Every tool, one connection - for the whole team.

Developer-tools MCPs connect your AI workspace to the APIs, services, and platforms your team already uses to ship software. You reach for these when you want an LLM to pull data from a project-management tool, trigger a deployment pipeline, query logs, or interact with a third-party service without writing custom integration code. The key technical differentiator is how many endpoints the MCP exposes and whether it handles authentication transparently or requires manual token management. Choose based on two factors: coverage and auth friction. A narrow MCP that wraps three endpoints might be perfect if those three are all you need. A broad one that surfaces dozens of methods pays off when your use cases evolve. If the MCP requires you to paste API keys into every conversation, it will slow your team down; look for options that store credentials once and reuse them across sessions.