Contents:
What is the StoriesOnBoard MCP server?
The StoriesOnBoard Model Context Protocol (MCP) server is a powerful integration bridge that connects your story maps directly to AI agents and LLMs (like Claude, Cursor, Visual Studio Code or ChatGPT). The MCP allows an AI to not just "chat" about your project, but to interact with it as an active collaborator.
Traditionally, AI could only help you by generating text that you then had to manually copy and paste into your story map. With the MCP server, the AI gains a "hands-on" connection to your workspace.
The MCP server allows agents to perform both comprehensive read and atomic write operations across the entire story map structure, unlocking powerful automation workflows:
Read & Discovery: Agents can discover story maps within a workspace, retrieve the full hierarchical structure of activities, tasks, subtasks, and releases, and fetch full details (description, comments, attachments etc.) of any specific card.
Write & Structural Changes: Agents can create new cards, update existing card fields, and perform structural changes like reordering, re-parenting tasks, and rescheduling subtasks across releases with a single MCP call.
Available tools for StoriesOnBoard MCP server
The StoriesOnBoard MCP server offers seven specialized tools, covering discovery, read, and write capabilities:
Discovery and Read Tools
Tool Name | Capability |
ListStoryMaps | Discovers all story maps in the workspace, returning key data like ID, slug, title, and the user's role (Admin/Editor/Viewer). |
GetStoryMapCards
| Retrieves the hierarchical card structure of a story map (activities → tasks → subtasks). It now returns a contiguous, zero-based |
GetStoryMapCardDetails
| Fetches the full details of a specific card, including the description, comments, attachments, and weblinks. |
GetStoryMapData
| Provides story map-level reference data necessary for valid write calls, such as collaborator lists, canonical color labels, subtask statuses, active priority framework (e.g., Basic, Moscow, Kano), and persona/annotation names. |
Write and Action Tools
CreateStoryMapCard
| Allows agents to create new activities, tasks, or subtasks with a single MCP call, supporting fields like title, description, color, estimation, and assignee. It also supports positioned insertion using the optional |
UpdateStoryMapCard
| Edits any combination of fields on an existing card in one MCP call. This includes updating the title, description, status, estimation, priority, and annotations/personas. |
MoveStoryMapCard
| Enables agents to perform structural changes: reorder activities, relocate a task under a different activity (reparent), and move a subtask between releases (schedule/unschedule) or different tasks. It uses the zero-based |
Standardization Feature
The MCP Position Semantics is a key standardization feature. It dictates that all relevant MCP tools use a unified, zero-based position field to describe a card's location. This standardization ensures that agents can reliably read a card's position from GetStoryMapCards and use that value directly in CreateStoryMapCard or MoveStoryMapCard for advanced positional commands.
Benefits of using StoriesOnBoard MCP server
The StoriesOnBoard Model Context Protocol (MCP) server represents a paradigm shift in product management. Instead of the AI being a separate chatbot where you copy-paste text, the MCP server turns the AI into an active collaborator with a "hands-on" connection to your actual story map.
By using an MCP-compatible host (like Claude Desktop, Cursor, or IDEs), your AI agent can see, understand, and edit your product's DNA in real-time.
Here are the primary benefits of this integration:
Elimination of Manual Data Entry (Agentic Mapping)
The most immediate benefit is the transition from static documents to visual maps without the "manual labor."
The Benefit: You can provide a Software Requirements Document (SRD) or meeting notes to the AI and say, "Build the backbone and draft the first 20 stories."
How it works: The AI uses the
CreateStoryMapCardtool to programmatically build the hierarchy (Activities → Tasks → Subtasks) in seconds, ensuring your map stays in sync with your latest documentation.
Intelligent Backlog Grooming & Quality Control
Backlog grooming is often the "chore" of product management. An AI agent can now perform this autonomously.
The Benefit: The AI can scan your map for "thin" cards (missing descriptions, story points, or priority) and proactively fill those gaps.
Contextual Awareness: By using
GetStoryMapCardDetails, the AI reads existing team comments and attachments to synthesize accurate Acceptance Criteria (AC) that reflect real team discussions, not just generic AI guesses.
Strategic "Slice" Planning (MVP Development)
Deciding what goes into an MVP vs. a later release is a complex logic puzzle.
The Benefit: You can ask the AI to perform "Value-Based Slicing."
Example: "Identify the 'Happy Path' for a first-time user and move those cards to the MVP release." The AI evaluates the entire map and uses the
UpdateStoryMapCardtool to reorganize your releases strategically.
Real-Time Gap Analysis
Because the AI can "see" the entire horizontal journey, it can spot architectural holes that humans might miss in a flat list.
The Benefit: You can prompt the AI to find missing edge cases.
Example: "Look at our checkout flow. Did we account for a scenario where the user's payment method expires mid-session?" If not, the AI can instantly create the necessary cards to bridge that gap.
Bridging the "Context Gap" for Developers
When developers use AI-powered IDEs (like Cursor or Windsurf) connected to StoriesOnBoard via MCP, the AI understands the "Why" behind the code.
The Benefit: The AI doesn't just see the code; it sees the User Story and the Activity it belongs to.
The Result: This leads to more accurate code generation and fewer "reworks" because the AI has the full business context of the feature it is helping to build.
Learn more about: