NanoContext FAQs

Question 1

Is NanoContext compatible with popular AI development tools and agents?

Accepted Answer

Yes, NanoContext integrates seamlessly via its Model Context Protocol (MCP) server. It's compatible with tools like VS Code Copilot, Claude Code, Cursor, Windsurf, Gemini CLI, and Codex CLI, often with auto-generated configurations.

Question 2

What is NanoContext and how does it help AI agents?

Accepted Answer

NanoContext is a CLI tool that uses Tree-sitter AST parsing to create a structured, searchable index of your codebase. It provides AI agents with a 'map' of your project, enabling them to navigate, understand, and generate code more efficiently with reduced token usage.

Question 3

What kind of search capabilities does NanoContext offer?

Accepted Answer

NanoContext supports powerful search options including exact text matching, regex patterns, and semantic vector search across your code and project memories. It helps AI agents find relevant code, classes, methods, and concepts quickly.

Question 4

How does NanoContext reduce AI agent token usage?

Accepted Answer

Instead of agents reading entire files, NanoContext allows them to query a compact index for exact code ranges, method signatures, or relevant context. This drastically cuts down on tokens spent, lowers costs, and prevents hitting context window limits on large projects.

Question 5

Does NanoContext require an LLM or embedding provider to function?

Accepted Answer

NanoContext's core Tree-sitter AST parsing, exact text search, and regex search features work entirely offline without any LLM or embedding provider. Optional semantic vector search and AI-generated insights can be enabled by integrating with providers like Ollama or OpenAI.

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