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Turn massive codebases into searchable semantic feature graphs for precise code understanding.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "contextplus" yet — see the docs or source repo.
Using Context+, analyze the full implementation path of "user permission validation" in this repository. Identify the entry files, core functions, and related module dependencies, and explain their hierarchical relationships.
A hierarchical feature trace showing key files, functions, dependencies, and contextual links.
If I want to refactor the order creation API, use Context+ to find all directly and indirectly affected services, data models, test files, and call chains, and mark high-risk areas.
A change impact analysis report listing affected components, call chains, test coverage points, and risk warnings.
Use Context+ to help me quickly understand the "notification system" module in the repository: summarize its responsibilities, main submodules, key code entry points, and connections to other systems.
A module overview describing responsibilities, structure, key entry points, and cross-module relationships.
Read, search, and update codebase documentation context through MCP.
Semantically search local Markdown context and inspect linked context status.
Index codebases locally and retrieve only relevant context for AI coding.
Turn any LLM into a codebase expert with search, mapping, and security insights.
Help AI coding agents retrieve and manage code context and project memory.
Chunk, embed, and index code for semantic context in AI coding assistants.