claude-context vs code-review-graph
Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.
Open source · MIT
Semantic code search server that lets Claude Code and other AI agents pull relevant code from a whole repo.
Open source · MIT
Builds a local map of your codebase so AI coding tools read only the files a change touches.
The short answer
Choose claude-context if you need…
- Developers working in large codebases where loading everything into an agent's context is impractical
- People already using Claude Code, Cursor, Gemini CLI, Codex CLI or similar MCP-compatible agents
- Teams comfortable creating OpenAI and Zilliz Cloud accounts and managing API keys
Choose code-review-graph if you need…
- Developers who use an MCP-compatible AI coding assistant on a large repository
- Teams that want code reviews to focus on the files a change affects
- People who want the code map kept local rather than sent to a hosted service
- Users of supported tools such as Claude Code, Cursor or Codex who want automatic setup
Side-by-side
| claude-context | code-review-graph | |
|---|---|---|
| Type | Dev tool | Dev tool |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 12.7k | 32.6k |
| Setup difficulty | Beginner | Beginner |
| How you get it | Install with a package manager | Install with a package manager |
| Main language | TypeScript | Python |
| Last code update | 4 months ago | 8 days ago |
What each one is
claude-context
Claude Context is an MCP plugin that adds semantic code search to Claude Code and other AI coding agents. It indexes your codebase into a vector database so the agent can find relevant code by meaning and load only that code into its context, instead of loading whole directories on every request. It uses an OpenAI embedding model and a Zilliz Cloud (Milvus) vector database.
code-review-graph
code-review-graph is a Python tool that scans a code repository with Tree-sitter and stores a graph of its functions, classes, imports and calls in a local database. AI coding assistants connected to it through MCP can then ask for a small set of relevant files instead of reading the whole project. The README says this is aimed at reducing the context an assistant needs during code reviews and on large repositories.
Best for
claude-context
- Developers working in large codebases where loading everything into an agent's context is impractical
- People already using Claude Code, Cursor, Gemini CLI, Codex CLI or similar MCP-compatible agents
- Teams comfortable creating OpenAI and Zilliz Cloud accounts and managing API keys
code-review-graph
- Developers who use an MCP-compatible AI coding assistant on a large repository
- Teams that want code reviews to focus on the files a change affects
- People who want the code map kept local rather than sent to a hosted service
- Users of supported tools such as Claude Code, Cursor or Codex who want automatic setup
Strengths
claude-context
- Uses semantic search, so it can find relevant code without the agent doing many rounds of file discovery
- Setup is a single configuration entry for each supported MCP client, documented in the README
- MIT licensed and actively maintained, with a large user base by star count
code-review-graph
- Runs locally and stores the graph in a local database (SQLite, per the README's pipeline diagram)
- One install command configures many AI coding tools and reports which were detected
- Incremental updates re-parse only files whose SHA-256 hash changed, per the README
Not ideal for
claude-context
- People who want a fully local setup, since the README describes OpenAI embeddings and a Zilliz Cloud vector database rather than a local option
- Small projects where the agent can already read all the code without search
- Anyone unwilling to send code embeddings to third-party services
code-review-graph
- Projects in languages outside the supported list, since parsing coverage is limited to the listed languages
- Users who do not use an MCP-compatible AI tool, since the main interface is through MCP
- Anyone expecting the token savings to hold exactly, since the README's numbers come from one 2026-08-02 snapshot and it says the repository has grown since
Trade-offs
claude-context
- Requires paid-or-signup accounts for an OpenAI API key and a Zilliz Cloud vector database, so ongoing costs and a third-party dependency are involved
- Code is sent to external embedding and vector services; review your privacy requirements before use
- The README is truncated here, so details on indexing behavior, limits and pricing are not confirmed in this analysis
code-review-graph
- The token-reduction figures are from a single snapshot and the README says current numbers are larger
- Parsing is limited to the listed languages, with fallbacks where no Tree-sitter grammar exists
- Requires Python 3.10 or newer and depends on MCP-compatible tools to be useful
Getting started
claude-context
Add the MCP server to Claude Code
claude mcp add claude-context -e OPENAI_API_KEY=sk-your-openai-api-key -e MILVUS_ADDRESS=your-zilliz-cloud-public-endpoint -e MILVUS_TOKEN=your-zilliz-cloud-api-key -- npx @zilliz/claude-context-mcp@latestcode-review-graph
Install from PyPI
pip install code-review-graphConfigure detected AI coding tools
code-review-graph installFrequently asked questions
What is the difference between claude-context and code-review-graph?
claude-context: Semantic code search server that lets Claude Code and other AI agents pull relevant code from a whole repo. code-review-graph: Builds a local map of your codebase so AI coding tools read only the files a change touches. claude-context suits developers working in large codebases where loading everything into an agent's context is impractical, while code-review-graph suits developers who use an mcp-compatible ai coding assistant on a large repository.
Are claude-context and code-review-graph free?
claude-context: Free and open source. code-review-graph: Free and open source.
Is claude-context or code-review-graph more popular?
code-review-graph has more GitHub stars (32.6k) than claude-context (12.7k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to claude-context and code-review-graph?
Other options people compare them with include codebase-memory-mcp, wshobson/agents, Botpress, Desktop Commander, Portkey AI Gateway.
Keep comparing
Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.