Connect your AI agent to the live story map.

Model Context Protocol (MCP) is the connection between an agent environment and StoriesOnBoard tools. Use it to inspect product context and carry out supported map changes, then review the result on the board. The MCP server is generally available.

  1. Agent request
  2. Read the map
  3. Review a proposal
  4. Apply a change
  5. Read back the result

Illustrative workflow. Approval is an instruction in the agent process; review the permissions configured in your host.

Meal-ordering map showing the Confirm address card used in the MCP read-and-verify example.
Confirm address card in the MVP under Confirm and pay, the target of the MCP workflow example. Illustrative target for the workflow below: read the selected story, propose a clearer description, apply an approved change, and verify the same card. This is a sample board, not a recorded agent execution. Open full map

Connect your workspace

Use the official server endpoint below when adding StoriesOnBoard as a remote MCP connector. The general availability announcement lists Standard, Pro, Plus, Premium, and trial plans. Check the current plan information and your agent host's connector support before setup.

For Claude Desktop, the documented path is Settings → Connectors → Add custom connector. Enter the endpoint, connect, choose the StoriesOnBoard workspace, and authorize it. Configure the tools you want the host to make available, then start a conversation. Other hosts may use a different setup screen; use their supported remote MCP connection flow rather than assuming the same configuration file.

Choose where the work happens
AI AssistInside StoriesOnBoard

Develop the map and card content.

External agentMCP connection

Read context and use supported map operations.

Story mapShared product context

Review the result with your team.

Workflow illustration; not a product screenshot.

Read the documentation: Connect Claude Desktop to StoriesOnBoard · MCP general availability announcement

What the connection lets an agent work with

The server exposes discovery, read, and write operations. Start by finding the intended map and inspecting its current structure. Do not infer identifiers, valid field values, or positions from a screenshot when they can be read from the map.

The examples below describe tasks rather than promise a fixed inventory. Consult the current tool reference and the tools exposed in your connected host for accepted inputs and available operations.

One Place an order goal above two equal-size steps: Choose dishes and Confirm and pay.
Illustrative backbone: one goal, two steps.
What the connection lets an agent work with
TaskDocumented toolsExample use
Discover a mapListStoryMapsIdentify the right map before a task.
Read structure and detailsGetStoryMapCards · GetStoryMapCardDetailsInspect a story and its place in the journey.
Read valid reference dataGetStoryMapDataCheck statuses, collaborators, and other allowed values.
Create or edit cardsCreateStoryMapCard · UpdateStoryMapCardApply a reviewed story or description change.
Reorganize selected workMoveStoryMapCardPlace a story under the intended step or release.

Read the documentation: MCP capabilities and connection endpoint

Make your first task a read-only orientation

Begin with a small task that proves you connected the correct workspace and map. Ask the agent to list maps, identify the one you mean, and summarize a selected journey without writing anything. Review the map name and the resulting summary before moving to edits.

For our meal-ordering example, the agent should recognize that Confirm address sits in the payment step of the first release. If it describes a different board or cannot read the story details, resolve the connection or access issue before asking it to generate new work.

The story in context
GoalPlace an order
StepConfirm and pay
StoryConfirm address

Release MVP Persona First-time customer

Illustrative meal-ordering example.
A useful first result
The intended map is identified, its structure is understandable, and any unavailable details are reported.
A reason to stop
The workspace is wrong, the target is ambiguous, or the agent is guessing at the board's content.

From a proposal to a verified board change

Use a bounded write task next. Ask for a proposed description of one existing story, review the text, and explicitly authorize the change you want. The agent should then inspect the updated card rather than treating a submitted request as proof of the final state.

Human approval here is a workflow instruction, not a claim that every host always prompts before every write. Review your host's tool permissions. If an operation fails or the connection drops, read the current state before retrying; an uncertain result is a reason to inspect, not blindly repeat a creation request.

A visible review loop
Read

Inspect the selected story and release.

Propose

Explain the change and open questions.

Review

The team decides what to apply.

Verify

Read back the result on the board.

Workflow illustration; not a product screenshot.
Worked example · meal ordering

Starting point

A chat response contains proposed acceptance criteria.

More useful result

The approved description is visible on the intended StoriesOnBoard card, with its original hierarchy and release preserved.

Review with your team: Compare the saved description with the approved version and confirm that unrelated cards were not changed.

Check access and scope before troubleshooting the prompt

If no maps appear, verify the authorized workspace and account. If reads work but a write fails, inspect the error and the tool configuration instead of repeatedly rewriting the prompt. A visible title alone is not proof of write access.

When the agent identifies the wrong card, narrow the task with the map and surrounding step. When results are incomplete, ask what was inspected and which details were unavailable. The connection supplies a way to interact with the product; the host, model, instructions, permissions, and source material still affect the outcome.

Choose where the work happens
AI AssistInside StoriesOnBoard

Develop the map and card content.

External agentMCP connection

Read context and use supported map operations.

Story mapShared product context

Review the result with your team.

Workflow illustration; not a product screenshot.

Read the documentation: Connect Claude Desktop to StoriesOnBoard

Built with StoriesOnBoard AI + MCP

Todoista

Keep track of your tasks, delegated commitments, and the right moment to follow up.

Todoista daily dashboard showing tasks you own and commitments waiting with others.Explore Todoista

TeamRally

Explore an interactive preview of a team movement challenge, with activities, role bonuses, and shared scores.

TeamRally interactive preview with a walking activity, role bonus, and team standings using sample data.Explore TeamRally

SpendVsInvest

Explore how everyday spending compares with a hypothetical investment using historical market data.

SpendVsInvest calculator comparing a weekly coffee budget with a historical investment timeline.Explore SpendVsInvest

Clear answers before you start.

Is StoriesOnBoard MCP generally available?+

Yes. StoriesOnBoard has announced general availability. The announcement includes Standard, Pro, Plus, Premium, and trial plans; use the current official documentation for plan and connection details.

Does connecting MCP give the agent unlimited access?+

The documented setup authorizes a selected workspace and lets you configure tools in the host. Review the account, workspace, and enabled operations. Do not assume that a prompt alone changes underlying access rights.

Does MCP replace an AI skill?+

No. MCP provides the tools for reading and changing the map. A skill supplies instructions about how to perform a task with those tools. You can connect MCP before adding a specialized workflow.

Try one focused workflow on your own product.

Choose a real question, keep the scope small, and review the result with the people who own the decision.

Open the connection guide