Convyy MCP

Convyy MCP is a standalone MCP server that lets AI clients work with Convyy boards.

Typical usage looks like this:

1. a user opens Convyy in the browser at the hosted domain;

2. a user connects Convyy MCP in Claude, Codex, Cursor, Cline, or another MCP client;

3. the agent gets access to Convyy board tools;

4. the agent works with the board through MCP tools.

What It Is For

Convyy MCP exists so an agent can work with an actual Convyy board instead of only producing text.

Through this MCP server, an agent can:

• read page context;

• understand which page the chat is bound to;

• create new AI-owned board content;

• commit each AI response as a separate batch;

• replace or revert only the latest AI batch for the current chat;

• choose a follow-up action such as append, replace-last-batch, undo-last-batch, new-page, or bind-page.

Related MCP server: Overboard Studio MCP Server

Current Capabilities

The current MCP server includes:

• runtime state for chat-to-page bindings;

• a one-active-generation gate per board runtime;

• follow-up action resolution;

• stdio MCP transport with initialize, ping, tools/list, and tools/call;

• an orchestration entrypoint for normal prompt workflows;

• direct tools for diagrams, kanban boards, template fill, journey maps, vision summaries, and generic board summaries.

MVP Constraints

The current MVP is intentionally constrained:

• the agent does not edit existing user-created objects;

• the agent only adds new AI-owned content;

• every AI response becomes a separate batch;

• undo and replace only work for the latest AI batch of the current chat;

• board-specific side effects go through the controlled Convyy runtime layer.

Main Tools

convyy_run_prompt

The main orchestration tool.

It:

• resolves the follow-up action from the prompt;

• picks the correct tool path;

• works with page binding;

• commits the final batch to the board.

Use this by default unless you specifically need to call a specialized tool directly.

convyy_bind_chat

Explicitly binds the current chat to a page.

Use it when the agent should continue working on a specific page.

convyy_list_pages

Returns the list of pages in the board.

Use it when the client needs to choose a page first.

convyy_revert_last_batch

Reverts the latest AI batch for a chat.

convyy_get_runtime_state

Returns the current MCP runtime state for the board.

Useful for diagnostic or system scenarios.

Direct Tools

These tools are available separately, but in most cases convyy_run_prompt is enough.

convyy_create_diagram

Builds a flow or diagram payload.

Good for:

• auth flows;

• onboarding flows;

• architecture diagrams;

• process flows.

convyy_create_kanban_board

Builds a kanban payload.

Good for:

• backlog boards;

• launch boards;

• task boards;

• work-stage boards.

convyy_fill_board_template

Prepares a payload for a built-in template.

Good for:

• SWOT;

• Business Model Canvas;

• roadmap-like template scenarios.

convyy_create_journey_map

Builds a journey map payload.

Good for:

• onboarding journeys;

• customer journeys;

• service flows;

• service-blueprint-style scenarios.

convyy_analyze_page_images

Prepares a vision-oriented payload from images found on the current page.

convyy_create_board_summary

Generic fallback tool for summary, structure, and draft-style scenarios.

Installation

Install Convyy MCP from its standalone Git repository:

git clone https://github.com/divulture/convyy-mcp.git
cd convyy-mcp
npm install
npm run build

Verification:

npm run typecheck
npm run test

Connect It To An MCP Client

After building, Convyy MCP can be connected like any other stdio MCP server.

Important:

• Convyy MCP is distributed as a separate repository and installed separately by the developer;

• Convyy itself is opened separately at its hosted domain;

• the MCP server does not embed the board inside the AI client, it gives the agent tools to work with an already opened Convyy runtime.

Example:

{
  "mcpServers": {
    "convyy": {
      "command": "node",
      "args": ["./dist/server.js"]
    }
  }
}

If you publish a binary entrypoint:

{
  "mcpServers": {
    "convyy": {
      "command": "convyy-mcp",
      "args": []
    }
  }
}

Recommended Usage Flow

1. call convyy_list_pages

2. call convyy_bind_chat if a specific page should be targeted

3. call convyy_run_prompt

4. call convyy_revert_last_batch if the latest AI result should be rolled back

Example requests:

• Create a kanban board for launch prep

• Build an onboarding journey map

• Create an auth flow diagram

• Fill a SWOT template for our product

• Analyze this screenshot and build a board summary

What Is Required For Real Usage

To actually work with a board, both parts are required:

1. Convyy must be open in the browser at its hosted domain;

2. Convyy MCP must be connected in the AI client.

Typical flow:

1. the user opens Convyy;

2. the user opens an AI chat;

3. the agent calls MCP tools;

4. the result appears in the active Convyy board runtime.

Repository Structure

src/
  application/
  contracts/
  orchestration/
  runtime/
  server/
  tools/
tests/

Commands

npm install
npm run build
npm run typecheck
npm run test