Installation
This MCP server can be installed in any AI client that supports the MCP protocol. Refer to your AI client's instructions if it isn't listed here.
Cursor installation steps
Create a .cursor/mcp.json file in your project root with the following content:
{
"mcpServers": {
"LaunchDarkly": {
"command": "npx",
"args": [
"-y", "--package", "@launchdarkly/mcp-server", "--", "mcp", "start",
"--api-key", "api-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"
]
}
}
}
Specify your API key as found on LaunchDarkly's Authorization page.
Claude installation steps
Add the following server definition to your claude_desktop_config.json file:
{
"mcpServers": {
"LaunchDarkly": {
"command": "npx",
"args": [
"-y", "--package", "@launchdarkly/mcp-server", "--", "mcp", "start",
"--api-key", "api-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"
]
}
}
}
Specify your API key as found on LaunchDarkly's Authorization page.
GitHub Copilot CLI installation steps
Use the Copilot CLI to interactively add the MCP server:
/mcp add
Or create/edit ~/.copilot/mcp-config.json with the following content:
{
"mcpServers": {
"LaunchDarkly": {
"command": "npx",
"args": [
"-y", "--package", "@launchdarkly/mcp-server", "--", "mcp", "start",
"--api-key", "api-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"
]
}
}
}
Specify your API key as found on LaunchDarkly's Authorization page.
For more information, see the GitHub Copilot CLI documentation.
Installation steps from a local clone
You can also run the MCP server locally by cloning this repository. Once cloned, you'll need to install dependencies (npm install) and build the server (npm run build).
Then, configure your server definition to reference your local clone. For example:
{
"mcpServers": {
"launchdarkly": {
"command": "node",
"args": [
"/path/to/mcp-server/bin/mcp-server.js", "start",
"--api-key", "api-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"
]
}
}
}
Installation steps using environment variables
Some AI clients allow for accessing environment variables within MCP configurations. In AI clients where this is supported, you can configure your MCP server to read from an environment variable like MCP_LD_TOKEN as follows:
{
"mcpServers": {
"launchdarkly": {
"command": "npx",
"args": [
"-y", "--package", "@launchdarkly/mcp-server", "--", "mcp", "start",
"--api-key", "$LD_ACCESS_TOKEN"
],
"env": {
"LD_ACCESS_TOKEN": "MCP_LD_TOKEN"
}
}
}
}
Installation steps for Docker
If installing the MCP server from the AWS Markeplace, pull the image using an authenticated role using the provided instructions in the marketplace listing.
To run the container:
docker run --rm -p 8080:8080 709825985650.dkr.ecr.us-east-1.amazonaws.com/launchdarkly/mcp --api-key api-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
Then, configure your server definition to reference your local clone. For example:
{
"mcpServers": {
"launchdarkly": {
"command": "npx",
"args": [
"-y", "--package", "@launchdarkly/mcp-server", "--", "mcp", "start",
"--api-key", "$LD_ACCESS_TOKEN"
],
"env": {
"LD_ACCESS_TOKEN": "MCP_LD_TOKEN"
}
"url": "http://localhost:8080/sse"
}
}
}
This won't work in AI clients (such as Cursor) which don't support accessing environment variables directly within MCP configurations. As a workaround, you can invoke a local script from your MCP configuration. See here for an example.