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AgenticSeek setup: how to run it locally, and when a team needs an open-source system

Running AgenticSeek locally means Docker and a local model, and its repository walks through both. When a team needs shared memory, roles and review instead of one machine, the open-source AI Operating System Kortix is where that work moves.

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Commands

Ship it in three commands, or self-host it

The same loop runs on Kortix Cloud and on a server your team controls.

terminalsh

1curl -fsSL https://kortix.com/install | bash2kortix init3kortix ship

Read the docs

terminalsh

1curl -fsSL https://kortix.com/install | bash2kortix self-host init --domain kortix.example.com --admin-email you@example.com3kortix self-host start

Source: kortix.com/docs/host

What running AgenticSeek locally takes

AgenticSeek is a local AI agent that runs on your own hardware, and its repository describes it as a fully local alternative to Manus AI. Setup starts with three pieces of software: Git, Python 3.10.x, and Docker Engine with Docker Compose. You clone the AgenticSeek repository, copy .env.example to .env, and set WORK_DIR to the folder the agent may read and write, along with the ports its services use.

A local model does the reasoning. The repository lists Ollama and LM-Studio as the local providers, and config.ini names the provider and the model, with deepseek-r1:14b as its worked example. SearxNG and Redis run in Docker beside the model for web search, and ./start_services.sh full opens the web interface on localhost:3000. Every part of the stack runs on the machine.

Where one machine stops and a team starts

AgenticSeek is built for one operator on one machine. Its configuration is a single config.ini on that machine, and both its sessions and its working directory stay on the local disk. There is no shared memory between people, no roles or permissions, and no review step before the agent changes something, so you watch it work and take the result. That fits a developer exploring a local agent, and it stops fitting as soon as a second person needs the same context, or someone else must approve what the agent changes.

Moving the team to Kortix, the open-source AI Operating System

Kortix is the open-source AI Operating System: your agents, their skills, your company memory, and every connector in one git repo you own, with the agents working on real cloud computers. Where AgenticSeek keeps its state in one config.ini on one disk, Kortix keeps the whole system in files a team can clone, review and own.

One isolated sandbox per session. Each session has its own isolated machine and branch, so several run at once without touching each other. Session work reaches main through a change request. Merge is default-deny for agents, so a person reviews the change before it lands. Models and hosting stay with your team. Any model provider with your own keys. Or the ChatGPT plan you already pay for. Run it on Kortix Cloud, in your VPC, or on your own on-prem network. Self-host is free. The full setup guide is in the Kortix docs, and the comparison table on this page sets the two systems side by side.

What changes for a team

Work no longer waits on one machine: sessions run in parallel, each on its own branch.
Setup becomes reviewable: the agents, skills and memory live in a repo with history.
A change waits for a person: nothing reaches main until someone approves it.
Access is per-person and per-agent: roles, groups, and an audit trail scope who can do what.
Models and hosting are the team's call: bring your own keys, and run it where you need it.

Compare

The setup, side by side

The Kortix column quotes Kortix; the AgenticSeek column comes from its own repository.

Our pickKortix

Open source: Yes
Setup lives in: One git repo you own
Models: Any provider with your own keys
Where it runs: Kortix Cloud, your VPC, or on-prem
Isolation: One sandbox and branch per session
Review: A person approves the change request
Shared context: Company memory as files in the repo

A local agentAgenticSeek

Open source: Yes
Setup lives in: A config.ini on one machine
Models: A local model through Ollama or LM-Studio
Where it runs: Your own machine
Isolation: Tasks share one machine
Review: No review step
Shared context: Sessions saved on the local disk

FAQ

AgenticSeek setup questions

What hardware does AgenticSeek need?

For a local model, the repository asks for a GPU that can run a 14B model at minimum, and it recommends a reasoning model such as Magistral or Deepseek. Its FAQ maps the sizes: 14B on 12GB of VRAM (an RTX 3060) covers simple tasks, 32B on 24GB or more (an RTX 4090) gets through most work, and 70B and up on 48GB is what it suggests for advanced use. A 7B model on 8GB is under what it recommends.

Do I need an API key to run AgenticSeek locally?

No. The repository says API keys are optional for anyone running a local model, which it calls the primary purpose of the project, so an empty key field is expected when the hardware is enough. Ollama and LM-Studio both serve local models without a key. A cloud API key is only the fallback for a machine that cannot run a local model at those sizes.

Can I run AgenticSeek on a separate server?

Yes. The repository documents running the model on a dedicated machine and pointing config.ini at it over the network with Ollama or any OpenAI-compatible server such as llama.cpp. No AgenticSeek code runs on that server; you set provider_server_address to its address and keep is_local = False.

Can I run AgenticSeek for a team?

AgenticSeek runs for one operator on one machine, with a single config.ini, local sessions, and no shared memory, roles or review. A team that needs several agents working at once, one memory it shares, and a person approving each change moves to Kortix, the open-source AI Operating System.

Run the work on a system the team owns.

Start with one job, then grow from there.

Try Kortix Read the docs

Open source · Any model, your keys · Self-host, VPC, or on-prem2026-10-15