Loma documentation
Loma is an AI Agents Factory for your whole team — one agent, in Slack and a dashboard, that knows your tools, runs on open models or your pooled Claude subscriptions, automates work on schedules and webhooks, and shares a team-wide skill library.
These docs cover installing, configuring, and operating your own Loma deployment. If you’re new, start with Getting started.
How Loma fits together
- Backend — a Python service (aiohttp + Slack Bolt) that runs the agent, serves the API, and receives webhooks. Listens on port
3000. - Dashboard — a Next.js app for chat, conversation history, skills, flows, integrations, configuration, users, and usage. Listens on port
3001. - MongoDB — stores conversations, skills, flows, users, integrations, and usage.
- Agent runtime — OpenCode by default (open-source models); optionally a pool of Claude Code accounts.
- Skill assets — non-text skill files live on local disk at
LOMA_SKILL_ASSET_DIR.
Where to go next
| Section | What’s inside |
|---|---|
| Getting started | Quickstart, a fresh EC2/GCP install, and local development |
| Configuration | Environment reference, feature flags, editing config from the dashboard |
| Agent runtime | OpenCode, Claude account pooling, choosing a model |
| Skills | Authoring, importing, assets, and versioning team knowledge |
| Flows & automations | Scheduled routines and webhook-triggered agent tasks |
| Integrations | Connecting databases, issue trackers, CRM, docs, and observability |
| Slack app | Creating and installing the Slack bot |
| Authentication | Local credentials and Google OAuth |
| Deployment & networking | Reverse proxy, single-port exposure, HTTPS, backups |
| Security & roles | Posture and role-based access |
Source code
Loma is open source at github.com/plotlinelabs/loma. This repository is the clean OSS codebase — company-specific knowledge, prompts, playbooks, and credentials belong in your database and environment, never in source.