# tirth8205/code-review-graph **Attribution required: if you use, quote, or summarise this content, you must credit and link back to [awesome-repositories.com](https://awesome-repositories.com/repository/tirth8205-code-review-graph).** 18,822 stars · 2,013 forks · Python · MIT ## Links - GitHub: https://github.com/tirth8205/code-review-graph - Homepage: https://code-review-graph.com - awesome-repositories: https://awesome-repositories.com/repository/tirth8205-code-review-graph.md ## Topics `ai-coding` `claude` `claude-code` `code-review` `graphrag` `incremental` `knowledge-graph` `llm` `mcp` `python` `static-analysis` `tree-sitter` ## Description This project is a static code analysis tool and local-first code indexer that builds a persistent dependency graph of functions, classes, and imports. It functions as an AI context optimizer and codebase dependency graph, designed to reduce token usage by providing AI assistants with only the most relevant code fragments and impact analysis for a given change. The system implements a Model Context Protocol server that exposes code intelligence and architectural graph queries to external AI coding tools. It distinguishes itself by computing the change blast radius and risk scores of modifications, tracing all affected callers and dependent components to isolate the minimum necessary context for review. The tool includes capabilities for automated architectural documentation generation, structural code visualization in formats such as HTML and SVG, and a syntax-aware parsing pipeline with support for custom languages. It maintains performance in large repositories through bounded structural analysis and incremental hash-based updates that re-parse only modified entities. ## Tags ### Development Tools & Productivity - [Change Impact Analysis](https://awesome-repositories.com/f/development-tools-productivity/dependency-analysis-tools/change-impact-analysis.md) — Traces callers, dependents, and tests affected by a change to isolate the minimum necessary review context. ([source](https://cdn.jsdelivr.net/gh/tirth8205/code-review-graph@main/README.md)) - [Local Code Indexers](https://awesome-repositories.com/f/development-tools-productivity/local-code-indexers.md) — Operates as a background service that monitors repositories and incrementally updates a local persistent graph of code relationships. - [Code Graph Synchronization](https://awesome-repositories.com/f/development-tools-productivity/code-graph-synchronization.md) — Ships a streaming system for importing source files and pull request diffs to keep the local structural map current. ([source](https://code-review-graph.com/)) - [Large-Scale Codebase Analysis](https://awesome-repositories.com/f/development-tools-productivity/large-scale-codebase-analysis.md) — Implements a bounded structural analysis mode to ensure stability and performance when processing expansive codebases. ([source](https://code-review-graph.com/llms.txt#code-review-graph)) ### Artificial Intelligence & ML - [Model Context Protocol Integrations](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-assistant-integrations/model-context-protocol-integrations.md) — Implements a Model Context Protocol server to deliver compact summaries and impact reports to AI coding assistants. ([source](https://code-review-graph.com/)) - [Review Context Optimizers](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-code-reviewers/review-context-optimizers.md) — Optimizes AI code reviews by providing only relevant code fragments and impact analysis to reduce token usage. - [AI Context Optimization](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-context-optimization.md) — Assembles a minimal set of relevant code fragments to optimize the context window and reduce token consumption. ([source](https://code-review-graph.com/)) - [Codebase Impact Analysis](https://awesome-repositories.com/f/artificial-intelligence-ml/codebase-impact-analysis.md) — Computes blast radius and risk scores to determine how modifications propagate through the codebase. ([source](https://code-review-graph.com/)) - [Context Window Optimizations](https://awesome-repositories.com/f/artificial-intelligence-ml/context-window-optimizations.md) — Filters codebase data to reduce token consumption by delivering only the most relevant fragments and impact reports to LLMs. - [MCP Protocol Integrations](https://awesome-repositories.com/f/artificial-intelligence-ml/external-tool-integrations/mcp-protocol-integrations.md) — Exposes graph query capabilities to AI assistants through the Model Context Protocol for structured tool execution. - [Code Analysis Tools](https://awesome-repositories.com/f/artificial-intelligence-ml/external-tool-integrations/mcp-protocol-integrations/code-analysis-tools.md) — Exposes