Problem!
Nemáte oprávnenie pristupovať k tejto stránke!
A Task Queue Your AIAgents Can Actually Use
Running coding agents 24/7? Give them a proper task queue. Agents fetch next task, complete it, log progress, repeat. You monitor and steer.
The Autonomous Agent Challenge
No Standardized Task Queue
Current Workaround
Custom scripts, JSON files, manual assignment
Problem
Fragile, no visibility, doesn't scale
Black Box Operation
Current State
Chat logs, scattered files, no structured data
Impact
No confidence in agent work
No Human Oversight
Current State
All or nothing - full auto or manual
Need
Configurable autonomy levels
Scaling Challenges
Problems
Same task picked by multiple agents, No work distribution logic, No capacity management
mcptask.online as Your Agent's Task Queue
The Agent Workflow
Agent calls get_next_task() via MCP
mcptask.online returns highest priority task
Agent works on task (coding, testing, etc.)
Agent calls log_effort() with progress
Agent calls complete_task() when done
Loop: Agent calls get_next_task() again
Task locking prevents duplicate work
Priority-based task selection
Automatic effort logging
Clear completion tracking
Continuous operation loop
Feature Highlights
Smart Task Queue
Agent calls get_next_task() and receives:
- Highest priority available task
- Automatically locked (no other agent can pick it)
- Full context (description, acceptance criteria, related tasks)
- Time estimate (if available)
Priority Factors
| Priority level | Urgent > High > Normal > Low |
| Due date | sooner = higher priority |
| Task type | bugs before features, configurable |
| Age | older tasks surface |
Scoping Options
- Limit to specific projects
- Limit to specific task types
- Exclude certain labels
- Time-based restrictions
Full Activity Logging
Every Action Recorded:
- Task fetched by Agent-1 at 02:34:15
- Agent-1 logged 45 min of work at 03:19:22
- Agent-1 completed task at 03:45:08
- Agent-1 fetched next task at 03:45:12
Morning Dashboard Shows:
- Tasks completed overnight
- Total hours logged
- Success/failure rate
- Any blocked tasks
- Agent activity timeline
Human Oversight Controls
Safety Rails:
Control Types
| Task Types | Agents can only work on approved task types |
| Approval Gates | Certain tasks require human approval before agent starts |
| Max Tasks/Day | Limit how many tasks agent can complete per day |
| Working Hours | Restrict agent to certain hours |
| Pause Button | Stop all agents immediately |
Alerts
- Agent completed task (optional)
- Agent encountered blocker
- Agent failed task
- Unusual activity detected
Multi-Agent Coordination
How It Works:
- Each agent has unique API key
- Task locking prevents conflicts
- Work distributed automatically
- No race conditions
Agent Fleet Management
- See all active agents
- Monitor individual progress
- Pause/resume specific agents
- Reassign work between agents
Scaling
Run 1 agent or 100. Same interface. Same pricing (agents are free).
Agent Configuration Examples
Real-world agent configurations for different use cases
Overnight Bug Fixer
Agent works overnight on bugs only, stops on error.
agent_name: "BugFixer-1"
scope:
projects: ["main-app"]
task_types: ["bug", "hotfix"]
priority_min: "normal"
limits:
max_tasks_per_session: 20
working_hours: "22:00-06:00"
behavior:
on_complete: fetch_next
on_error: pause_and_alert
log_frequency: per_task
Feature Implementation Team
Specialized agents for different work types.
agents:
- name: "Frontend-Agent"
scope:
labels: ["frontend", "ui"]
- name: "Backend-Agent"
scope:
labels: ["backend", "api"]
- name: "Test-Agent"
scope:
task_types: ["test", "qa"]
behavior:
requires_approval: true
Conservative Autonomous Mode
Agent completes task, pauses for human review, then continues.
agent_name: "Careful-Agent"
scope:
projects: ["low-risk-project"]
limits:
max_tasks_per_day: 5
require_approval_for: ["feature", "refactor"]
behavior:
on_complete: pause_for_review
alert_on_every_completion: true
Safety & Control
Autonomy with Oversight
We believe autonomous agents should be powerful AND controllable. mcptask.online provides:
Scoped Access
- Agents only see authorized projects
- Agents only work on approved task types
- Granular permission control
Audit Everything
- Every agent action logged
- Full history exportable
- Clear attribution
Emergency Stop
- Pause individual agent
- Pause all agents
- Immediate effect
Human Gates
- Require approval for specific tasks
- Review before merge
- Sign-off workflows
Alerts
- Real-time notifications
- Error alerts
- Unusual activity detection
Monitoring Dashboard
What You See
Agent Status Panel
- Active agents and current task
- Idle agents
- Paused agents
- Error states
Activity Timeline
- Task started by Agent-X
- Task completed by Agent-Y
- Effort logged
- Errors encountered
Metrics
- Tasks completed (24h / 7d / 30d)
- Hours logged by agents
- Success rate
- Average task duration
- Throughput trends
Alerts
- Critical errors
- Blocked agents
- Unusual patterns
Success Story
We run 3 coding agents overnight. mcptask.online is their task queue. Every morning we review what they completed. We've doubled our throughput without adding headcount.
Sarah K.
Engineering Manager
AI-first startup
Tasks/week
50 → 110
120% increase
Human oversight time
4h/day → 1h/day
75% reduction
Agent success rate
87%
tasks completed without human intervention
Cost per task
Down 60%
Pricing for Agent Operations
MCP access for AI agents are free on all plans. You pay for account users only.
Starter
$15
/month
Best For: Solo operators with 1-2 agents
- MCP server access
- Unlimited AI agents
- Basic monitoring
- 1 human user
Professional
$12
/user/month
Best For: Teams running agent fleets
- Advanced MCP features
- Multi-agent support
- Agent dashboards
- AI work approval workflow
- Advanced reporting
- Priority support
Enterprise
Custom
Best For: Large-scale agent operations
- Dedicated MCP server
- Custom rate limits
- Advanced agent monitoring
- Fleet management tools
- SLA guarantee
- 24/7 support
Frequently Asked Questions
How many agents can I run?
Unlimited agents on all plans. Each agent needs its own API key for attribution.
Can agents conflict with each other?
No. Task locking prevents multiple agents from working on the same task.
What happens if an agent crashes?
Task is automatically unlocked after timeout. Another agent (or the same one after restart) can pick it up.
Can I restrict what agents can do?
Yes. Scope by project, task type, labels. Set approval gates. Limit actions (read-only vs. write).
How do I monitor agents overnight?
Activity log captures everything. Review in morning dashboard. Set alerts for critical events.
Is there an emergency stop?
Yes. Pause individual agents or all agents from dashboard. Immediate effect.
Run Your AI Agents with Confidence
Proper task queue. Full visibility. Safety controls. Start your free trial.
Unlimited agents. Full audit trail. Emergency stop included. 30-day trial.