Bazel

The AgentOps MCP server provides access to observability and tracing data for debugging complex AI agent runs. This adds crucial context about where the AI agent succeeds or fails.

Enables Docker container management with tools for listing, running, stopping, removing containers and pulling images from registries through a TypeScript-based interface

Integrates with web search APIs and crawling tools to enable internet-wide information retrieval, content extraction, and data mining capabilities for research and analysis tasks.

Provides browser automation capabilities through a simple API, enabling execution of web tasks using natural language instructions

Store and query structured data in local knowledge graphs.

Context Engineer MCP is an IDE-agnostic orchestration layer that eliminates context loss when working with AI coding agents. It automatically analyzes your local codebase, generates structured documentation (PRDs, epics, stories, tech specs, and diagrams), and feeds it back into your agents. This ensures better planning, cleaner implementations, and scalable feature development—without the chaos of fragmented context across tools.