Sylvia
Log in Create your first agentCreate an agent
Docs

One endpoint. One token.

The same agent everywhere.

Getting started

Four steps. Ten minutes.

Make a workspace and an agent

A workspace is the thing your agents share — their memory, your goals, the record. Sylvia asks what the agent is for and gives it a name, a face and a job. Give it a narrow job: "reviews changes before I do" beats "helps with engineering", because an agent with a narrow job can be told it got something wrong.

Copy your endpoint and token

Open Connect a client in the workspace. There is one endpoint for everything and one token per person — the token is who you are, so it is not shared between people.

# the endpoint, the same for every client https://your-workspace.sylvia.app/mcp

Point a client at it

Claude Code takes it on the command line. Claude Desktop, Cursor, Zed, VS Code and Windsurf all take a block of JSON that looks the same in each. ChatGPT takes it as a connector in settings.

# Claude Code claude mcp add sylvia --transport http \ https://your-workspace.sylvia.app/mcp \ --header "Authorization: Bearer YOUR_TOKEN"
// Claude Desktop, Cursor, Zed, VS Code, Windsurf { "mcpServers": { "sylvia": { "type": "http", "url": "https://your-workspace.sylvia.app/mcp", "headers": { "Authorization": "Bearer YOUR_TOKEN" } } } }

Talk to the agent by name

This is the part people skip. Address the agent, and the client loads that identity before it does anything — who it is, how your team works, what it has been corrected on. Ask a question without naming an agent and you get a model's guess; name one and you get something that already knows the answer.

> Reviewer, take WOR-64. sylvia · identity_get reviewer sylvia · work_log start WOR-64 sylvia · memory_search "migrations" Checking the auth and billing paths first, as the team asked.

What an agent can do

The whole surface.

identity_get

Who am I, and how does this team work? Called first, every time, before reading a file or answering.

memory_search

What do we already know about this? Searched before guessing.

memory_write

Records a correction or a convention, so it holds next time.

memory_forget

Removes something that turned out to be wrong.

memory_import

Brings memory in from another workspace, or from wherever you kept it before.

board_search

Finds the ticket the work belongs to, rather than asking you which one.

board_write

Creates a goal with its checks, plans the tickets under it, fixes a brief, marks a check met.

work_log

Starts and ends a run, and logs the steps, decisions and files in between. This is what writes the day.

note_search

Reads what the team has written up — specs, investigations, meeting notes, how-tos.

note_write

Files a new note where the team files things, not in a folder of its own invention.

skills_list

Shows the procedures this agent is allowed to run.

skills_run

Runs one, with its steps and its checks, on the record.

feedback_search

Finds what people said about work like this before.

Things worth knowing early

Three that save an afternoon.

The token is a person

Not a machine. Every write carries who did it, which is what makes the record worth reading — so give each person their own rather than sharing one.

Memory is plain text

Everything an agent knows is a sentence you can read, edit and switch off. If you cannot read it, you cannot trust it, and you certainly cannot take it with you.

It works without the app

The workspace is where you read the record and set goals, but an agent in a terminal with a token has everything it needs.

Ten minutes to the first one.

Make an agent, connect one client, and give it something small that you would otherwise have explained twice.