scrumdo-mcp
OfficialThe scrumdo-mcp server provides an MCP interface connecting AI tools to ScrumDo project management boards, enabling comprehensive management through the following capabilities:
Board & Project Management
List boards, get board details (columns, custom fields, statistics), list iterations/sprints, labels, and epics
Card Operations
List, search, retrieve, create, update, move, archive cards
Move cards between columns or iterations, assign/unassign members, add/remove labels, set custom fields
Blockers
List active blockers, block cards with a reason (optionally as show-stopper or external dependency), unblock/resolve blockers
Tasks (Checklists)
List, create, update, complete, reopen, and delete tasks on cards
Comments
List, add (with Markdown support), and delete comments on cards
Custom Fields
List field definitions, get/set individual or all custom field values on cards
Members
List organization/project members, find by name, username, or email
Search
Full-text search across card summaries, descriptions, and comments; search by custom field value
Activity Logging
Log structured activity entries to cards; retrieve per-card or workspace-wide activity logs
Webhooks
List, create, and delete project webhooks
Time Tracking
List time entries (per card or project-wide), log time spent on a card
Spec Management
Get, set, and patch card specs; view spec history; check spec drift
GitHub Integration
List repos, link PRs/commits/issues to cards
Agent Runs & Loops
Start, get, list, approve, report progress on, and cancel agent runs
Start/pause/resume/cancel loops, manage verification loops, log loop steps, attach evidence
Intelligence Features
Velocity forecasts, spec complexity analysis, behavior contract verification
Provides tools for linking GitHub PRs, commits, and issues to ScrumDo cards, as well as listing GitHub repositories connected to the project.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@scrumdo-mcpWhat's the status of ENG-42?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
scrumdo-mcp
Connect any MCP-compatible AI tool (Claude Code, Cursor, Windsurf, and others) directly to your ScrumDo boards.
Once installed, your AI assistant can read cards, move them, create tasks, post comments, and search across your board — without you copy-pasting anything.
Installation
pip install scrumdo-mcpRelated MCP server: kanban-mcp
Cursor quick-start
1 — Install
# To run the server only:
pip install scrumdo-mcp
# To run tests too:
git clone https://github.com/ScrumDoLLC/scrumdo-mcp.git
cd scrumdo-mcp
pip install -e ".[dev]"
pytest tests/ -v2 — Get your token
Log in to ScrumDo → your org → Settings → API Tokens → Create Token. Copy it — shown once only.
3 — Add to ~/.cursor/mcp.json
{
"mcpServers": {
"scrumdo": {
"command": "scrumdo-mcp",
"env": {
"SCRUMDO_TOKEN": "your-token-here",
"SCRUMDO_ORG": "your-org-slug",
"SCRUMDO_PROJECT": "your-default-project-slug"
}
}
}
}Your org and project slugs are the short names in your board URL:
app.scrumdo.com/my-company/engineering
4 — Restart Cursor
Done. In any Cursor chat you can now ask:
"What cards are in the current sprint?"
"Move ENG-42 to In Review"
"Add a comment to ENG-42: PR is up for review"
"List all cards assigned to me"
Setup
Step 1 — Get your token
Log in to ScrumDo → your organization → Settings → API Tokens → Create Token.
Copy the token — it is only shown once. This is your personal key; keep it private.
Step 2 — Configure your AI tool
Find your tool's MCP config file and add the scrumdo server entry:
Tool | Config file |
Claude Code |
|
Cursor |
|
Windsurf |
|
{
"mcpServers": {
"scrumdo": {
"command": "scrumdo-mcp",
"env": {
"SCRUMDO_TOKEN": "your-token-here",
"SCRUMDO_ORG": "your-org-slug",
"SCRUMDO_PROJECT": "your-default-project-slug"
}
}
}
}Your org slug and project slug are the short names in your board URL:
app.scrumdo.com/my-company/engineering
Step 3 — Restart your AI tool
Done. Your AI assistant now has direct access to your board.
What you can do
Once connected, just talk to your AI tool naturally:
"What's the status of ENG-42?"
"Move ENG-42 to In Review and add a comment saying the PR is up"
"List all cards assigned to me in the current sprint"
"Create a sub-task on ENG-42: write release notes"
"Search for cards about the login bug"
"What did the team work on this week?"
"Block ENG-42 — waiting on design approval"
"Move ENG-42 to the Sprint 14 iteration"
"Set the due date on ENG-42 to 2026-04-30"
"Assign ENG-42 to Sarah"Available tools (93 total)
Group | Tools |
Boards |
|
Cards |
|
Blockers |
|
Tasks |
|
Comments |
|
Attachments |
|
Fields |
|
Members |
|
Search |
|
Activity |
|
Webhooks |
|
Time |
|
Spec |
|
Spec proposals |
|
GitHub |
|
Agents |
|
Agent runs |
|
Loops & verification |
|
Intelligence |
|
For a governed verification loop, an orchestrator agent calls start_verification_loop
(by VerificationProfile slug or inline proof_requirements/verifier_agent), the
Maker (Grok/Codex) implements and calls run_verifier against the accepted spec
(never self-verifies), and log_loop_step / attach_evidence write the audit trail
to the card. When an agent runs inside a loop (SPRYNG_LOOP_ID set), the loop-scoped
tools default to that loop, so loop_id is optional.
Environment variables
Variable | Default | Description |
| — | Required. API token from Settings → API Tokens (or an agent's token, for AI Agent runs) |
|
| API base URL |
| — | Your organization slug |
| — | Default project slug |
| — | Optional. AI Agent run id this MCP is driving. When set, every write sends the |
| — | Optional. The governed loop this MCP is running inside. When set, writes carry the |
Token scope
Your API token is restricted to your organization's board data only — cards, tasks, comments, members, iterations. It cannot access billing, account settings, or any other organization's data. Revoke it at any time from Settings → API Tokens.
What is MCP?
Model Context Protocol is an open standard for connecting AI tools to external services. Claude Code, Cursor, Windsurf, and other AI editors support it natively. Install the server once; any MCP-compatible tool can use it.
License
MIT
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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