octocode

Code research platform for AI agents; find, understand, and prove context across your code and all of GitHub, in a fraction of the tokens. One toolset, MCP or C

What is octocode?

Code research platform for AI agents; find, understand, and prove context across your code and all of GitHub, in a fraction of the tokens. One toolset, MCP or CLI

Overview of octocode

What it is

Octocode is an evidence-first code research platform for AI agents and developers. It researches local code and external code (GitHub repositories, PRs, npm) with one toolset: ripgrep + AST search, trees, precise reads, and LSP. It can be used as a CLI or MCP server, backed by a Rust engine for fast, token-efficient results across single files or mega-repos.

Key features

  • Agent-driven, efficient flows: chains cheap steps into an optimized research flow with smart pagination and minification, so the model never over-fetches.
  • Scales to monorepos: spot a pattern in one repository, follow the PR that introduced it, then trace it across other repositories and local files.
  • Smart GitHub flow: parallel bulk queries across code, PRs, commits, issues, and repositories with the same search-broad, read-narrow discipline.
  • Works without GitHub: clone any repository and point local tools (search, AST, LSP, content) at it.
  • Reads shape, not noise: on-the-fly minify/skeletonize across 70+ languages.
  • Fast, self-contained: search, parsing, navigation, and redaction run in one prebuilt Rust engine.
  • Safe by default: every byte to the model is scanned and secrets redacted first.

Use cases

  • Codebase questions: search local or GitHub code, read exact regions, browse trees, and carry file/line anchors into the answer.
  • Implementation research: compare patterns across repositories, npm packages, pull requests, commits, and local files before changing code.
  • Semantic navigation: resolve definitions, references, callers/callees, call hierarchy, hovers, symbols, diagnostics, and type relationships through LSP.
  • Structural matching: run AST-shaped searches with patterns or YAML rules so comments and strings do not become false positives.
  • Large-file context: minify, skeletonize, or paginate code so agents spend tokens on relevant structure instead of boilerplate.
  • Agent workflows: same engine through MCP, CLI, and Agent Skills.

Getting started

Prerequisites: Node.js 20.12+ Run the Octocode CLI with npx: npx octocode --help Authenticate with GitHub (optional, but unlocks private repositories and higher API rate limits): npx octocode auth login npx octocode status Choose your interface: CLI: npx octocode MCP: add to your MCP client config (or use one-click install options in the repository README).

License and pricing

The license is MIT. The project is open source.

Based on the project's public README and repository metadata.

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