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DevCycle MCP Getting Started

The DevCycle Model Context Protocol (MCP) Server is based on the DevCycle CLI and enables AI coding tools like Claude Code and Cursor, or general-purpose tools like Claude Desktop, to interact directly with your DevCycle projects and make changes on your behalf.

Quick Setup​

The DevCycle MCP is hosted so there is no need to set up a local server. We'll walk you through installation and authentication with your preferred AI tools.

Direct Connection: For clients that natively support the MCP specification with OAuth authentication, you can connect directly to our hosted server:

https://mcp.devcycle.com/mcp

Protocol Support: Our MCP server supports both SSE and HTTP Streaming protocols, automatically negotiating the best option based on your client's capabilities.

Alternative Endpoint: If your client has issues with protocol negotiation, use the SSE-only endpoint:

https://mcp.devcycle.com/sse

MCP Registry: If you're using registry.modelcontextprotocol.io, the DevCycle MCP is listed as: com.devcycle/mcp

info

These instructions use the remote DevCycle MCP server. For installation of the local MCP server, see the reference docs.


Configure Your AI Client​

Step 1: Add DevCycle MCP Server

Run the following command in your terminal:

claude mcp add --transport http devcycle https://mcp.devcycle.com/mcp

Step 2: Manage MCP Connection

Start Claude Code and enter the MCP management interface:

/mcp

Step 3: Authentication

You'll see the DevCycle server listed as "Needs authentication":

  1. Select the DevCycle server and press Enter to authenticate
  2. This will open a browser page at mcp.devcycle.com for authorization
  3. Review and click "Allow Access" to grant permissions
  4. If you have multiple organizations, select your desired organization at auth.devcycle.com
  5. Return to Claude Code where the server will show as connected

For more details, see the Claude Code MCP documentation.


Available Tools​

The DevCycle MCP Server provides comprehensive feature flag management tools organized into 6 categories:

CategoryToolsDescription
Feature Managementlist_features, create_feature, update_feature, update_feature_status, delete_feature, cleanup_feature, get_feature_audit_log_historyCreate and manage feature flags
Variable Managementlist_variables, create_variable, update_variable, delete_variableManage feature variables
Project Managementget_current_project, select_projectProject selection and details
Self-Targeting & Overridesget_self_targeting_identity, update_self_targeting_identity, list_self_targeting_overrides, set_self_targeting_override, clear_feature_self_targeting_overridesTesting and overrides
Results & Analyticsget_feature_total_evaluations, get_project_total_evaluationsUsage analytics
SDK Installationinstall_devcycle_sdkSDK install guides and examples

Try It Out​

Once configured, try asking your AI assistant:

  • "Create a new feature flag called 'new-checkout-flow'"
  • "List all features in my project"
  • "Enable targeting for the header-redesign feature in production"
  • "Show me evaluation analytics for the last 7 days"

Next Steps​

Getting Help​