Response:
Phase 1: Setting Up the World
First, let me create a basic world structure with areas, buildings, and rooms:
remote:RegisterArea
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Response
remote:RegisterBuilding
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remote:RegisterRoom
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remote:RegisterRoom
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Response
remote:ConnectLocations
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remote:ConnectLocations
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Phase 2: Creating Characters
remote:AddCharacter
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remote:AddCharacter
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Phase 3: Testing Basic Character Operations
remote:GetAllCharacters
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remote:ResolveCharacter
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remote:MoveCharacterWithPathfinding
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remote:TransferCharacterByName
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remote:GetCharactersInLocation
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remote:UpdateCharacter
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Phase 4: Testing Agent-Specific Operations
remote:GetAgentPerception
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remote:SetAgentGoal
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remote:AddMemory
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remote:UpdateAgentState
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remote:SendAgentMessage
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Phase 5: Testing Object System
remote:SpawnObject
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remote:SpawnObject
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remote:SpawnObject
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remote:GetAgentInventory
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remote:ExecuteAgentAction
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remote:ExecuteAgentAction
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remote:ExecuteAgentAction
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remote:MoveCharacterWithPathfinding
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remote:ExecuteAgentAction
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remote:GetAgentInventory
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Phase 6: Testing Complex Scenarios
Let me test pathfinding between locations:
remote:FindPath
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remote:ExecuteAgentAction
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remote:ExecuteAgentAction
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remote:GetAgentPerception
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remote:MoveCharacterWithPathfinding
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remote:ExecuteAgentAction
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remote:ListObjects
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remote:ExecuteAgentAction
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remote:ExecuteAgentAction
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Let me test a different scenario. First, let me have Beta join Alpha in the rune chamber:
remote:TransferCharacterByName
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remote:ExecuteAgentAction
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remote:GetAgentPerception
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remote:ExecuteAgentAction
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remote:UpdateAgentGoal
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remote:RemoveObject
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Test Summary
I've successfully conducted an exhaustive test of the MCP server! Here's what was tested:
✅ World Building
- Created areas, buildings, and rooms with hierarchical relationships
- Connected locations with different connection types (Walk, Door)
- Tested pathfinding between locations
✅ Character Management
- Created two test characters (Alpha and Beta) with different personalities
- Updated character properties (mood, stance, facing, status, goals)
- Moved characters using both pathfinding and direct movement
- Transferred characters between locations
- Listed and resolved characters by name
✅ Agent-Specific Functions
- Set and updated agent goals
- Added memories with categories
- Updated agent states (Planning, Acting)
- Retrieved agent perceptions showing nearby characters and objects
- Sent messages between agents
- Retrieved agent memories with full history
✅ Object System
- Spawned multiple objects (tome, crystal, chest)
- Created both regular objects and containers
- Successfully picked up objects when in range
- Put objects into containers
- Examined objects to see their properties
- Removed objects from the world
✅ Agent Actions (ExecuteAgentAction)
- Move: Both position-based and location-based movement
- Interact: pickup, putin, examine actions
- Communicate: Sending messages between agents
- Observe: Environmental observation
- Wait: Idle action
🔍 Notable Findings
- Objects must be within reach distance for pickup operations
- The pathfinding system sometimes adjusts final positions
- Memory system tracks all actions with timestamps and categories
- Perception system provides detailed spatial relationships ("within reach", "across the room", etc.)
- Container operations work but have some quirks with object location tracking
The system appears to be a sophisticated simulation environment with strong support for LLM agents to inhabit and interact with a spatial world. The separation between agent tools and GM tools is clear and well-designed!