OpenFeature MCP Server
The OpenFeature Model Context Protocol (MCP) Server enables AI coding assistants to interact with OpenFeature through a standardized protocol. It provides SDK installation guidance and feature flag evaluation capabilities directly within your AI-powered development environment.
The OpenFeature MCP Server is a local tool that connects AI coding assistants (like Cursor, Claude Code, VS Code, and Windsurf) to OpenFeature functionality. It acts as a bridge between your AI assistant and OpenFeature capabilities, enabling intelligent code generation and migration, SDK installation guidance, and feature flag evaluation.
This server is published to the MCP Registry under dev.openfeature/mcp.
Quick Startโ
NPX Installโ
The easiest way to use the OpenFeature MCP Server is through NPX, which requires no installation:
{
"mcpServers": {
"OpenFeature": {
"command": "npx",
"args": ["-y", "@openfeature/mcp"]
}
}
}
NPM Global Installโ
You can install the MCP server globally:
npm install -g @openfeature/mcp
Then configure your AI assistant to use the global installation:
{
"mcpServers": {
"OpenFeature": {
"command": "openfeature-mcp"
}
}
}
AI Assistant Configurationโ
Cursorโ
๐ฆ Install in CursorTo open Cursor and automatically add the OpenFeature MCP, click the install button above.
Alternatively, navigate to Cursor Settings -> Tools & MCP -> New MCP Server and add to ~/.cursor/mcp_settings.json:
{
"mcpServers": {
"OpenFeature": {
"command": "npx",
"args": ["-y", "@openfeature/mcp"]
}
}
}
VS Codeโ
๐ฆ Install in VS CodeTo open VS Code and automatically add the OpenFeature MCP, click the install button above.
Alternatively, add to .continue/config.json:
{
"mcpServers": {
"OpenFeature": {
"command": "npx",
"args": ["-y", "@openfeature/mcp"]
}
}
}
Claude Codeโ
Add the server via the Claude Code CLI:
claude mcp add --transport stdio openfeature npx -y @openfeature/mcp
Then manage the connection with /mcp in the CLI.
Windsurfโ
In the Manage MCP servers raw config, add:
{
"mcpServers": {
"OpenFeature": {
"command": "npx",
"args": ["-y", "@openfeature/mcp"]
}
}
}
Codex CLIโ
Edit ~/.codex/config.toml:
[mcp_servers.openfeature]
command = "npx"
args = ["-y", "@openfeature/mcp"]
Restart Codex CLI after saving.
Gemini CLIโ
Edit ~/.gemini/settings.json:
{
"mcpServers": {
"OpenFeature": {
"command": "npx",
"args": ["-y", "@openfeature/mcp"]
}
}
}
Restart Gemini CLI after saving.
Claude Desktopโ
Edit your Claude Desktop config at:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
Add the following configuration:
{
"mcpServers": {
"openfeature": {
"command": "npx",
"args": ["-y", "@openfeature/mcp"]
}
}
}
Restart Claude Desktop after saving.
Available Toolsโ
The OpenFeature MCP Server provides two main tools accessible to AI assistants:
SDK Installation Guide: install_openfeature_sdkโ
Fetches installation instructions for OpenFeature SDKs in various languages and frameworks. Optionally includes provider-specific setup documentation.
SDK Tool Parametersโ
| Parameter | Type | Required | Description |
|---|---|---|---|
technology | string | Yes | Target language/framework (see supported list below) |
providers | string[] | No | Provider identifiers to include installation instructions |
Supported Technologiesโ
The technologies list is built from the available prompts/*.md, updated automatically using scripts/build-prompts.js
| Technology | SDK |
|---|---|
android | Android Kotlin SDK |
dotnet | .NET SDK |
go | Go SDK |
ios | iOS Swift SDK |
java | Java SDK |
javascript | JavaScript Web SDK |
nestjs | NestJS SDK |
nodejs | Node.js SDK |
php | PHP SDK |
python | Python SDK |
react | React SDK |
ruby | Ruby SDK |
Supported Providersโ
The provider list is automatically sourced from the OpenFeature ecosystem (open-feature/openfeature.dev repo).
See scripts/build-providers.js for details on how the provider list is maintained.
OFREP Flag Evaluation: ofrep_flag_evalโ
Evaluate feature flags using the OpenFeature Remote Evaluation Protocol (OFREP). Supports both single flag and bulk evaluation.
OFREP Tool Parametersโ
| Parameter | Type | Required | Description |
|---|---|---|---|
base_url | string | No | Base URL of your OFREP-compatible flag service |
flag_key | string | No | Flag key for single evaluation (omit for bulk) |
context | object | No | Evaluation context (e.g., { targetingKey: "user-123" }) |
etag | string | No | ETag for bulk evaluation caching |
auth | object | No | Authentication configuration |
auth.bearer_token | string | No | Bearer token for authorization |
auth.api_key | string | No | API key for authorization |
OFREP Configurationโ
To use OFREP flag evaluation features, configure authentication and endpoint details. The server checks configuration in this priority order:
-
Environment Variables
OPENFEATURE_OFREP_BASE_URLorOFREP_BASE_URLOPENFEATURE_OFREP_BEARER_TOKENorOFREP_BEARER_TOKENOPENFEATURE_OFREP_API_KEYorOFREP_API_KEY
-
Configuration File:
~/.openfeature-mcp.json
Example ~/.openfeature-mcp.json:
{
"OFREP": {
"baseUrl": "https://flags.example.com",
"bearerToken": "<your-token>",
"apiKey": "<your-api-key>"
}
}
You can override the config file path using the OPENFEATURE_MCP_CONFIG_PATH environment variable.
Note: All logs are written to stderr. The MCP protocol messages use stdout.
MCP Usage Examplesโ
SDK Installation Exampleโ
"install the OpenFeature SDK for Node.js with the flagd provider"
The AI will use the MCP to fetch relevant installation instructions and attempt to install the OpenFeature SDK with the correct provider.
Flag Evaluation Exampleโ
When interacting with your AI assistant:
"Can you check the value of the 'new-checkout-flow' feature flag for 'user-123'?"
The AI will use the MCP to evaluate the flag using OFREP and provide you with the result, along with additional metadata like variant and reason.