MCP Server the Character Vector Database

What is MCP Server the Character Vector Database?

MCP Server the Character Vector Database is a vector database system for managing complex internal states, emotions, relationships, and memories of agentic AI characters. It integrates with AI assistants through the Model Context Protocol (MCP) and is intended for AI character developers.

How to use MCP Server the Character Vector Database?

Install Python 3.8+, clone the repository, and install dependencies with pip install -r requirements.txt. Start the MCP server with python main.py, or python main.py test for test mode. Configure it in Claude Desktop by adding the server command to claude_desktop_config.json.

Key features of MCP Server the Character Vector Database

• Character profile management with personality traits, values, goals, and fears
• Session continuity with state persistence between sessions
• Oscillation pattern analysis using secure entropy and pink noise
• Document integration for loading and searching system documentation
• Security-focused implementation with no dynamic compilation or pickle
• MCP protocol integration for seamless AI assistant connectivity

Use cases of MCP Server the Character Vector Database

• Maintaining a consistent character persona across multiple AI interaction sessions
• Storing and retrieving conversation history and character memories
• Analysing character evolutionary trends over time
• Managing relationship states between characters and users
• Providing secure entropy and oscillation metrics for character behavior modulation

FAQ from MCP Server the Character Vector Database

What are the runtime requirements?

Python 3.8 or later, pip or conda, and standard dependencies (ChromaDB, Sentence Transformers) installed via requirements.txt.

How do I resolve a ChromaDB initialization error?

Delete the ./chroma_db directory and restart the server to force reinitialization.

What security measures are implemented?

No dynamic compilation, no pickle, no subprocess calls, path traversal attack prevention, secure file permissions, and strict session ID validation.

How are sessions managed?

Sessions can be started (start_session), resumed (resume_session), and exported (export_session_data). Session state includes oscillation buffer data and is stored in secure JSON files.

What data types are supported?

The system supports 19 data types including conversation, memory, internal state, relationship, engine state, oscillation pattern, and character profile data.