Get Started

Integrating the Pieces MCP with Visual Studio Code brings your workflow context directly into your editor. With this integration, your AI assistant can access past implementations, similar code, and historical debugging context—without searching through commits or notes.

Prerequisites

There are two prerequisites for integrating Pieces with VS Code as an MCP—an active instance of PiecesOS and the fully-enabled Long-Term Memory engine.

Make sure that PiecesOS is installed and running. This is *required* for the MCP server to communicate with your workflow data and pass context through to VS Code. 
If you do not have PiecesOS, you can download it alongside the [Pieces Desktop App](/products/desktop/download) or [install it standalone](/products/core-dependencies/pieces-os/manual-installation#manual-download--installation) here.
For the MCP server to interact with your workflow context, you must enable the Long-Term Memory Engine (LTM-2.7) through the Pieces Desktop App or the [PiecesOS Quick Menu](/products/core-dependencies/pieces-os/quick-menu) in your toolbar.

Installing PiecesOS & Configuring Permissions

Follow the instructions below for a detailed guide on setting up and configuring PiecesOS to correctly pass captured workflow context to the Pieces MCP server.

Getting the MCP Endpoint for PiecesOS

To use Pieces MCP with VS Code, you'll need the MCP endpoint from PiecesOS. VS Code supports Streamable HTTP (recommended) or SSE.

Streamable HTTP (recommended):

http://localhost:39300/model_context_protocol/2025-03-26/mcp

SSE (legacy):

http://localhost:39300/model_context_protocol/2024-11-05/sse
Keep in mind that the **specific port** (e.g., `39300`) PiecesOS is running on **may vary**.

To find the current MCP endpoint with the active instance of PiecesOS, open the PiecesOS Quick Menu and expand the Model Context Protocol (MCP) Servers tab. You can copy the endpoint, which includes the active port number.

You can also find this in the Pieces Desktop App by opening Settings and clicking Model Context Protocol (MCP).

Setting Up VS Code

There are two ways to set up Pieces MCP for VS Code: use the Pieces CLI for automatic configuration, or configure manually.

One-Click Install

Install Pieces MCP in VS Code with a single click. Ensure PiecesOS is running and Long-Term Memory is enabled before clicking.

Method 1: CLI Install (Recommended)

The Pieces CLI can automatically configure Pieces MCP for VS Code—no manual config editing required.

Install the [Pieces CLI](/products/cli/get-started) if you haven't already. In your terminal, run: 
```bash
pieces mcp setup
```
A platform selection menu appears with options: *VS Code*, *Cursor*, *Claude Desktop*, *Windsurf*, *Claude Code*, *Raycast*, and *Warp*. Use the arrow keys to navigate to *VS Code*, then press `return` (macOS) or `enter` (Windows/Linux) to auto-install. For VS Code, you'll be asked to choose *User Settings* (MCP available in all projects) or *Workspace Settings* (MCP for the current project only).

Method 2: Manual Configuration

VS Code uses a servers root key (not mcpServers) in its MCP configuration. The transport type is set with a type field.

Config File Location

Scope Path
Workspace .vscode/mcp.json in your project root
User (global) Via Settings > search "MCP Servers"

Local Setup (Streamable HTTP — recommended)

Add or edit .vscode/mcp.json in your project root:

{
  "servers": {
    "pieces": {
      "type": "http",
      "url": "http://localhost:39300/model_context_protocol/2025-03-26/mcp"
    }
  }
}

Local Setup (SSE — legacy)

{
  "servers": {
    "pieces": {
      "type": "sse",
      "url": "http://localhost:39300/model_context_protocol/2024-11-05/sse"
    }
  }
}

Adding via Command Palette

Press `Cmd+Shift+P` (macOS) or `Ctrl+Shift+P` (Windows/Linux). Search for **MCP: Add Server** and select the command. Select **HTTP** or **SSE** as the transport type. Paste your MCP endpoint and name it `pieces`.

Using Pieces MCP Server in VS Code

Once integrated, you can utilize Pieces LTM directly in VS Code through extensions that support MCP, such as GitHub Copilot Chat.

Open the chat interface for your MCP-enabled extension (e.g., GitHub Copilot Chat). If your extension has chat modes, switch to *Agent* mode so it can use the `ask_pieces_ltm` tool. Ask context-rich questions about your workflow. For example: *"What was I working on yesterday?"* or *"Show me previous implementations of this authentication method."* Check out this [MCP-specific prompting guide](/products/mcp/prompting) if you want to effectively utilize the Long-Term Memory Engine (LTM-2.7) with your new Pieces MCP server.

Updating

To update the URL, edit .vscode/mcp.json and save. VS Code picks up changes without a restart. You can also use MCP: Edit Server in the Command Palette to update the URL for the pieces server.

Troubleshooting

If you're experiencing issues integrating Pieces MCP with VS Code:

  1. Verify PiecesOS Status: Ensure PiecesOS is actively running on your system.

  2. Confirm LTM Engine Activation: Make sure the Long-Term Memory Engine (LTM-2.7) is enabled in PiecesOS.

  3. Check Config Location: The file must be .vscode/mcp.json (not .cursor/mcp.json or mcp.json at root).

  4. Verify Transport Type: Use type: "http" for Streamable HTTP or type: "sse" for SSE. Ensure you're using the correct servers key (not mcpServers).

  5. Tools Not Visible: Ensure your MCP-enabled extension (e.g., GitHub Copilot Chat) is installed and active. Run MCP: List Servers to confirm pieces shows as connected.

You're now set to enhance your VS Code workflow with powerful context retrieval through Pieces MCP. Happy coding!