> For the complete documentation index, see [llms.txt](https://docs.envector.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.envector.io/1.4.x/integrations/mcp.md).

# MCP

## Introduction

The [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) 🔌 is a protocol for communicating with LLMs, primarily used for exchanging information (context) or performing actions.

🚀 **enVector** supports using MCP with various AI applications. You can interact with your LLMs like Claude through natural language inputs.

## Use Cases

The enVector MCP server allows your AI application to directly interact with enVector's utilities.

* Secure AI coding assistants
* Secure RAG
* Secure Context Memory
* Or other AI applications needs to be secured

## Quick Start

Follow our Quick Start tutorial to run your first secure search or jump right into the detailed [MCP guide](/1.4.x/integrations/mcp/mcp-guide.md) to set up your environment.

1. Run enVector server.
2. Clone the [envector-mcp-server](https://github.com/CryptoLabInc/envector-mcp-server) and setting up the Python environment.

   ```bash
   python -m venv .venv
   source .venv/bin/activate
   pip install -r requirements.txt
   ```

   See more details in [envector-mcp-server manuals](https://github.com/CryptoLabInc/envector-mcp-server/blob/main/MANUAL.md).
3. (Optional) Run MCP server with the following example command:

   ```bash
   python srcs/server.py \
       --envector-address "your-ev-address" \
       --envector-cloud-access-token "your-ev-access-token"
   ```

   This is optional when you run MCP server via AI application (e.g. Claude Desktop). See more details in [Run MCP Server](/1.4.x/integrations/mcp/mcp-guide.md#run-mcp-server).
4. Connect your AI application (e.g. Claude) to the MCP server by configuring settings and Chat with enVector 🚀

   See more details in [Connect MCP Server](/1.4.x/integrations/mcp/mcp-guide.md#connect-mcp-server).

## Next Steps

* [🚀 MCP Guide](/1.4.x/integrations/mcp/mcp-guide.md): How to start enVector MCP in details
* [🔌 MCP Integration](/1.4.x/integrations/mcp/integration.md): How to integrate your AI applications
  * [Claude](/1.4.x/integrations/mcp/integration/mcp-claude.md)
  * [Cursor](/1.4.x/integrations/mcp/integration/mcp-cursor.md)
  * [Gemini](/1.4.x/integrations/mcp/integration/mcp-gemini.md)
  * [Codex](/1.4.x/integrations/mcp/integration/mcp-codex.md)
  * [Cline](/1.4.x/integrations/mcp/integration/mcp-cline.md)


---

# Agent Instructions
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## Querying This Documentation
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Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.envector.io/1.4.x/integrations/mcp.md?ask=<question>&goal=<endgoal>
```

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