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open-code-review/ROADMAP.md
kite 07b41bad79 docs(roadmap): mark MCP as shipped and add delegate mode 
Move MCP server to the current-state list now that it is supported, and
replace the MCP roadmap entry with a delegate mode that lets ocr run on
the host coding agent's subscription without a standalone LLM endpoint.
2026-07-09 13:42:45 +08:00

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Roadmap

This document describes the planned direction for OpenCodeReview over the next year. It is a living document and will be updated as priorities evolve.

Feedback is welcome via GitHub Discussions or Issues.

Current State (Mid-2026)

OpenCodeReview currently provides:

  • A CLI tool (ocr) for AI-powered code review with deterministic engineering and agent hybrid architecture.
  • Integration with coding agents: Claude Code (plugin/skill), Codex (plugin), and Cursor (plugin).
  • A VSCode extension for in-editor code review.
  • CI/CD integration (GitHub Actions, GitLab CI, etc.).
  • Multi-provider LLM support (OpenAI-compatible, Anthropic, Google Gemini, Amazon Bedrock, Azure OpenAI, etc.).
  • MCP server — expose OpenCodeReview over the Model Context Protocol so review capabilities can be invoked from any MCP-compatible client.
  • Review rules engine with per-file pattern matching.
  • Multi-language documentation (English, Chinese, Japanese, Korean, Russian).

Planned — H2 2026

IDE Plugins

  • JetBrains plugin — Bring AI code review to IntelliJ IDEA, GoLand, PyCharm, and other JetBrains IDEs with the same capabilities as the existing VSCode extension.

Delegate Mode

  • Subscription-friendly review — An opt-in mode where ocr no longer depends on a separately-configured LLM endpoint. Instead of calling an LLM itself, ocr resolves the review scope, applies excludes, loads review rules, injects background context, and collects the diffs, then hands that off as a structured review task for the host coding agent (e.g. Claude Code) to execute using its own agent loop and included subscription usage — removing the need for a standalone API key.

Ultra Mode

  • Higher-recall review mode — An opt-in mode that trades increased token consumption and review time for significantly higher issue recall rate. Designed for security-sensitive or high-risk changesets where thoroughness is more important than speed.

Planned — H1 2027

Domain-Specific Long-Term Memory

  • Persistent review knowledge — Enable the review engine to accumulate domain-specific knowledge over time (recurring patterns, past review decisions, project-specific conventions) and apply it to future reviews, improving relevance and reducing repeated feedback.

Not Planned

The following are explicitly out of scope for the foreseeable future:

  • Automated code fixing without human review — OCR is a review tool, not an auto-fix tool. While it can suggest fixes, applying changes always requires human approval.
  • General-purpose AI coding assistant — OCR focuses exclusively on code review. Features like code generation, refactoring, or chat-based coding assistance are not planned.
  • Self-hosted LLM bundling — OCR connects to external LLM providers but does not bundle or host models itself.