roadmap-skill
Click on "Deploy 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., "@roadmap-skillcreate a task to research user authentication options"
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.
Roadmap Skill
AI-readable docs: llms.txt · llms-full.txt · Architecture · Tool Interface Standard
What Makes It Different
Shared context — Chat with your Agent to plan tasks, or edit directly in the Kanban — both stay in sync. Your Agent always sees the latest state.
Agent-native — Built as an MCP server. Your AI can create, update, and query tasks directly in conversation.
Visual workspace — Open localhost:7860 when you feel like it, or ask your Agent to open it with open_web_interface. Kanban for status, Graph View for sequencing. Or just stay in chat. All three work.
Local-first — Your data lives on your machine. No accounts, no cloud sync, no vendor lock-in.
Related MCP server: crunchy-work
New in v0.3.0: Graph View
Graph View is one of the headline features in v0.3.0.
Kanban is great for tracking status. Graph View is for understanding execution order.
It helps you and your Agent answer questions like:
What has to happen first?
Which tasks are ready right now?
What is blocked by unfinished work?
Which dependency should be added, reversed, or removed?
Instead of treating roadmap tasks as a flat list, Graph View turns them into a visual dependency map with node connections, ready/done states, detailed task cards, and export support. It is designed for planning sessions where sequencing matters just as much as status.
If you are using Roadmap Skill as an MCP workspace, this is the view that makes agent-assisted planning feel concrete: your Agent can build and update dependency graphs in chat, and you can immediately inspect the structure visually in the web UI.
Quick Start (Zero Config)
# Integrate with your AI assistant (MCP config below)claude mcp add roadmap "npx -y roadmap-skill"{
"mcpServers": {
"roadmap": {
"command": "npx",
"args": ["-y", "roadmap-skill"]
}
}
}/mcp addOr edit ~/.copilot/mcp-config.json:
{
"mcpServers": {
"roadmap": {
"type": "local",
"command": "npx",
"args": ["-y", "roadmap-skill"]
}
}
}{
"mcpServers": {
"roadmap": {
"command": "npx",
"args": ["-y", "roadmap-skill"]
}
}
}Install Cline plugin, then add to cline_mcp_settings.json:
{
"mcpServers": {
"roadmap": {
"type": "stdio",
"command": "npx",
"args": ["-y", "roadmap-skill"]
}
}
}{
"mcpServers": {
"roadmap": {
"type": "stdio",
"command": "npx",
"args": ["-y", "roadmap-skill"]
}
}
}Edit ~/.config/opencode/opencode.json:
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"roadmap": {
"type": "local",
"command": [
"npx",
"-y",
"roadmap-skill"
],
"enabled": true
}
}
}Go to Settings -> MCP -> Add new MCP Server:
{
"mcpServers": {
"roadmap": {
"command": "npx",
"args": ["-y", "roadmap-skill"]
}
}
}{
"mcp": {
"servers": {
"roadmap": {
"command": "npx",
"args": ["-y", "roadmap-skill"]
}
}
}
}Follow Windsurf MCP documentation and use:
{
"mcpServers": {
"roadmap": {
"command": "npx",
"args": ["-y", "roadmap-skill"]
}
}
}{
"context_servers": {
"roadmap": {
"command": {
"path": "npx",
"args": ["-y", "roadmap-skill"]
}
}
}
}One-liner (recommended):
codex mcp add roadmap -- npx -y roadmap-skillManual config — edit ~/.codex/config.toml:
[mcp_servers.roadmap]
command = "npx"
args = ["-y", "roadmap-skill"]Windows: No
cmd /cwrapper needed — Codex handles the subprocess directly.
Server name: Must match
^[a-zA-Z0-9_-]+$. Names with spaces or parentheses are rejected.
Note: Both Codex CLI and the Codex VSCode extension share the same
~/.codex/config.toml. A syntax error breaks both.
After setup, simply tell your AI:
"Create a website redesign project with tasks for homepage, about page, and contact form"
The AI will immediately create the project and tasks, saving them to local storage. You can open http://localhost:7860 anytime to view the visual Kanban board.
Agent Skills
This repository includes installable skills under skills/, distributed through the git repository rather than the published npm package.
Available skills:
skills/roadmap/- lightweight background and routing for roadmap-skillskills/roadmap-task-flow/- capture, enrich, tag, and prioritize roadmap tasksskills/roadmap-planning-views/- build focused planning graphs from task subsetsskills/roadmap-web-visualization/- open and use the local roadmap web workspace
Recommended installation pattern for skill-aware tools:
# install from the git repository when the installer supports repo sources
npx skills add shiquda/roadmap-skillThese skills are still in beta. If you run into issues or have suggestions, feedback is very welcome.
