts:ro # your local agami-artifacts (the model), read-only # No `ports:` and no `depends_on:` — agami is reached only via Caddy/the tunnel on the internal # network, and the entrypoint waits for the DB itself (so the external-DB/cloud-run profiles work). postgres: image: postgres:16 profiles: ["bundled-db"] restart: unless-stopped logging: *default-logging environment: POSTGRES_DB: agami POSTGRES_USER: agami # A bundled-local default — fine because the DB is never exposed; override it in agami.env if you like. POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-agami-bundled-local} volumes: - pgdata:/var/lib/postgresql/data healthcheck: test: ["CMD-SHELL", "pg_isready -U agami -d agami"] interval: 2s timeout: 3s retries: 30 # No `ports:` — the database is never published to the host or the internet. cloudflared: image: cloudflare/cloudflared:latest profiles: ["tunnel"] restart: unless-stopped logging: *default-logging command: tunnel --no-autoupdate run environment: TUNNEL_TOKEN: ${CLOUDFLARE_TUNNEL_TOKEN:-} # from your Cloudflare Zero Trust tunnel volumes: pgdata: caddy_data: caddy_config: -
README.md 1.2 KB
# Your agami deploy bundle `/agami-deploy` prepared this folder. It's self-contained — it **pulls** the published image (`ghcr.io/agamiai/agami-core`), so there's nothing to build and no repo to clone. ## What's here - `docker-compose.yml` — Caddy (auto-TLS, the only public service) + agami + bundled Postgres. - `Caddyfile` — TLS for your hostname. - `agami.env` — your config (filled by `/agami-deploy`; `deploy_preflight` generated the signing secret). - `artifacts/` — your semantic model + warehouse credentials (mounted read-only). - `deploy.sh` — pulls the image and brings the stack up. ## Run it On a host with Docker + your hostname's DNS A-record pointed at it (or a Cloudflare tunnel): ```sh ./deploy.sh ``` Then open `<PUBLIC_BASE_URL>/admin` to sign in, and share `<PUBLIC_BASE_URL>/mcp` with your team. ## Recommended VM size 2 vCPU / 4 GB RAM / 20 GB disk runs the server + bundled Postgres comfortably for a small team. Open only ports 80 and 443 (or use the `tunnel` profile to expose nothing inbound). ## Updating the model later Refresh your model locally, re-run `/agami-deploy` (or re-copy `artifacts/`), then on the host: `docker compose restart agami` — the server re-ingests the model on boot. No rebuild, no DB access.
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SKILL.md 11.4 KB
--- name: agami-deploy description: "EARLY ACCESS (in testing) — usable today, but newer than the local single-player path; feedback welcome via a GitHub issue. Prepares a ready-to-run, self-hosted agami deploy bundle ON THE USER'S MACHINE so a team can stand up a shareable MCP server their Claude connects to. Conversationally gathers the hard-floor inputs (hostname, admin identity), auto-detects the local model, writes docker-compose.yml + Caddyfile + a filled agami.env (referencing the PUBLISHED image ghcr.io/agamiai/agami-core — no clone, no build), and stages the model artifacts. Generates the signing secret via deploy_preflight; the admin password is typed by the user into the file (never in chat). Then runs `docker compose up` if Docker is local, otherwise prints the exact VM steps + the shareable MCP URL. Username/password auth only on this paved path." when_to_use: "Use when the user says 'deploy agami', 'self-host agami', 'set up the agami server for my team', 'stand up a shared agami', 'host agami on a VM / in the cloud', '/agami-deploy', or otherwise wants the multi-user HTTP server (not the local single-player setup — that's agami-serve). Requires agami-connect to have run first (needs a semantic model + credentials). This is the TEAM path: it produces an internet-reachable server with OAuth + admin that claude.ai connects to." --- # agami deploy — prepare a self-host bundle the user ships to their own host You are preparing a **deploy bundle** on the user's machine so they can stand up the multi-user agami server (the HTTP MCP server with OAuth + admin) that their team's Claude connects to. The bundle pulls the **published image** (`ghcr.io/agamiai/agami-core`) — there is **no repo to clone and nothing to build**. You gather a few inputs, write the bundle locally, and hand off the cloud steps you can't do. The local mirror of this (single-player, no network, no auth) is `agami-serve` — if the user only wants agami in their own Claude Desktop, point them there instead. ## HARD RULES (load-bearing — a deploy handles secrets) 1. **Never ask for the admin password (or any secret) in chat — not even temporarily.