Convyy
БесплатноНе проверенEnables AI agents to create and manage Convyy boards, including diagrams, kanban boards, journey maps, and more, through MCP tools like convyy_run_prompt.
Описание
Enables AI agents to create and manage Convyy boards, including diagrams, kanban boards, journey maps, and more, through MCP tools like convyy_run_prompt.
README
A standalone stdio MCP server that lets an AI agent (Codex, Claude, Cursor, Cline, etc.) work with an already open Convyy board: draw on the canvas, apply templates, manage pages, read content, and revert its own actions.
1. What this is
Convyy MCP is a bridge between an AI agent and a live Convyy board. The agent doesn't just
produce text — it calls tools, and the result appears on the canvas.
Core principle: the model owns the content and the structure, the server owns layout and style. The server never invents content from a fixed template — it lays out exactly what the agent sends and styles it to match the board.
How it works
By default the server starts in relay mode:
- the MCP client (Codex/Claude) talks to
convyy-mcpover stdio; convyy-mcpexposes its tools immediately viatools/list;- the Convyy board open in the browser connects to the local relay at
http://127.0.0.1:4318; - tool calls are forwarded into the board runtime and committed onto the canvas.
To actually draw anything you need both halves: an open board in the browser and
Convyy MCP connected in the agent. The --local flag is for debugging only.
Note: these are MCP tools, not slash commands. The correct protocol is
initialize → tools/list → tools/call. Don't type /convyy_draw into the client's input box.
2. Installation
git clone https://github.com/divulture/convyy-mcp.git
cd convyy-mcp
npm install
npm run build
Verify the build:
npm run typecheck # types
npm run test # unit tests
npm run smoke # stdio boot/handshake check
npm run smoke confirms the server starts and answers the handshake. It does not prove that
the browser board is already attached to the relay.
After building, two binaries are available:
convyy-mcp→dist/server.js(the MCP server);convyy-mcp-dev→dist/dev/devRelayCli.js(dev relay CLI).
3. Connecting it to your agent
Connect it like any other stdio MCP server. Point it at dist/server.js or the convyy-mcp
binary.
Claude (Desktop / Claude Code)
Claude Code (CLI):
claude mcp add convyy -- node /absolute/path/convyy-mcp/dist/server.js
Or manually in claude_desktop_config.json (Claude Desktop):
{
"mcpServers": {
"convyy": {
"command": "node",
"args": ["/absolute/path/convyy-mcp/dist/server.js"]
}
}
}
Codex
In ~/.codex/config.toml:
[mcp_servers.convyy]
command = "node"
args = ["/absolute/path/convyy-mcp/dist/server.js"]
If the binary is on your PATH
If the package is installed globally or linked (npm link), it's simpler:
{
"mcpServers": {
"convyy": { "command": "convyy-mcp", "args": [] }
}
}
After connecting
- restart/reconnect the MCP client;
- confirm
tools/listexposes theconvyy_*tools; - open a Convyy board in the browser and check the relay reaches
healthy; - give the agent a task — the result appears on the canvas.
4. Available tools
Five tools with clear boundaries: four write tools (draw, apply_template, pages,
revert) and one read tool (analyze).
convyy_draw — draw anything
The universal tool. The agent sends an array of elements built from native board primitives;
the server lays them out as canvas objects.
Supported elements:
shape— a shape (process, decision, terminator, rectangle, ellipse… the flowchart set);sticky— a sticky note (with a colour);frame— a container frame;text— a text block;connector— a link between elements (from/toby id).
An optional layout hint (free | flow-lr | grid) lets the agent skip coordinates and have
the server place elements. This is the escape hatch for anything that doesn't fit a template
(custom diagrams, sticky sets, flows, summaries).
convyy_apply_template — adaptive named template
Recurring business artefacts with a tuned layout and style. The agent provides a templateId
and a structure (lanes and stages of any size); the server builds the grid and grows it
to fit the content, inheriting the preset style. Content is never truncated.
Available templateIds:
cjm— customer journey map (default lanes: actions/pains/opportunities; add your own);swot— SWOT analysis;raci— RACI matrix (roles × tasks);retro— retrospective board;bmc— Business Model Canvas;kanban— kanban board (rendered as a native kanban frame).
Calling with { "list": true } returns the available templates and their structure shape
without committing anything.
convyy_pages — page management
action:
list— pages + active page + session binding;create— create a page (name) and make it active;switch— switch to a page (pageId).
convyy_analyze — read the canvas (read-only)
scope:
image— analyze the images on the page;page— text summary of the whole page;selection— summary of the selection (falls back to the whole page if unavailable).
Returns a text summary and changes nothing on the board.
convyy_revert — undo
Reverts the last AI batch of the current session. A safety tool.
Example prompts
- "Draw an auth flow diagram with a branch" →
convyy_draw - "Build an onboarding CJM with 6 stages and an emotions lane" →
convyy_apply_template(cjm) - "Launch kanban: Backlog / Doing / Review / Done" →
convyy_apply_template(kanban) - "Drop 5 sticky notes about risks" →
convyy_draw - "What's on this page right now?" →
convyy_analyze(page) - "Undo that" →
convyy_revert
Constraints (MVP)
- the agent does not edit existing user objects — it only adds new AI-owned content;
- every response is committed as a separate batch;
- undo only works for the last AI batch of the current session;
- native tables and images in
convyy_draware not supported yet (backlog) — grid-style tables are assembled fromshapeelements.
Architecture
The public surface (what the model sees in tools/list) is owned by the server catalog.
Rendering to the board goes through the internal commit engine (runPrompt → commitBatch) —
which is no longer a public tool. The agent names a content tool directly (convyy_draw /
convyy_apply_template) and the server resolves the page and commits the batch.
src/
application/ # orchestration: runPrompt (internal commit engine), pages, analyze
contracts/ # tool, session and host-adapter types
orchestration/ # tool registry, follow-up actions, session machine
runtime/ # runtime state (session ↔ page bindings)
server/ # stdio transport, JSON-RPC, tool catalog
tools/ # drawTool, templateTool, templatePresets
tests/
Commands
npm install
npm run build
npm run smoke
npm run typecheck
npm run test
Troubleshooting (relay)
If tools/list exposes the tools but nothing shows up on the board, the problem is the
board↔relay link, not MCP registration:
- the board's relay diagnostics panel is open and not
disabled; - it reached
healthy(instead of getting stuck inconnecting/failing); - the local relay is listening on
127.0.0.1:4318; - the server was started without
--local.
An error like Unknown command: /convyy_draw only means a tool was called as a slash command —
it's not a server failure. Tools are invoked through tools/call.
Установка Convyy
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/divulture/convyy-mcpFAQ
Convyy MCP бесплатный?
Да, Convyy MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Convyy?
Нет, Convyy работает без API-ключей и переменных окружения.
Convyy — hosted или self-hosted?
Доступен hosted-вариант: Unyly запускает сервер в облаке, локальная установка не обязательна.
Как установить Convyy в Claude Desktop, Claude Code или Cursor?
Открой Convyy на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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