Who Is This For?
Solo developers, AI power users, and vibe coders who want their Agent to be a real collaborator — not just a code generator.
Typical Use Cases
1. Capture Ideas Without Breaking Flow
Mid-session, something pops into your head:
"Note this down: switch the auth module to JWT + refresh token rotation"
Use /quick-capture or just say "help me note this down" — your Agent turns it into a task, saves it locally, and you keep going. No context switch, no forgotten ideas.
2. Let Agent Help You Prioritize
"This month's OKR is finishing the user system refactor — can you list the related tasks and figure out which ones should come first?"
Use /auto-prioritize to let your Agent analyze the current project state and reorder task priorities accordingly.
3. Let Agent Recommend What to Do Next
"What's left on the current project? Any high-priority tasks I haven't touched yet?"
Or use /suggest-tasks — your Agent recommends the next actions based on current progress and priorities.
No tab switching. No copy-pasting. Just ask
Core Features
Feature | Description |
Kanban View | Four columns: Todo, In Progress, Review, Done |
Graph View | Visual dependency map for sequencing work, spotting blockers, and reviewing execution order |
Ready / Blocked Signals | Quickly see which tasks are ready now and which ones still depend on unfinished work |
Dependency Editing | Add, reverse, and remove task dependencies directly from the planning graph |
Graph Export | Export dependency graphs as images for sharing, review, or release planning |
Drag and Drop | Drag tasks to update status, WYSIWYG |
Quick Create | Click "+" button on any column to instantly add tasks |
Dual View | Compact mode for overview, detailed mode for full info |
Smart Search | Quick task search across all projects, keyword filtering |
Supported Platforms
✅ Claude Code, Codex, OpenCode — Command-line AI assistants
✅ Cursor, VS Code — AI-powered IDEs
✅ Any MCP Client — Standard MCP protocol support
Data Storage
Roadmap Skill uses pure local JSON file storage. All data is saved in your user directory:
Platform | Storage Path |
Windows |
|
macOS |
|
Linux |
|
You can export or import backup files from the web interface.
License
MIT © shiquda
Available Tools
31 toolsadd_dependency_view_edgeA
Create a dependency edge between two tasks already present in a dependency planning view. Returns summary plus changed ids by default; set verbose=true for full data.
Inputs: viewId (required), toTaskId (required), projectId (required), fromTaskId (required), +1 more.
add_task_to_dependency_viewA
Add an existing task into a dependency planning view. Returns summary plus changed ids by default; set verbose=true for full data.
Inputs: taskId (required), viewId (required), projectId (required), x, +4 more.
analyze_dependency_viewA
Analyze a dependency planning view and return topological layers, ready tasks, blocked tasks, roots, leaves, and isolated tasks.
Inputs: viewId (required), projectId (required).
batch_update_dependency_view_nodesA
Update multiple task node layouts or notes inside a dependency planning view. Returns summary plus changed ids by default; set verbose=true for full data.
Inputs: nodes (required), viewId (required), projectId (required), verbose.
batch_update_tasksA
Update multiple tasks at once. tags must be existing tag IDs from the same project. Returns summaries by default; set verbose=true for full task data.
Inputs: taskIds (required), projectId (required), tags, status, +3 more.
close_web_interfaceB
Close web visualization interface
Inputs: no named parameters.
create_dependency_viewA
Create a dependency planning view inside a project. Returns summary by default; set verbose=true for full data.
Inputs: name (required), projectId (required), verbose, dimension, +1 more.
create_projectC
Create a new project roadmap. Returns summary by default; set verbose=true for full data.
Inputs: name (required), startDate (required), targetDate (required), description (required), +2 more.
create_tagB
Create a new tag in a project. If color is omitted, it is generated deterministically from tag name.
Inputs: name (required), projectId (required), color, description.
create_taskA
Create a new task in a project. tags must be existing tag IDs from the same project. Returns summary by default; set verbose=true for full data.
Inputs: title (required), projectId (required), description (required), tags, +4 more.
delete_dependency_viewB
Delete a dependency planning view by project ID and view ID
Inputs: viewId (required), projectId (required).
delete_projectB
Delete a project by ID
Inputs: projectId (required).
delete_tagB
Delete a tag by project ID and tag ID
Inputs: tagId (required), projectId (required).
delete_taskB
Delete a task by project ID and task ID
Inputs: taskId (required), projectId (required).
get_dependency_viewA
Get a dependency planning view by project ID and view ID. Returns Agent-friendly task snapshots by default; set verbose=true for raw node and edge data.
Inputs: viewId (required), projectId (required), verbose.
get_projectA
Get a project by ID with all its data (tasks, tags, milestones). Tasks are returned as summaries by default; set verbose=true for full task data.