** The password is typed by the **user** directly into the `agami.env` file (Phase 2 hand-off), exactly like `agami-connect` does for DB credentials. You never see it. 2. **Never put a secret on a Bash command line.** `prepare_deploy.py` takes only non-secret values; `deploy_preflight` generates the signing secret *into the file*. Hosts render Bash calls in chat. 3. **Username/password is the only auth this skill sets up.** Do **not** collect Google/Microsoft client id/secret. Social login ships free but is a manual `agami.env` step — point the user at the in-repo deploy README if they ask, and move on. 4. **No signup, no license key, no LLM/embedding key.** None are required; don't ask for any. ## Conversation style Tight and oriented. Print one-line progress markers (`✓ Bundle written to …`, `✓ agami.env validated`). Be honest about what's the user's clicks (provision the VM, point DNS) vs what you automate. ## Phase −1: Plan-mode preflight Run the detection logic from [`shared/plan-mode-check.md`](../../shared/plan-mode-check.md). This skill writes files and may run Docker. If plan mode is active, refuse with: *"I can't prepare a deploy bundle in plan mode — it writes the bundle + your agami.env and may run Docker. Switch to **Auto** or **Edit Automatically** mode (Shift+Tab) and re-invoke me."* **DO NOT** write a plan file or call `ExitPlanMode`. ## Phase 0: Preflight 1. **Resolve the environment** — `python3 "$AGAMI_PLUGIN_ROOT/scripts/connect_resolve.py"` prints JSON; read `data.artifacts_dir` (the local model dir) and `data.interpreter.python3` (call it `$PY` — the interpreter that has the agami-core package; use it for `deploy_preflight`). 2. **Model present** — `<artifacts_dir>/<active_profile>/datasource.yaml` must exist. If there's no model yet, stop and invoke `/agami-connect` first — the deployed server has nothing to serve without one. ## Phase 1: Gather the hard floor, then write the bundle Ask only these (everything else is defaulted or generated). Prefer one compact exchange: 1. **Hostname** — "What address will your team connect to?" It must be a **hostname, not a bare IP** (TLS + OAuth need a DNS name). → `PUBLIC_BASE_URL=https://<host>`. - If they have **no domain / can't open ports**, offer the **Cloudflare tunnel** path (profiles `bundled-db,tunnel`; they'll add `CLOUDFLARE_TUNNEL_TOKEN` to `agami.env`). The tunnel still needs a domain on Cloudflare — it removes the public IP, not the name. 2. **Admin** — first name, last name, work **email** (the email is the admin identity). 3. *(only if they bring their own Postgres)* note it → use profiles `edge` (drops the bundled DB). The managed `postgresql://…` URL is a **credential**, so do **not** collect it in chat — after the bundle is written, the user sets `APP_DATABASE_URL` in `agami.env` themselves (the same hand-off as the password). 4. **Which datasource(s)?** — list the models in the artifacts dir (one per profile: `<artifacts_dir>/<profile>/datasource.yaml`). If there's exactly one, use it silently. If there's **more than one**, ask: *"You have N datasources — `<names>`. Deploy all, or pick?"* Pass the chosen set as `--datasources a,b` (omit to deploy all). The server serves **every** datasource you stage, and each needs its own DSN (Phase 2). **Confirm where to write the bundle.** Ask: *"Where should I put the deploy bundle? (default `~/agami-deploy`)"* and use their answer as `--target`. It must **not** be inside the artifacts dir (prepare_deploy rejects that — it copies the model *out of* artifacts *into* the bundle). Then write it: ```bash python3 "$AGAMI_PLUGIN_ROOT/scripts/prepare_deploy.py" \ --target <chosen-dir, default ~/agami-deploy> \ --artifacts-dir "<data.artifacts_dir>" \ --public-base-url "https://<host>" \ --admin-email "<email>" --admin-first "<first>" --admin-last "<last>" \ --profiles "bundled-db,edge" ``` **Append these flags to the command when they apply** (add each as another `\`-continued line): `--datasources "a,b"` to stage a subset of models; on a **version upgrade** `--image-tag "<version>"` to bump it (omit it on a model-only re-stage so an existing pin isn't changed). (Use `--profiles "bundled-db,tunnel"` for the tunnel, or `--profiles "edge"` for managed Postgres — then have the user set `APP_DATABASE_URL` in `agami.env` by hand, never on the command line.) **Read the status line** and branch on the first token: - `PREPARED <dir>` — a **fresh** bundle. Go to Phase 2 (fill the secrets). - `UPGRADED <dir> new_keys=<a,b,…>` — an **existing** bundle upgraded **in place**: every value the user typed (password, secret, DSN) is kept. If `new_keys` is **non-empty**, this version added settings — tell the user exactly which to set (e.g. *"this version added `DATASOURCE_URL` — set it in `agami.env` before we restart"*). If it's **empty**, nothing new is needed. Existing secrets are already there — don't re-ask; continue to Phase 3 (deploy). ## Phase 2: Hand off the secrets (then end the turn) **Open the file for them** so they don't have to hunt for it (it's a plain visible file, `agami.env`, in the bundle dir): `open -t -- "<target>/agami.env"` on macOS (opens it in the default text editor; the `--` stops a path that starts with `-` being read as a flag); on other platforms just print the **absolute path**. Then tell the user (do **not** proceed past this in the same turn). These are credentials — the user types them by hand; you never see them, they stay in the file on their machine: > Open `<target>/agami.env` (I just opened it for you) and set, then save: > - **`AGAMI_ADMIN_PASSWORD=`** — a strong admin password. > - the **warehouse DSN(s)** — the connection string(s) the model queries (the scheme picks the type: > `postgresql://` `mysql://` `redshift://` `snowflake://…`). *(These live here now — **not** shipped in > the bundle.)* Name them per the datasource(s) you deployed: > - **one datasource** → **`DATASOURCE_URL=`** (e.g. `postgresql://<user>:<password>@host:5432/db`). > - **several** → one per datasource: **`DATASOURCE_URL__<TOKEN>=`**, where `<TOKEN>` is the datasource id > upper-cased with every non-alphanumeric char turned to `_` (so `sales-pg` → `DATASOURCE_URL__SALES_PG`). > *(List the exact var names for the datasources they chose in Phase 1.4.)* > agami only runs read-only SELECTs, so the warehouse user only needs read access — a read-only user is > safest. Ask for "the read-only grant" and I'll hand you the SQL ([`shared/readonly-grants.md`](../../shared/readonly-grants.md)). > - *(only if you chose managed Postgres)* **`APP_DATABASE_URL=`** — your Postgres URL. > > Then tell me to continue. End the turn here. The user fills the secrets and re-invokes (or says "continue"). ## Phase 3: Finalize + deploy 1. **Validate + generate the signing secret:** `$PY -m deploy_preflight ~/agami-deploy/agami.env`. If it reports missing inputs (e.g. the password still blank, or a non-https URL), relay them and stop. On success it has written `AGAMI_SIGNING_SECRET` + derived `AGAMI_PUBLIC_HOST` into the file. 2. **Bring it up:** - **Docker present here** (the user is on the target host, or testing locally) — run `cd ~/agami-deploy && ./deploy.sh` (pulls the image + `docker compose up -d`). - **No Docker / deploying to a remote VM** — hand off: have them copy `~/agami-deploy` to the host (`scp -r` or a synced folder), then run `./deploy.sh` there. Give them the **cloud checklist** below. 3. **Print the share lines:** the connector URL **`<PUBLIC_BASE_URL>/mcp`** (what teammates add in claude.ai → Connectors), and the admin console **`<PUBLIC_BASE_URL>/admin`**. ## The cloud steps you can't do (👤 — walk them through it) - **A VM** (~2 vCPU / 4 GB RAM / 20 GB disk), Ubuntu LTS, **only ports 80 + 443 open** (or the tunnel). - **DNS:** an **A-record** for their hostname → the VM's public IP. (Skip for the tunnel.) - **Docker** on the host: `curl -fsSL https://get.docker.com | sudo sh`. - Then `./deploy.sh` on the host → wait ~30s for Caddy to issue the cert → open `<PUBLIC_BASE_URL>/admin`. ## Re-running later (model update vs version upgrade) A re-run of `/agami-deploy` over an existing bundle is **non-destructive** — it never touches the secrets the user typed (`UPGRADED` status); it re-stages the model, appends any settings new in this version, and reports them as `new_keys`. Two cases: - **Model update** (they changed the semantic model): re-run **without** `--image-tag` (keeps the pinned version), then on the host `docker compose restart agami` — the server re-ingests the model on boot. No rebuild, no DB access. - **Version upgrade** (a newer agami release): re-run **with** `--image-tag "<version>"` (bumps it), set any `new_keys` the run reports, then `cd <target> && ./deploy.sh` (pulls the new image + recreates). ## Notes - This is the **team** path. For a quick local feel of the same tools, that's `agami-serve` (stdio, no network). For a fully managed, governed, always-on server, that's the hosted product — see `docs/open-vs-hosted.md`. - The bundle is self-contained and re-shippable: the generated signing secret lives in its `agami.env`, so a VM rebuild that re-uses the same bundle keeps every connected Claude working (no reconnect).
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