StoryOS

The difference

Your business, run by agents.

Most tools bolt a chatbot on the side. StoryOS makes your workspace the place an agent actually works — reading, writing, and moving your business forward.

A StoryOS task record where an agent has posted research and scheduling results as comments

An agent's work lands where your team already looks: on the record — fields updated, reasoning in the comments.

Why StoryOS is built for agents

Agents fail on work tools because they invent field names, invent IDs, and invent query syntax. StoryOS removes all three: a stable, described schema; server-side validation that names any mistake; and structured filters instead of a query language. The result is an agent that acts on your real data without hallucinating.

MCP = the hands

47 tools to read, write and build any workspace — works with Claude & ChatGPT today.

The workspace = the memory

Your databases are the agent’s long-term state — no brittle context stuffing.

Automations = the nervous system

Triggers and buttons kick off agent runs on events or a schedule.

Approvals = the seatbelt

Consequential moves wait for a human. Autonomy is opt-in, per workflow.

How a run works

From trigger to approved result — one loop, five stops.

Trigger Read schema Act via MCP Write back Human gate Done
1

A trigger fires

A record is created, a state changes, or a schedule comes due. Automations are the nervous system — they decide when an agent should wake up.

2

The agent reads the schema

Over MCP it calls describe_database and sees your fields, types, select options and relations — real names, not guesses. This is why it doesn’t hallucinate structure.

3

It does the work

Query records with structured filters, draft the update, enrich the lead, roll up the numbers. Every write is validated server-side; a mistake gets named, not silently saved.

4

It writes back where you work

The result lands on the record: fields updated, state advanced, a comment explaining what it did and why. No separate chat log to archaeology through.

5

You approve the moves that matter

Consequential actions wait at a human gate. You review from the record or your inbox, and the run continues — autonomy is opt-in, per workflow.

The StoryOS automations panel with agent trigger rules on a Tasks database
The trigger side: rules that wake an agent on record events or a schedule.
A StoryOS board the agent moves work across
The result side: work moving across the board, visible to the whole team.

Your AI. Your bill. Zero markup.

Connect the Claude or ChatGPT you already pay for and StoryOS charges you nothing to use it — not metered, not marked up, on any plan including Free. Most competitors resell AI back to you with margin; we think the AI you bring is yours. If your team doesn’t have its own AI, the optional StoryOS AI add-on offers hosted model access at prepaid, near-cost credits — and it’s the only thing we ever bill for AI.

The StoryOS API tokens page where you create the personal access token your agent uses

One personal access token connects your assistant. Set it up in two minutes →

Three levels of trust

1

Assistive — today

You drive Claude or ChatGPT against your workspace through the MCP. It reads the schema, queries, and writes — grounded, not guessing.

2

Triggered — next

An automation fires an agent on a schedule or a record event. It proposes changes; you approve them from your inbox.

3

Autonomous — later

Policy-bounded agents act within a scope and cost cap, escalating only the edge cases to a human.

Agentic workflows, by the job

A few of the loops StoryOS is built to run.

A StoryOS workspace home — the connected spaces and databases an agent can reach

Everything in the workspace — clients, projects, content, sales — is reachable by the agent, with your permissions as the boundary.

Put an agent to work on your data.

Start free — 30 days of Pro, no card. Connect your own Claude or ChatGPT and we never meter it.