Inputs: projectId (required), verbose.
get_taskA
Get a specific task by project ID and task ID
Inputs: taskId (required), projectId (required).
get_tasks_by_tagB
Get all tasks that have a specific tag
Inputs: tagName (required), projectId (required).
list_dependency_viewsA
List dependency planning views in a project. Returns summaries by default; set includeTasks=true for Agent-friendly task snapshots or verbose=true for raw node and edge data.
Inputs: projectId (required), verbose, includeTasks.
list_projectsA
List all projects. Summary mode includes current project tags for Agent reuse. Set verbose=true for full project data.
Inputs: verbose.
list_tagsB
List all tags in a project
Inputs: projectId (required).
list_tasksA
List tasks with optional filters. By default, completed (done) tasks are excluded. Set includeCompleted=true to include them. Returns summaries by default; set verbose=true for full task data.
Inputs: tags, status, verbose, assignee, +5 more.
open_web_interfaceD
Open web visualization interface
Inputs: port.
remove_dependency_view_edgeB
Remove a dependency edge from a dependency planning view. Returns summary plus changed ids by default; set verbose=true for full data.
Inputs: edgeId (required), viewId (required), projectId (required), verbose.
remove_task_from_dependency_viewA
Remove a task node from a dependency planning view. Connected edges are removed too. Returns summary plus changed ids by default; set verbose=true for full data.
Inputs: taskId (required), viewId (required), projectId (required), verbose.
update_dependency_viewA
Update dependency planning view metadata. Returns summary by default; set verbose=true for full data.
Inputs: viewId (required), projectId (required), name, verbose, +2 more.
update_dependency_view_edgeA
Update the direction of a dependency edge inside a dependency planning view. Returns summary plus changed ids by default; set verbose=true for full data.
Inputs: edgeId (required), viewId (required), projectId (required), verbose, +2 more.
update_dependency_view_nodeA
Update a task node layout or note inside a dependency planning view. Returns summary plus changed ids by default; set verbose=true for full data.
Inputs: taskId (required), viewId (required), projectId (required), x, +4 more.
update_projectB
Update an existing project. Returns summary by default; set verbose=true for full data.
Inputs: projectId (required), name, status, verbose, +4 more.
update_tagC
Update an existing tag
Inputs: tagId (required), projectId (required), name, color, +1 more.
update_taskA
Update an existing task. tags must be existing tag IDs from the same project. Returns summary by default; set verbose=true for full data.
Inputs: taskId (required), projectId (required), tags, title, +6 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
TDQS
Scored across 31 tools
Most tools are clearly distinct in action and resource. A few pairs like update_task vs update_dependency_view_node could be confused based on names, but descriptions clarify the difference. Overall, the tool set is well-differentiated.
All tool names follow a consistent verb_noun snake_case pattern, including batch_ and *_by_tag conventions. The naming style is uniform and predictable.
At 31 tools, the server exceeds the 25+ threshold, which feels heavy even for a broad roadmap scope. While each tool has a purpose, the count could be streamlined by consolidating some batch operations.
The server provides full CRUD for projects, tasks, tags, and dependency views, plus analysis and web UI control. Minor gaps like a missing get_tag or project-level task reassignment exist, but they are not critical for roadmap workflows.
Maintenance
Related MCP Connectors
Shared task board and knowledge base for AI coding agents Give your coding agents a shared task board and knowledge base, so the plan survives between sessions and across agents.
Task & board management for AI agents + humans. Kanban, comments, digests via MCP.
AI-native project management for tasks, docs, collaboration, and agents.
Project management for AI agents: tasks, docs, decisions and time in one shared team context.
Related MCP Servers
- -licenseNot gradedqualityNot gradedmaintenanceEnables local task planning and execution with DAG-based plans, multiple reasoning methods, and persistence for AI agents.-
- AlicenseNot gradedqualityBmaintenanceA local kanban board and docs tool that AI agents can drive over MCP. It enables project management without accounts or API keys.MIT
- FlicenseNot gradedqualityCmaintenanceEnables AI assistants to manage a local-first Kanban board with Azure DevOps-style workflow rules, including task creation, status updates, subtask breakdown, full-text search, daily summaries, and next-task suggestions.-

AgentTaskerofficial
AlicenseNot gradedqualityBmaintenanceEnables AI agents to create, query, update, claim, hand off, and complete tasks on a local SQLite-backed, project-namespaced kanban board through stdio MCP tools, including filtering for ready/blocked/stale work and exchanging task attachments. It also lets agents list projects and manage statuses, ownership, and evidence without any server or accounts.MIT