A semantic code intelligence layer that plugs into any MCP-compatible AI coding agent to boost code quality by up to 80%.
Context Engine MCP exposes Augment's proprietary semantic indexing and deep codebase understanding to any AI coding tool through the Model Context Protocol. It provides intelligent code search that understands meaning rather than just text, indexing how files connect across repositories, services, and architectures while incorporating commit history and codebase patterns. The product operates in Local mode for active development and Remote mode for cross-repo context. Benchmark testing on 300 Elasticsearch PRs showed quality improvements of up to 80% for Claude Code and 71% for Cursor when paired with the Context Engine.
Enhancing existing AI coding tools with deep codebase context
Reducing token consumption and improving output quality
Enabling cross-repository semantic code search
Providing consistent understanding across heterogeneous AI tool environments
2x faster task completion through instant contextual retrieval
Up to 80% quality improvement in AI-generated code
Reduced token consumption
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