> For the complete documentation index, see [llms.txt](https://www.conserver.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://www.conserver.io/mcp-server/what-is-the-vcon-mcp-server.md). # What is the vCon MCP Server? Have you ever wanted to ask an AI assistant about past conversations? Maybe you want to find all the times a customer called about billing issues, or analyze patterns in support calls, or track what happened in a sales meeting. The vCon MCP Server makes this possible. This post explains what the vCon MCP Server is, what problem it solves, and why it might be useful for you. ### The Problem with Conversation Data Most businesses have conversations happening everywhere. Phone calls, video meetings, chat messages, emails. These conversations contain valuable information, but they are usually scattered across different systems. Each system stores data in its own format. This makes it hard to: * Search across different types of conversations * Analyze patterns over time * Share conversation data between tools * Work with AI assistants on conversation history * Maintain privacy and compliance standards You might have customer support calls in one system, sales meetings in another, and email threads in yet another. To get a complete picture, you would need to check all three systems separately. That takes time and effort. ### What is vCon? vCon stands for Virtual Conversation. It is an IETF standard format for representing conversations. Think of it like PDF for conversations. Just as PDF is a standard format that works across different computers and programs, vCon is a standard format that works across different systems. A vCon file can contain: * The actual conversation content, whether it came from voice, video, text, or email * Information about who participated in the conversation * Analysis results from AI, like transcripts, sentiment scores, or summaries * Attachments like documents or images related to the conversation * Privacy markers that track consent and can hide sensitive information The key benefit is portability. If you store conversations in vCon format, you can move them between systems without losing data. You are not locked into one vendor's system. You own your conversation data in a standard format. ### What is MCP? MCP stands for Model Context Protocol. It is a way for AI assistants to use external tools and data sources. Without MCP, AI assistants can only work with the information they learned during training. They cannot access your live data or perform actions in your systems. With MCP, an AI assistant can: * Read data from your databases * Perform actions using your tools * Access real-time information * Maintain context about what you are working on Think of MCP like giving an AI assistant access to your toolbox. The assistant can see what tools are available, understand what each tool does, and use them when you ask. This makes AI assistants much more useful for real work. ### What is the vCon MCP Server? The vCon MCP Server combines these two ideas. It is a server that lets AI assistants work with conversation data stored in vCon format. You connect the server to an AI assistant like Claude, and then the assistant can: * Create new conversation records * Search through historical conversations * Analyze conversations for insights * Organize conversations with tags * Answer questions about your conversation data The server speaks the MCP protocol, which AI assistants understand. When you ask the assistant to do something with conversation data, it uses the server's tools to get the job done. ### What Can It Do? Here are the main capabilities: **Store conversations** - The server can store conversations in vCon format, following the IETF standard exactly. **Search conversations** - You can search in four different ways: * Basic filtering by subject, participants, or dates * Keyword search that looks for exact words * Semantic search that finds conversations by meaning, even if the exact words are different * Hybrid search that combines keyword and semantic approaches **Organize with tags** - You can add tags to conversations for easy organization and filtering. Tags work like labels you might put on file folders. **Analyze and monitor** - The server can provide analytics about your conversation database, showing growth trends, content patterns, and health metrics. **Manage components** - You can add or update different parts of a conversation, like adding analysis results or attaching files, without recreating the whole conversation. **Use templates** - The server includes templates for common conversation types, making it easier to create new records. **Extend with plugins** - The server supports plugins that can add custom functionality, like privacy controls or compliance features. ### Who Would Use This? Several groups of people might find this useful: **Customer support teams** - Store and search support calls, track issues, analyze agent performance, and maintain compliance records. **Sales teams** - Record sales conversations, extract action items, analyze what works, and generate meeting summaries. **Compliance and legal teams** - Maintain conversation archives, apply privacy controls, track consent, and generate audit reports. **Researchers** - Collect conversation datasets, study communication patterns, and build training data for machine learning models. **Developers** - Build applications that work with conversation data using a standard format and API. **Business analysts** - Search across conversations to find insights, track trends, and answer questions about customer interactions. ### A Simple Example Imagine you run a customer support team. You have thousands of support calls stored in a system. You want to know: "What are customers complaining about most this month?" Without the vCon MCP Server, you might need to: 1. Export data from your phone system 2. Load it into a spreadsheet or database 3. Write queries or scripts to analyze it 4. Create reports manually With the vCon MCP Server, you can simply ask your AI assistant: "What are customers complaining about most this month?" The assistant uses the server's search tools to find relevant conversations, analyzes them, and gives you an answer. If you want more detail, you can ask follow-up questions. The assistant has access to all your conversation data through the server. ### Why Standards Matter Both vCon and MCP are open standards. This means: * They are not controlled by a single company * Anyone can implement them * They work across different systems * They evolve through community input * They are documented publicly Using standards gives you options. If you build on top of the vCon MCP Server and later want to switch to a different system, your data is in a standard format. You are not locked in. You also benefit from the work others do with these standards. New tools and integrations appear as the standards grow. ### Getting Started The vCon MCP Server is open source ([vcon-dev/vcon-mcp](https://github.com/vcon-dev/vcon-mcp), MIT licensed) and free to use. The repo ships a TypeScript implementation that targets Node.js 20+, with a published Docker image and an installable `vcon-mcp` npm package. Minimum requirements: * A Supabase Postgres deployment for the database (free tier is fine to start) * An MCP-aware client — Claude Desktop, the MCP inspector CLI, or any custom client that speaks MCP * For semantic search: an OpenAI API key (or another embedding provider — the model is configurable) * For caching, observability, or HTTP transport: see [Transport and Deployment](/mcp-server/transport-and-deployment.md) See [Transport and Deployment](/mcp-server/transport-and-deployment.md) for the full environment-variable reference and three deployment recipes (local development, Docker, Claude Desktop). ### What's Next? This was a high-level overview. The other pages in this section go deeper: * [MCP and AI](/mcp-server/mcp-and-ai.md) — how MCP works with AI assistants in more detail * [What the vCon MCP Server Can Do](/mcp-server/what-the-vcon-mcp-server-can-do.md) — the complete scope of capabilities * [How the vCon MCP Server is Built](/mcp-server/how-the-vcon-mcp-server-is-built.md) — internal architecture * [Tool Reference](/mcp-server/tool-reference.md) — every tool, grouped by purpose * [Contract Tools](/mcp-server/contract-tools.md) — the May 2026 LLM-facing surface * [Transport and Deployment](/mcp-server/transport-and-deployment.md) — auth, transport modes, Docker, npm * [MCP and Conserver Together](/mcp-server/mcp-and-conserver-together.md) — how the MCP server and conserver compose * [Business Cases](/mcp-server/business-cases-for-mcp-servers-and-vcon.md) — when to reach for this --- # Agent Instructions This documentation is published with GitBook. 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