Augment Code Alternatives: Context Engine Options for Claude Code, Cursor and Codex

The main alternatives to Augment's Context Engine are free local code graphs (CodeGraph, Graphify, GitNexus, Serena) that run beside your agent, and hosted indexes (Sourcegraph's MCP server, Greptile, repowise) that work wherever the agent runs. Pick local if your agent runs on your laptop and cost matters; pick hosted for cross-repo context or browser agents.

Prices and licenses checked on each vendor's page and GitHub repository on 6 October 2026. Disclosure: I build repowise.

What Augment's Context Engine actually is

Augment Code started as an AI coding assistant whose selling point was its retrieval: a semantic index of your codebase that decides which code the model gets to see. On 6 February 2026 Augment made that index available as an MCP server, so other agents can use it. MCP, the Model Context Protocol, is the standard way an agent like Claude Code or Cursor calls an outside tool.

It has two modes. In local mode you run Augment's Auggie CLI as an MCP server on your machine and it indexes your working directory in real time. In remote mode Augment hosts the index, installs a GitHub App, and re-indexes the default branch of selected repositories when commits land. Augment lists quickstarts for Claude Code, Cursor, GitHub Copilot, Codex, Gemini CLI, Zed, OpenCode, Kiro and others.

Augment's launch post reports that adding the Context Engine improved agent results by 70% or more, measured on 300 Elasticsearch pull requests with three prompts each, graded on correctness, completeness and code reuse. Those are Augment's own numbers on one repository, so I would read them as evidence that the retrieval works well there and expect the gain on your own code to differ.

The pricing needs a close look. Context Engine queries are billed by tokens at the model provider's rate plus a 40% service fee, and Augment's docs put the average at roughly $0.03 to $0.06 per query. The paid plans are $20/month and $100/month, flat for up to 50 seats, and each includes that same dollar amount of usage across models, the Context Engine and compute. An agent that makes 200 context queries in a working day would spend roughly $6 to $12 a day at that average, before any model usage. That figure is my own arithmetic from Augment's stated average, and I have not seen a real bill.

Why the agent's location decides most of this

Before comparing tools, work out where your agent runs, because that rules out half of them.

If it runs on your laptop (Claude Code, Cursor, Codex CLI), any local MCP server works, and the free tools below are good choices because they read your files directly and nothing leaves your machine.

If the agent runs on someone else's server (Claude.ai, ChatGPT, a cloud agent, a CI job), it cannot reach localhost. You need a hosted index with a public MCP address and proper sign-in. That rules out every local tool in the table, however good it is, and it is the main reason hosted context engines such as Augment's remote mode exist.

The second question is how many repositories one question touches. Local graphs index the folder you are in. If an answer needs your API repo, your frontend and a shared library, you want something that indexes several repos and answers across them.

Free local alternatives

CodeGraph (MIT, about 73,000 GitHub stars) builds a code knowledge graph with a Rust core and keeps it synced as files change. It ships integrations for Claude Code, Cursor, Codex, Gemini, OpenCode, Copilot and more, and promises fewer tokens and fewer tool calls. On our sealed retrieval benchmark (more below) it was the strongest open-source tool we tested, at 0.609 file coverage. Its author is building a hosted platform; the open-source CLI is fully local today.

Graphify (Apache-2.0, about 124,000 stars) runs as a /graphify skill inside your assistant. It parses code with tree-sitter into a graph with no model calls and no embeddings, tags every edge as extracted or inferred, and writes an HTML graph, a report and a JSON graph you can query. Docs, PDFs and images go through your assistant's model. It scored 0.571 on our benchmark.

GitNexus (about 48,000 stars) indexes dependencies, call chains and execution flows into a knowledge graph, installs agent skills and hooks, and writes AGENTS.md and CLAUDE.md files. Read the license before you adopt it at work: it is PolyForm Noncommercial 1.0.0, which does not allow commercial use without a separate agreement.

