Cursor needs to stop guessing names and check first

[SoMaCoSF]

Dope.

Ive been working on Agent Orchitration Control Plane App all day.

Here is an earlier today version of my readme…

Its taking on a scope_kreep in just this afternoon and evening that its super fun and crazy.

Developing with YOLO is so fn fantastic.!!!

(also not that when you hit the “25 call limit” stall-warning:

EDIT, HAHA did it again:

Slap My B**** Up - Or how talk to agent?

[NOTE: I am going to stream of conscious the development of my new Shiny_Object_ADHD_project: Just curious how others talk to their bots, for great justice: (Im building a Huge Rabbit Hole Warren for myself its seems - but man this is fun. I’ve wanted this my whole life, as a former Director of Devops, this is like having infinite Devops Eng Minions at my beck and call - and since I have tons of experience managing very skills devops engineers, that I could never compare to - but I knew how …

Introducing the Cursor Agent Control Plane: Multi-Instance Collaboration with PostgreSQL

TL;DR

A PostgreSQL-based control plane that enables multiple Cursor IDE instances to work together seamlessly, sharing context, commands, and workspace state across machines.

The Vision

Imagine running Cursor on multiple machines, each instance aware of the others, sharing context, and working together seamlessly. That’s what the Cursor Agent Control Plane enables - a distributed system where Cursor instances become collaborative agents.

Architecture Overview

graph TB
    subgraph "Control Plane"
        PG[("PostgreSQL<br/>Source of Truth")]
        
        subgraph "Core Services"
            CMD["Command Queue"]
            SYNC["Sync Manager"]
            LOCK["Lock Manager"]
            CTX["Context Manager"]
        end
        
        subgraph "Monitoring"
            HEALTH["Health Check"]
            METRICS["Metrics"]
            LOGS["Event Log"]
        end
    end
    
    subgraph "Agent 1 (Machine A)"
        A1["Cursor Instance"]
        A1_WS["Workspace"]
        A1_COORD["Coordinator"]
    end
    
    subgraph "Agent 2 (Machine B)"
        A2["Cursor Instance"]
        A2_WS["Workspace"]
        A2_COORD["Coordinator"]
    end
    
    A1_COORD --> PG
    A2_COORD --> PG
    PG --> CMD & SYNC & LOCK & CTX
    CMD & SYNC & LOCK & CTX --> HEALTH & METRICS & LOGS

Key Features

Feature	Description	Implementation
Agent Discovery	Automatic discovery and registration of Cursor instances	PostgreSQL-based session tracking with heartbeats
Command Queue	Cross-instance command execution	Priority-based queue with ACID guarantees
Workspace Sync	File synchronization and conflict resolution	Content hashing and version tracking
Shared Context	Distributed knowledge sharing	JSONB-based context store with versioning
Resource Locking	Distributed locking mechanism	Row-level locks with timeout management
Event Logging	Comprehensive audit trail	Structured logging with context preservation

Communication Flow

sequenceDiagram
    participant A1 as Cursor Agent 1
    participant DB as PostgreSQL
    participant A2 as Cursor Agent 2
    
    Note over A1,A2: Agent Discovery
    A1->>DB: Register session
    A2->>DB: Register session
    
    Note over A1,A2: Command Execution
    A1->>DB: Enqueue command
    A2->>DB: Poll commands
    A2->>DB: Execute command
    A2->>DB: Update status
    
    Note over A1,A2: Workspace Sync
    A1->>DB: Log file change
    A2->>DB: Detect change
    A2->>A2: Apply change

Implementation Highlights

1. PostgreSQL as Source of Truth

-- Agent session management
CREATE TABLE cursor_control.agent_sessions (
    session_id UUID PRIMARY KEY,
    machine_name TEXT,
    workspace_path TEXT,
    capabilities JSONB,
    last_heartbeat TIMESTAMPTZ
);

-- Command queue
CREATE TABLE cursor_control.command_queue (
    command_id UUID PRIMARY KEY,
    source_agent UUID,
    target_agent UUID,
    command_type TEXT,
    payload JSONB,
    status TEXT
);

2. Python Coordinator

class CursorPgCoordinator:
    """PostgreSQL-based coordinator for Cursor agents"""
    
    def enqueue_command(self, target: str, command: str, payload: dict):
        """Send command to another agent"""
        
    def get_pending_commands(self) -> list:
        """Get commands waiting for execution"""
        
    def update_workspace_state(self, changes: list):
        """Sync workspace changes"""

Benefits

1. Seamless Collaboration

   • Share context between instances
   • Coordinate actions across machines
   • Maintain workspace consistency

2. Robust Architecture

   • ACID compliance for critical operations
   • Built-in monitoring and recovery
   • Scalable design

3. Developer Experience

   • Automatic synchronization
   • Cross-machine debugging
   • Shared knowledge base

Real-World Use Cases

Scenario	Description	Benefit
Multi-Machine Development	Work across desktop and laptop	Seamless context switching
Team Collaboration	Share debugging sessions	Real-time assistance
Resource Distribution	Distribute compute-intensive tasks	Better resource utilization
Knowledge Sharing	Share discoveries and insights	Improved team efficiency

Getting Started

1. Prerequisites

   • PostgreSQL 14+
   • Python 3.8+
   • Cursor IDE

2. Quick Setup

   # Clone the repo
   git clone https://github.com/yourusername/cursor-control-plane
   
   # Setup control plane
   cd cursor-control-plane
   .\scripts\setup_control_plane.ps1
   
   # Start coordinator
   python .control_plane/agents/pg_coordinator.py
   

What’s Next?

1. Enhanced Features

   • Real-time collaboration
   • Shared debugging sessions
   • Cross-machine testing

2. Community Contributions

   • Plugin system
   • Custom commands
   • Integration patterns

Join the Discussion

I’m excited to share this project with the Cursor community and would love to hear your thoughts:

1. What features would you like to see?
2. How would you use multiple coordinated Cursor instances?
3. What integration patterns would be most valuable?

Let’s build a more connected Cursor ecosystem together!

Resources

• GitHub Repository
• Technical Documentation
• Architecture Overview

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Note: This is an open-source project in development. Contributions and feedback are welcome!