kasl-server
Team server for kasl. Employees run kasl on their machines; the agents send work-time data to the server. Managers get dashboards, charts, and reports across the whole team; every employee gets a personal page.
Status: pre-alpha. The door for kasl agents is open and survives a bad connection: a day at a time on
POST /api/v1/days, a backlog on/days/batch, and a task the employee deleted can be deleted here too. History from before the server arrived can be imported from an agent's own database; people sign in, and an administrator manages the team and its agent tokens without touching the host. The tables are filled; almost nothing reads them back yet — dashboards and the personal page are the next milestones, and there is still nothing to deploy for real use.
Try it
Requires Rust and Docker.
$ git clone https://github.com/lacodda/kasl-server && cd kasl-server
$ docker compose up -d db
$ export DATABASE_URL=postgres://kasl:kasl@localhost:5433/kasl
$ export KASL_AGENTS=employee@example.com:agent-token
$ cargo run
2026-08-20T23:14:30.598244Z INFO kasl_server: database schema is up to date version=20260818000001
2026-08-20T23:14:30.653426Z INFO kasl_server::provision: provisioned agents from KASL_AGENTS agents=1
2026-08-20T23:14:30.656763Z INFO kasl_server: kasl-server listening version="0.7.0" addr=0.0.0.0:8080 max_batch_days=31 max_body_bytes=4194304
$ curl http://127.0.0.1:8080/health
{"database":"ok","status":"ok","version":"0.7.0"}
# An agent back from three days offline. The middle day is impossible - it ends
# before it starts - and the others land anyway.
$ curl -X POST http://127.0.0.1:8080/api/v1/days/batch \
-H "Authorization: Bearer agent-token" -H "Content-Type: application/json" \
-d '{"days":[
{"date":"2026-08-15","started_at":"2026-08-15T09:04:00-03:00","ended_at":"2026-08-15T18:12:00-03:00",
"tasks":[{"agent_task_id":7,"recorded_at":"2026-08-15T18:10:00-03:00","name":"Reliable ingest","completeness":60}]},
{"date":"2026-08-16","started_at":"2026-08-16T19:00:00-03:00","ended_at":"2026-08-16T09:00:00-03:00"},
{"date":"2026-08-17","started_at":"2026-08-17T09:11:00-03:00","ended_at":"2026-08-17T17:40:00-03:00",
"tasks":[{"agent_task_id":7,"recorded_at":"2026-08-17T17:38:00-03:00","name":"Reliable ingest","completeness":100}],
"tasks_are_complete":true}]}'
{"accepted":2,"rejected":1,"results":[
{"status":"accepted","workday_id":"82ca500d-feeb-4d1f-8fb7-0b376339be02","date":"2026-08-15","pauses":0,"tasks":1,"deleted_tasks":0},
{"status":"rejected","date":"2026-08-16","error":"ended_at is before started_at"},
{"status":"accepted","workday_id":"2ea46d40-3aa0-48d3-8d8d-e1bb152a36bc","date":"2026-08-17","pauses":0,"tasks":1,"deleted_tasks":0}]}
# The employee deletes the task in kasl; the agent re-sends the day and says so.
$ curl -X POST http://127.0.0.1:8080/api/v1/days \
-H "Authorization: Bearer agent-token" -H "Content-Type: application/json" \
-d '{"date":"2026-08-17","started_at":"2026-08-17T09:11:00-03:00","ended_at":"2026-08-17T17:40:00-03:00",
"tasks":[],"tasks_are_complete":true}'
{"workday_id":"2ea46d40-3aa0-48d3-8d8d-e1bb152a36bc","date":"2026-08-17","pauses":0,"tasks":0,"deleted_tasks":1}
The task is gone from the 17th - and still there on the 15th, where the employee did not delete it.
The dev database listens on 5433, leaving a PostgreSQL you may already run on
5432 alone; override with KASL_DB_PORT.
The API
/api/v1 from the first endpoint: agents update on their own schedule, so a
path keeps meaning what it meant when the agent calling it shipped.
POST /api/v1/days — upload one day. Requires Authorization: Bearer
<token>. The body is the workday with its pauses and tasks; ended_at is
absent while the day is still running, and so is a pause's, and tasks may be
empty.
Two properties are worth knowing before writing a client:
- Every instant needs a UTC offset, and the day carries its own
date.2026-08-14T09:12:00without an offset is refused (422): one team's hours have to stay comparable across time zones, and which calendar day work belongs to is the agent's call, not a value derived on the server. - The last upload wins. Re-sending a day replaces what is stored, so a
correction made in kasl lands and a retry after a lost connection is safe -
the same payload twice leaves the same rows. Pauses are replaced as a set;
tasks are matched on
agent_task_id, so a task carried into the next day moves rather than multiplying. - Deleting a task takes one word. Send
"tasks_are_complete": trueand the date's tasks the payload omits are deleted, which is how a task the employee removed in kasl disappears here too. Other dates are untouched. Leave the flag out - as agents written before it did - and nothing is ever deleted.