Serena (about 30,000 stars) takes a different route. Instead of building its own graph, it drives real language servers, the same engines your IDE uses for go-to-definition and find-references, and gives the agent symbol-level reading and editing tools. That makes it precise for "where is this used" questions and always current, since it reads the live files. The Serena application is GPL-3.0-or-later; its language-server client library is MIT.

None of these four tools gives you git history (who owns a file, what changes together, what changed recently), a view across more than one repo, or access from a browser agent. For many solo developers those gaps do not matter.

Hosted alternatives

Sourcegraph's MCP server exposes Sourcegraph's search to agents: keyword and natural-language code search, commit and diff search, go-to-definition, find-references and Deep Search, across every repository your Sourcegraph instance indexes. It supports OAuth sign-in, so Claude Code connects with one command. It is available on Enterprise plans, which makes it the natural choice if your company already runs Sourcegraph and an expensive one if it does not. See Sourcegraph alternatives for the wider picture.

Greptile's MCP server is built around Greptile's code review product. Its tools list pull requests and reviews, search Greptile's past review comments, manage custom review rules, and read a generated knowledge base per repository where that is enabled. It is useful if you already use Greptile for review and want your agent to see the same rules and history, but its focus is review, and code retrieval comes second.

repowise is what I work on. It parses the code into a dependency graph, reads git history for hotspots (files that change often and are complex), ownership and files that change together, writes a wiki on top, and serves all of it over MCP: an overview tool, context for a file or symbol, change risk, the reasons behind past decisions, semantic search and dead code. Self-hosted it is AGPL-3.0 and runs with no API key. Hosted, every repo gets an MCP address that works in Claude Code, Cursor, VS Code, and as a connector in Claude.ai, and Pro re-indexes private repos on every push for $15/month. Graph, git and health tools do not call a model, so a context query does not carry a per-token fee; get_answer uses a model and draws from Pro's monthly $5 of credits.

How the open-source tools did on a retrieval benchmark

In August we published a retrieval benchmark on ContextBench, a public set of real coding tasks where the files an agent needs are known. We split the 112 tasks into 70 for development and 42 sealed, and scored file coverage: what share of the needed files each tool returned.

We came last on that first run and published the result. After fixing a query-time bug, repowise scored 0.876 on the 42 sealed tasks it had never been tuned on, against CodeGraph's 0.6095. The whole story, including the parts that still look bad, is in we benchmarked ourselves and came last.

Augment, Sourcegraph and Greptile were not in that run, so this table says nothing about them. Retrieval coverage also measures only one part of a good agent result, since an agent can find the right files and still write the wrong fix.

How to choose

• If you work alone, your agent runs on your laptop and cost matters, start with CodeGraph or Graphify. Add Serena if your agent makes a lot of symbol-level edits.
• For commercial use, check licenses first: GitNexus is noncommercial, and Serena's GPL terms matter if you redistribute it.
• If you already pay for Sourcegraph Enterprise or Greptile, use their MCP servers before buying anything new.
• If you want Augment's semantic retrieval and accept usage billing, the Context Engine is a reasonable choice, and you should cap usage per seat.
• If you need context in Claude.ai or a cloud agent, across several repos, with history and ownership, you need a hosted index. That is where I would put repowise, and you can try it free on any public repo.

For a wider buyer's view of this category, see the repository intelligence buyer's guide, and for single-tool comparisons the CodeGraph, Graphify and Serena alternative pages.

How we checked

On 6 October 2026 I read Augment's pricing page, its Context Engine MCP docs and its February launch post; Sourcegraph's MCP documentation; Greptile's MCP tool reference; and the README, license file and GitHub metadata of each open-source tool. Star counts are rounded and move daily. The benchmark numbers come from our published ContextBench run in August 2026; its raw data is public and linked from that post. I did not run Augment's Context Engine, so I make no claim about its retrieval quality beyond quoting Augment's own evaluation.