Dutify 教學:讓 AI 智能體以單一 MCP 連接器接入四項工作區產品
Give your AI agent one MCP connector to your whole workspace
Dutify 教學示範以一個託管式 MCP 伺服器和一個 API key,讓 AI 智能體連接 Dutify Cloud、Dutify Hub、Codexum 和 Roadmarq 四項產品。
Most AI agents start their first day the way a new hire does: one login for the task tracker, another for the docs, another for call recordings, another for customer feedback. Every extra tool is another token to manage, another set of permissions to reason about, and another place where the agent's picture of the work goes stale.
This tutorial connects an agent to all four through one hosted MCP server and one API key, using Dutify. It takes about five minutes.
What you get
One remote MCP server at https://mcp.dutify.ai (Streamable HTTP), covering four products:
| Product | Tools | What they cover |
|---|---|---|
| Dutify Cloud (projects) | pm_* |
Tasks, subtasks, comments, sprints, views, custom fields, time tracking |
| Dutify Hub (calls) | hub_* |
Call recordings, transcripts, summaries, search across calls |
| Codexum (wiki) | wiki_* |
Spaces, pages, search, attachments |
| Roadmarq (feedback) | fr_* |
Feature requests, bugs, votes, statuses |
Plus a handful of discovery tools (whoami, list_workspaces, find_my_workspace) so the agent can orient itself. The tool list is public; every data call needs a key, and the backend enforces that key's scopes and your workspace permissions on each call.
1. Get a key
Sign up at dutify.cloud (free), then create a personal key in account settings. It starts with du_live_ and works across every product your account can access.
If you'd rather keep an agent inside one product, workspace keys exist too: dk_live_… for Cloud, Codexum and Roadmarq, dh_live_… for Hub.
2. Connect your client
Claude Code:
claude mcp add --transport http dutify https://mcp.dutify.ai --header "X-API-Key: du_live_YOUR_KEY"
Cursor, Claude Desktop and other JSON-config clients:
{
"mcpServers": {
"dutify": {
"url": "https://mcp.dutify.ai",
"headers": { "X-API-Key": "du_live_YOUR_KEY" }
}
}
}
VS Code (.vscode/mcp.json):
{
"servers": {
"dutify": {
"type": "http",
"url": "https://mcp.dutify.ai",
"headers": { "X-API-Key": "du_live_YOUR_KEY" }
}
}
}
3. First calls
Ask the agent to run whoami and then list_workspaces. With a personal key, the agent passes the workspace on each data call; you can also pin one with an X-Dutify-Workspace header.
From there the useful prompts are the ones that cross tools, because that's the part a single-product integration can't do:
- "What did we decide about pricing on last week's calls, and is there a task for it?"
- "Summarize the open feature requests tagged Jira and link any related wiki pages."
- "Create a task for each action item from today's call and assign it to the person who took it."
A note on scope
One connector does not mean one giant permission. A personal key can only reach what your account can reach, and a workspace key is bound to one workspace and product family. For an agent that only needs to read the roadmap, give it a narrow key, not your personal one.
Links
- Server docs and configs for more clients: github.com/dutifyai/dutify-mcp
- Official MCP Registry:
io.github.dutifyai/dutify - Product: dutify.ai
來源:DEV Community · dev.to