POST /api/v1/days/batch — upload a backlog. The body is {"days": [...]}
with the same day objects, and the answer reports each one:
Each day is written on its own, so one the server will never accept does not
block the rest - an agent that could not deliver any of its backlog because of
a single bad row would retry the same request forever. The batch carries at most
KASL_MAX_BATCH_DAYS days (31) and the body at most KASL_MAX_BODY_BYTES
(4 MiB); past either, 413.
Which failures are worth retrying. 4xx means the payload will not be
accepted as sent, however many times it is tried - fix it or drop it. 5xx
means the fault is on this side; send it again later. A batch that answers 5xx
stopped partway: the days already accepted are stored, and re-sending them is
safe because the last upload wins.
A malformed day is refused with 400 and a reason naming the field
({"error":"tasks[0]: completeness must be between 0 and 100"}); an
unrecognized, revoked or deactivated token gets 401. The reasoning behind all
of this is in ADR 0004
and ADR 0005.
Signing in
People sign in with an email and a password; kasl agents keep using their bearer token and are unaffected by any of this.
$ kasl-server admin --email boss@example.com --password '...'
admin boss@example.com is ready
$ curl -i -X POST http://127.0.0.1:8080/api/v1/auth/login -H "Content-Type: application/json" -d '{"email":"boss@example.com","password":"..."}'
HTTP/1.1 200 OK
set-cookie: kasl_session=b7857303342e1a4b...; Path=/; HttpOnly; SameSite=Strict; Max-Age=1209600
{"status":"ok"}
$ curl -H "Cookie: kasl_session=b7857303342e1a4b..." http://127.0.0.1:8080/api/v1/auth/me
{"id":"de836432-5dce-4705-9344-a65b356fc662","email":"boss@example.com","display_name":"boss@example.com","role":"admin"}
POST /auth/logout ends this session, POST /auth/logout-everywhere ends all of
them, and GET /auth/me says who the caller is.
Sessions are rows in the database, not signed tokens. The query per request buys the thing a self-contained token cannot give: access ends when it is ended — the afternoon someone leaves, not whenever their token happens to expire. A session lasts a fortnight and each use pushes that out again.
An unknown email, a deactivated account and a wrong password all answer
{"error":"wrong email or password"}, so the login form cannot be used to find
out who works somewhere.
The first administrator comes from kasl-server admin or
KASL_ADMIN=email:password in the environment. Running it again resets the
password and promotes the account, which is both the way back in after a
forgotten password and the way to make an admin of someone whose account already
exists because their agent has been reporting. Accounts created by KASL_AGENTS
have no password and cannot be signed into — they exist to own an agent's data.
Set KASL_SECURE_COOKIES=false when serving over plain http://. A Secure
cookie is silently dropped by the browser there, which looks exactly like login
doing nothing. The reasoning is in
ADR 0007.
Managing the team
Once an administrator exists, people and agent tokens are managed over the API rather than through the host's environment.
$ curl -X POST http://127.0.0.1:8080/api/v1/users -H "Cookie: kasl_session=..." -H "Content-Type: application/json" -d '{"email":"ivan@example.com","display_name":"Ivan","password":"..."}'
{"id":"9b5c1fd8-cf3d-433e-bb9e-0c2bf1c1cfac"}
$ curl -X POST http://127.0.0.1:8080/api/v1/users/9b5c1fd8-.../agents -H "Cookie: kasl_session=..." -H "Content-Type: application/json" -d '{"name":"ivan-laptop"}'
{"id":"b749b090-db08-464d-b48d-4fe15f7acc43","name":"ivan-laptop",
"token":"kasl_<64 hex chars>",
"notice":"this token is shown once; the server keeps only its hash"}
$ curl -X DELETE http://127.0.0.1:8080/api/v1/agents/b749b090-... -H "Cookie: kasl_session=..."
# 204; the same token now gets 401 from the ingest routes
| Route | Who |
|---|---|
GET /users, GET /users/{id}/agents |
admin, manager |
POST /users, PATCH /users/{id} |
admin |
POST /users/{id}/agents, DELETE /agents/{id} |
admin |
POST /auth/password |
anyone signed in, for their own password |
A manager reads the team and changes nothing. Departments arrive in the next milestone; until a manager has a group to be in charge of, any authority granted is authority over the whole company — and issuing an agent token is the authority to write someone's history.
