MCP Servers
The open registry for Model Context Protocol servers. Find the right tools, resources, and prompts for your AI agents — filtered by category, transport, or use case.
Servers
177
Tools
471
Categories
11
Contributors
155
Provides AI agents with access to PostHog product analytics through the Model Context Protocol. Enables querying events, analyzing funnels, inspecting feature flags, and reviewing session recordings metadata. Supports HogQL queries for advanced analytics and cohort analysis for user segmentation.
Official LaunchDarkly MCP server for feature management. Lets AI agents create and toggle feature flags, manage targeting rules and segments, and inspect flag status across environments. Useful for progressive delivery, kill switches, experimentation, and automating flag lifecycle from an AI assistant.
GrowthBook's official MCP server for working with feature flags, experiments, and metrics so agents can safely support product experimentation workflows.
Skills vs MCP servers
what’s the difference?Skillsthe “what to do”
A skill packages know-how — instructions, an example prompt, and recommended models — so an agent performs a task consistently. Skills add knowledge, not new connections.
MCP serversthe “how to connect”
An MCP server gives an agent new capabilities by connecting it to real systems (databases, APIs, files) over a transport. MCP adds connections and actions, not task instructions.
Rule of thumb: reach for a skill when you need the model to do a task well, and an MCP server when you need it to reach a tool or system. They compose — a skill can rely on tools an MCP server provides.
Built an MCP server?
Submit it to the registry — it’s open source and community-maintained.