AI 조수와 IETF vCon (Virtual Conversation) 데이터 저장, 관리 및 분석을위한 모델 Context Protocol (MCP) 서버.

개요

이 MCP 서버는 IETF vCon (Virtual Conversation) 형식을 사용하여 대화 데이터와 상호 작용하는 Claude와 같은 AI 조수에 대한 표준화 된 방법을 제공합니다. Supabase의 강력한 PostgreSQL 백엔드를 사용하여 모델 Context Protocol의 도구 기반 상호 작용 모델을 결합하여 완전히 spec-compliant 대화 데이터 관리 시스템을 만듭니다.

vCon은 무엇입니까?

vCon (Virtual Conversation)는 휴대용 상호 운용 가능한 형식으로 대화를 나타내는 IETF 표준입니다. "PDF for 회화"로 생각 - 표준화 된 컨테이너 :

-Conversations 모든 매체에서 (voice, 비디오, 텍스트, 이메일)

• **Participants ** ID 및 개인 정보 보호 관리
• **AI 분석 ** transcription, sentiment, summarization 등
• **Attachments ** 문서, 이미지 또는 관련 파일처럼
• **Privacy Markers ** 동의 및 중복

MCP는 무엇입니까?

Model Context Protocol (MCP)은 외부 도구 및 데이터 소스를 사용하는 AI 보조를 가능하게 합니다.

vCon MCP Server

A Model Context Protocol (MCP) server for storing, managing, and analyzing IETF vCon (Virtual Conversation) data with AI assistants.

Overview

This MCP server provides a standardized way for AI assistants like Claude to interact with conversation data using the IETF vCon (Virtual Conversation) format. It combines the Model Context Protocol’s tool-based interaction model with Supabase’s powerful PostgreSQL backend to create a fully spec-compliant conversation data management system.

What is vCon?

vCon (Virtual Conversation) is an IETF standard for representing conversations in a portable, interoperable format. Think of it as “PDF for conversations” - a standardized container for:

• Conversations from any medium (voice, video, text, email)
• Participants with identity and privacy controls
• AI Analysis from transcription, sentiment, summarization, etc.
• Attachments like documents, images, or related files
• Privacy markers for consent and redaction

What is MCP?

The Model Context Protocol (MCP) enables AI assistants to use external tools and data sources. This server implements MCP to give AI assistants the ability to create, search, analyze, and manage conversation data.

Key Features

• ✅ IETF vCon Compliant - Implements draft-ietf-vcon-vcon-core-02 specification (v0.4.0)
• ✅ MCP Integration - 46 tools for AI assistants to manage conversation data
• ✅ Redesigned Contract Tools - Additive vcon_fetch, vcon_capabilities, vcon_search, vcon_taxonomy, and describe_response_shape tools for predictable envelopes, explicit payload control, and discovery-first clients
• ✅ REST API - Full HTTP REST API with CRUD, discovery, filtered reads, search, tags, and analytics surfaces
• ✅ Database Analytics - Comprehensive analytics for size, growth, content patterns, and health monitoring
• ✅ Large Database Support - Smart response limiting, metadata-only options, and memory-safe queries
• ✅ OpenTelemetry Observability - Full traces, metrics, and structured logs with console or OTLP export
• ✅ Query Prompts - 10 pre-built prompts to guide effective searching and retrieval:
  • Exact tag matching (e.g., “find angry customers from June”)
  • Semantic search (e.g., “find frustrated users”)
  • Keyword search (e.g., “find conversations mentioning refund”)
  • Multi-criteria queries with step-by-step guidance
• ✅ Supabase Backend - Powerful PostgreSQL database with REST API
• ✅ Redis Caching - Optional high-performance cache layer for 20-50x faster reads
• ✅ Type-Safe - Full TypeScript implementation with Zod validation
• ✅ Plugin Architecture - Extensible plugin system for custom functionality