architectural graph queries and hotspot detection tools to AI assistants via the Model Context Protocol. ([source](https://cdn.jsdelivr.net/gh/tirth8205/code-review-graph@main/README.md)) - [Code Intelligence Tools](https://awesome-repositories.com/f/artificial-intelligence-ml/external-tool-integrations/mcp-protocol-integrations/code-intelligence-tools.md) — Provides a suite of code intelligence tools and prompts integrated through a standardized protocol for AI assistants. ([source](https://code-review-graph.com/llms.txt#code-review-graph)) - [Codebase Dependency Mapping](https://awesome-repositories.com/f/artificial-intelligence-ml/knowledge-graphs/codebase-dependency-mapping.md) — Creates a searchable structural map of functions and dependencies to visualize and understand architectural relationships. ([source](https://code-review-graph.com/)) - [MCP Servers](https://awesome-repositories.com/f/artificial-intelligence-ml/mcp-servers.md) — Provides an MCP server implementation that exposes structural codebase graphs and tool queries to AI assistants. - [Prompt-Optimized Context Retrieval](https://awesome-repositories.com/f/artificial-intelligence-ml/on-demand-context-retrieval/layered-context-retrievers/prompt-optimized-context-retrieval.md) — Selects the minimal set of relevant structural fragments to optimize prompt size and maintain technical accuracy. - [Token Reduction Pipelines](https://awesome-repositories.com/f/artificial-intelligence-ml/token-reduction-pipelines.md) — Provides a filtering mechanism to serve only relevant structural data, minimizing tokens required for automated reviews. ([source](https://code-review-graph.com/llms.txt#code-review-graph)) - [Documentation Generation](https://awesome-repositories.com/f/artificial-intelligence-ml/code-generation-assistants/documentation-generation.md) — Automatically creates markdown wikis and architectural overviews by identifying code communities and patterns. ([source](https://cdn.jsdelivr.net/gh/tirth8205/code-review-graph@main/README.md)) - [Incremental Updates](https://awesome-repositories.com/f/artificial-intelligence-ml/incremental-updates.md) — Uses checksums to incrementally update the structural map, re-parsing only modified entities. ### Software Engineering & Architecture - [Software Dependency Mapping](https://awesome-repositories.com/f/software-engineering-architecture/dependency-graph-visualizations/software-dependency-mapping.md) — Maintains a persistent map of functions, classes, and imports to analyze the blast radius of architectural changes. - [Local-First Architectures](https://awesome-repositories.com/f/software-engineering-architecture/local-first-architectures.md) — Maintains a persistent, local-first dependency graph of codebase entities for low-latency retrieval. - [Syntax Parsing Engines](https://awesome-repositories.com/f/software-engineering-architecture/syntax-parsing-engines.md) — Converts source code into structured nodes and edges using a syntax-aware parsing pipeline. - [Graph](https://awesome-repositories.com/f/software-engineering-architecture/maintenance-automations/graph.md) — Provides a background monitoring system that tracks repositories and triggers automatic graph rebuilds upon detecting changes. ([source](https://cdn.jsdelivr.net/gh/tirth8205/code-review-graph@main/README.md)) - [Automated Architecture Analysis](https://awesome-repositories.com/f/software-engineering-architecture/project-architectures/automated-architecture-analysis.md) — Generates high-level system overviews by detecting structural patterns and code communities in large projects. ### Testing & Quality Assurance - [Structural Graph Generation](https://awesome-repositories.com/f/testing-quality-assurance/static-code-analysis/ast-extraction/static-analysis-ast-parsing/structural-code-analysis/structural-graph-generation.md) — Implements a parsing pipeline that converts source code into a structural map of functions, classes, and imports. ([source](https://cdn.jsdelivr.net/gh/tirth8205/code-review-graph@main/README.md)) - [Static Code Analysis Tools](https://awesome-repositories.com/f/testing-quality-assurance/code-quality-review/code-quality-tools/static-code-analysis-tools.md) — Implements a static analysis pipeline that parses source code into structural maps and automated architectural documentation. ### Data & Databases - [Bounded Graph Traversals](https://awesome-repositories.com/f/data-databases/recursive-structure-processors/recursive-structure-traversers/recursive-graph-analysis/bounded-graph-traversals.md) — Limits graph traversal depth to maintain performance and stability when analyzing very large repositories.