An administrator sets an initial password and hands it over; the person
changes it with POST /auth/password, which requires the current one. The
server has no mail channel, so there is nothing to send an invite link to that
would not be handed over the same way a password is.
Some things follow from a change rather than being asked for separately:
- Deactivating someone, or resetting their password, deletes their sessions.
- Changing your own password ends every other session and keeps the one you are using.
- The last administrator cannot be demoted or deactivated — the only way back
from that is the
adminsubcommand on the host. - A user is never deleted, only deactivated: their days have to keep an owner.
Agent tokens are shown once and stored as a SHA-256. The reasoning is in ADR 0008.
Importing history from before the server
Someone can track their time with kasl for a year before their team runs a server. That history is an ordinary SQLite file on their machine, and it does not have to be lost because the server arrived second:
$ kasl-server import --db kasl.db --user employee@example.com --timezone -03:00
read 240 workdays, 312 pauses, 460 tasks from kasl.db
skipped 17 tasks the employee had deleted
imported 240 days as employee@example.com at -03:00
--timezone is required and has no default. kasl stores bare wall-clock text,
so nothing in the file says which offset it was recorded in - and a wrong guess
produces a perfectly plausible-looking year of work at the wrong hour. The
answer comes from whoever knows, and is echoed back so it is on the record.
--dry-runreads and reports without writing anything.--since/--untilbound the import by date, both ends inclusive. This is how someone who moved between time zones is imported correctly: one run per stretch, each with the offset that stretch was recorded in.- The account must already exist - an import will not create it, so a typo in the email address cannot quietly file a year of history under a stranger.
- Re-importing replaces rather than duplicates, so a run that failed partway can simply be repeated, and a wrong offset is fixed by importing again with the right one.
The agent's file is opened read-only and never written to. Details and the trade-offs behind the fixed offset are in ADR 0006.
The data model
Migrations live in migrations/ and are applied on startup. The shape follows
kasl's own model, so a reader who knows the agent recognizes it:
| Table | Holds |
|---|---|
users |
People and their role: admin, manager, employee |
sessions |
Browser sign-ins; a token hash each, never the token |
agents |
Installed kasl instances; a token hash each, never the token |
workdays |
One row per person per date: when the day started and ended |
pauses |
Idle stretches and manual breaks inside a day |
tasks, tags, task_tags |
What was worked on, and how it is labelled |
reports |
That a report was submitted, when, and with which figures |
Two differences from the agent's database are deliberate: instants are stored with a time zone (the agent stores bare wall-clock text, which does not survive a team spread across zones), and rows are tied together by foreign keys rather than by comparing dates. Both are recorded in ADR 0003.
Running it somewhere real
docker-compose.prod.yml builds the server and starts it next to PostgreSQL.
The image is built on the machine that will run it, so a stand on a Raspberry
Pi gets an aarch64 binary without cross-compiling anything:
$ cat > .env <<'ENV'
POSTGRES_PASSWORD=<a long random string>
KASL_AGENTS=employee@example.com:<the agent's token>
ENV
$ chmod 600 .env
$ docker compose -f docker-compose.prod.yml up -d --build
The database publishes no port — only the server reaches it, over the compose network — and the server runs as an unprivileged user. The first build takes a while on a small machine (about fifteen minutes on a Pi 4); later ones reuse the cached layers.
This is a stand, not a supported deployment: backups, restore and an install guide come with the deployment milestone.
Configuration
Everything comes from the environment:
| Variable | Meaning | Default |
|---|---|---|
DATABASE_URL |
PostgreSQL connection string | required |
KASL_SERVER_ADDR |
Address the HTTP server binds to | 0.0.0.0:8080 |
KASL_AGENTS |
Agents to provision on startup, as email:token pairs separated by commas |
none |
RUST_LOG |
Log filter (tracing syntax) | kasl_server=info,tower_http=info |
Database migrations are embedded in the binary and applied on startup.
KASL_AGENTS is how the first agents get in while the admin UI does not exist
yet: each entry becomes an employee and an agent holding that token's hash.
Re-running with a changed token rotates it and revokes the old one. Tokens are
secrets — pass them through your deployment's secret store, not a committed
file — and the variable stops being the way in once tokens are issued from the
UI.
What it will do
- Ingest work-time data from kasl agents: workdays, pauses, tasks, reports (days, backfill and history import: done)
- Manager dashboards: who is working right now, hours per person, trends over time
- Personal pages: every employee sees their own history
- Roles: admin, manager, employee
- Self-hosted: a single binary (Docker image planned) plus PostgreSQL — your data stays on your infrastructure
Stack
Rust REST API (axum) + PostgreSQL (sqlx), React single-page app for the web UI. Architectural decisions are recorded in docs/adr/.