OpenFeature MCP Server
OfficialProvides OpenFeature SDK installation guidance for various programming languages and enables feature...
- Click the "Install Now" button to open the FastMCP connection interface (the place where the MCP server connection and environment variables are configured).
- In the FastMCP connection interface find the environment / secrets section and add the OFREP endpoint URL: set OPENFEATURE_OFREP_BASE_URL (or OFREP_BASE_URL) to the base URL provided by your OFREP-compatible flag service (e.g., https://flags.example.com). (openfeature.dev)
- Obtain a bearer token or API key from your flag management system: sign in to your flag provider → open Account / API / Integrations / Service tokens → create a new token (give it only the permissions needed for flag evaluation) → copy the token.
- If the provider issues a bearer token, paste it into OPENFEATURE_OFREP_BEARER_TOKEN (or OFREP_BEARER_TOKEN).
- If the provider issues an API key, paste it into OPENFEATURE_OFREP_API_KEY (or OFREP_API_KEY). (openfeature.dev)
- If the FastMCP interface accepts inline auth fields for an individual call, you may instead provide the token there (auth.bearer_token or auth.api_key) for one-off tests; otherwise prefer the environment variables above so the MCP can use them for all calls. (glama.ai)
- (Optional) Instead of environment variables, you can create a local config file at ~/.openfeature-mcp.json with the OFREP settings and point the MCP to it with OPENFEATURE_MCP_CONFIG_PATH. Example file contents:
{
"OFREP": {
"baseUrl": "https://flags.example.com",
"bearerToken": "",
"apiKey": ""
}
} (openfeature.dev) - Save the FastMCP connection settings in the interface. Use the MCP's OFREP flag-evaluation tool (ofrep_flag_eval) or run a small test evaluation to confirm the base URL and token/api key are correct. If the test fails, verify the exact endpoint and token permissions in your flag provider's docs. (openfeature.dev)
- Secure the credentials: treat tokens/API keys as secrets (do not commit them to source control). If available, store them in your platform’s secrets manager and reference them from FastMCP rather than pasting into plaintext fields.
Quick Start
Choose Connection Type for
Authentication Required
Please sign in to use FastMCP hosted connections
Run MCP servers without
local setup or downtime
Access to 1,000+ ready-to-use MCP servers
Skip installation, maintenance, and trial-and-error.
No local setup or infra
Run MCP servers without Docker, ports, or tunnels.
Always online
Your MCP keeps working even when your laptop is off.
One secure URL
Use the same MCP from any agent, anywhere.
Secure by default
Encrypted connections. Secrets never stored locally.
Configuration for
Environment Variables
Please provide values for the following environment variables:
HTTP Headers
Please provide values for the following HTTP headers:
started!
The MCP server should open in . If it doesn't open automatically, please check that you have the application installed.
Copy and run this command in your terminal:
Make sure Gemini CLI is installed:
Visit Gemini CLI documentation for installation instructions.
Make sure Claude Code is installed:
Visit Claude Code documentation for installation instructions.
Installation Steps:
Configuration
Installation Failed
More for API Development
View All →Sentry
Streamline Sentry API integration with this remote MCP server middleware prototype. sentry-mcp acts as a bridge between clients and Sentry, supporting flexible transport methods and offering tools like the MCP Inspector for easy service testing. Inspired by Cloudflare’s remote MCP initiative, it helps developers adapt and debug workflows, making Sentry interaction smoother for both cloud and self-hosted environments.
More for Developer Tools
View All →
GitHub
Extend your developer tools with the GitHub MCP Server—a powerful Model Context Protocol server enhancing automation and AI interactions with GitHub APIs. It supports diverse functionalities like managing workflows, issues, pull requests, repositories, and security alerts. Customize available toolsets to fit your needs, enable dynamic tool discovery to streamline tool usage, and run the server locally or remotely. With read-only mode and support for GitHub Enterprise, this server integrates deeply into your GitHub ecosystem, empowering data extraction and intelligent operations for developers and AI applications. Licensed under MIT, it fosters flexible and advanced GitHub automation.
Desktop Commander
Desktop Commander MCP transforms Claude Desktop into a powerful AI assistant for managing files, running terminal commands, and editing code with precision across your entire system. It supports in-memory code execution, interactive process control, advanced search and replace, plus comprehensive filesystem operations including reading from URLs and negative offset file reads. With detailed audit and fuzzy search logging, it enables efficient automation, data analysis, and multi-project workflows—all without extra API costs. Designed for developers seeking smarter automation, it enhances productivity by integrating all essential development tools into a single, intelligent chat interface.
Chrome DevTools
Provides direct Chrome browser control through DevTools for web automation, debugging, and performance analysis using accessibility tree snapshots for reliable element targeting, automatic page event handling, and integrated performance tracing with actionable insights.
FreeCAD
Enables AI-driven CAD modeling by providing a remote procedure call (RPC) server that allows programmatic control of FreeCAD, supporting operations like creating documents, inserting parts, editing objects, and executing Python code for generative design workflows.