Stop Copy-Pasting Task Context to AI
You use Claude Code or GitHub Copilot daily. But every session starts with manual context setup. mcptask.online gives AI direct access to your task system via MCP.
Acceptance Criteria: User can login...
✓ Acceptance criteria
✓ Related tasks
✓ Attachments
AI Reads Tasks Directly via MCP
How It Works
Set Up MCP Connection (5 minutes)
{
"mcpServers": {
"mcptask": {
"command": "npx",
"args": ["-y", "@mcptask/mcp-server"],
"env": {
"MCPTASK_API_KEY": "your-key"
}
}
}
}
Ask AI to Read Task
"Read task #47 and implement the login feature"AI Gets Full Context Automatically
AI receives:
- Task name and description
- Acceptance criteria
- Parent story/epic context
- Related tasks
- Previous comments
- Attached files
AI Logs Work Automatically
When done, AI calls MCP to:
- Log time spent
- Describe what was done
- Update task status
- Add any notes
Zero manual context setup. Zero manual logging.
The AI Context Problem
Manual Context Setup Every Time
Every Claude Code session starts the same:
- Copy task description
- Paste into chat
- Copy acceptance criteria
- Paste into chat
- Explain the context
- Finally start working
No Automatic Work Logging
AI helped you fix 5 bugs today. But your task system shows nothing. You spend 30 minutes at day's end reconstructing what AI did and logging it manually.
Lost Data:
- What AI actually implemented
- Time spent per task
- Context for future reference
Inconsistent Context
Sometimes you copy the full task. Sometimes you summarize. Sometimes you forget related tasks. AI works with incomplete information. Results vary.
Consequences:
- AI misses requirements
- Rework needed
- Frustration
No Audit Trail
Manager asks: "What exactly did the AI help with this sprint?"
You have: scattered chat logs, fuzzy memories, no structured data.
Impact:
- Can't justify AI tool costs
- No visibility into AI productivity
- No metrics for improvement
Feature Highlights
Complete Task Context
What AI Receives:
- Task name and full description
- Parent epic/story context
- Acceptance criteria
- Related tasks and dependencies
- All comments and discussion
- Attached files (specs, designs)
- Work history
Benefit:
AI understands the full picture, not just a snippet.
Automatic Work Logging
AI Logs:
- Task worked on
- Duration (estimated from session)
- What was implemented
- Progress percentage
- Any blockers encountered
Human Effort:
Zero. AI handles it all.
Consistent Workflow
Every Session:
- 1AI reads task from MCP
- 2AI works on task
- 3AI logs completion via MCP
- 4Human reviews when convenient
No more:
Copy-paste ceremonies, forgotten logging, inconsistent context.
Clear Attribution
Every Action Tagged:
"Effort logged by Claude-Code-1"
"Status changed by AI Agent"
"Comment added by AI Assistant"
Benefit:
Always know what AI did vs. what human did.
Workflow Examples
Bug Fix Session
Before mcptask.online:
- 1Open Jira, find bug ticket (2 min)
- 2Copy description, paste to Claude (1 min)
- 3Copy steps to reproduce (1 min)
- 4Claude investigates and fixes (15 min)
- 5Manually log time in Jira (2 min)
- 6Update ticket status (1 min)
With mcptask.online:
- 1Tell Claude "work on bug #47" (10 sec)
- 2Claude reads task via MCP automatically
- 3Claude investigates and fixes (15 min)
- 4Claude logs work via MCP automatically
Feature Implementation
Before mcptask.online:
- 1Read epic and stories in Jira (5 min)
- 2Copy relevant context to Claude (3 min)
- 3Discuss approach with Claude (5 min)
- 4Claude implements feature (30 min)
- 5Manually document what was done (5 min)
- 6Log time across multiple tasks (3 min)
With mcptask.online:
- 1Tell Claude "implement story #23" (10 sec)
- 2Claude reads story and all subtasks via MCP
- 3Discuss approach with Claude (5 min)
- 4Claude implements feature (30 min)
- 5Claude logs work automatically via MCP
Success Story
Claude Code is 10x more useful now. It reads the full task context, understands the requirements, and logs its work automatically. I haven't copy-pasted a task description in months.
Martin V.
Full-Stack Developer
Using Claude Code with mcptask.online
Results
Context setup time:
5 min → 10 seconds (98% reduction)
Work logging time:
30 min/day → 0 (100% reduction)
AI productivity:
Up 40% (better context = better output)
Audit trail:
100% coverage (was 60%)
Technical Details
Supported AI Tools
Fully Compatible:
- Claude Code (Anthropic)
- Claude Desktop
- Any MCP-compatible assistant
Via REST API:
- Custom AI agents
- GitHub Copilot (with custom integration)
- Other tools via API
MCP Capabilities
Read:
- Tasks, stories, epics
- Comments and attachments
- Project structure
- Work history
Write:
- Log efforts
- Update status
- Add comments
- Complete tasks
Security
Access Control:
- API keys per workspace
- Scoped permissions
- Project-level restrictions
- Action limits
Audit:
- All AI actions logged
- Full attribution
- Exportable history
Pricing for AI Teams
Starter
- 5 projects
- Unlimited tasks
- MCP server access
- GitHub/GitLab webhooks
- 1 user + unlimited AI agents
Best For:
Solo developers using AI daily
Professional
- Unlimited projects
- Unlimited team members
- Advanced MCP features
- Sprint management
- AI work approval workflow
- Advanced reporting
Best For:
Teams where everyone uses AI assistants
MCP access for AI agents are free on all plans. You only pay for account users.
FAQ
Does this work with Claude Code?
Yes! Claude Code is fully MCP-compatible. Setup takes 5 minutes.
What about GitHub Copilot?
Copilot doesn't natively support MCP, but you can use our REST API for custom integration.
Can AI create tasks?
Yes, if you grant that permission. AI can create tasks, subtasks, and comments.
Is AI access logged?
Every AI action is logged with full attribution. You always know what AI did.
Do I need to change my workflow?
Minimally. You'll ask AI to read tasks instead of copy-pasting. Everything else improves automatically.
Give Your AI Assistant the Context It Needs
30-day free trial. MCP server included. Connect Claude Code in 5 minutes.
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