Augment Code Alternative: MCP Graph Context

This page is for teams already sold on the idea that an agent needs real code context beyond a bigger prompt, and who are now comparing Augment Code's Context Engine against a more graph-forward approach. Augment is the closest architectural neighbor Symvanta has, so the comparison is narrower and more useful than most. For the wider category, see code graph MCP servers compared.

Where the two products actually differ

Augment's Context Engine maintains what Augment describes as a live understanding of a codebase: semantic search over the code, mapping of how files and services connect, indexed commit history, codebase patterns, docs and tickets, and what Augment calls tribal knowledge (Context Engine). That understanding feeds retrieval. The documented MCP surface is a retrieval tool, named codebase-retrieval in Augment's own quickstart, which hands the agent relevant code for a question (Claude Code quickstart). As of September 2026, Augment's public docs describe retrieval and relationship mapping; they do not document direct graph-traversal operations such as "find every caller of this function" or "compute this symbol's blast radius" as callable MCP tools.

Symvanta builds the same kind of graph (nodes are symbols, edges are calls, imports, implements, and instantiates) and then exposes it as first-class MCP tools: relate with callers, dependencies, blast_radius, implementers, heritage, and chain modes, plus find_node for symbol resolution, find_http_route for HTTP handlers, and diff_impact for change sets (Symvanta MCP tools). An agent does not get a pre-fetched context bundle assembled on Symvanta's side; it walks the graph itself, one traversal at a time, and can ask a second, more specific question if the first answer is not enough. Embeddings and text search sit alongside the graph for the cases where semantic or literal matching is the right tool.

That difference matters most exactly where code embeddings vs. code graph draws the line: embeddings are excellent at "find code that looks like this," and weaker at "tell me everything that would break if I change this," because relatedness in vector space is not the same thing as an edge in a call graph. It is also the pattern behind why AI coding agents fail on large codebases: retrieval that returns a plausible chunk still leaves the agent guessing about what is actually connected to it.

Pricing, as of September 2026

Augment's pricing page now lists three plans, all flat, with no per-seat charge (Augment Code pricing, checked 2026-09-21):

• Standard: $20/month with $20 of usage included, up to 50 seats.
• Business: $100/month with $100 of usage included, up to 50 seats.
• Enterprise: custom pricing, unlimited users, custom usage limits, and volume-based annual discounts.

Usage is measured in dollars across LLM tokens, the Context Engine, and compute, and the included amount is pooled across the team. LLM tokens are billed at the model provider's public API list price, and Augment adds a flat 40% service fee on LLM usage. There is no service fee on compute; Cosmos compute is billed at $0.19 per hour in 5-minute increments (Token-based pricing). Included usage resets each month and does not roll over, and usage beyond the pool continues pay-as-you-go at the same rates without a manual top-up.

One clarification if you have seen a $20/month individual plan in older roundups: the current $20 plan is Standard, a flat team plan with up to 50 seats and $20 of pooled usage. The plan generation has changed, so check the pricing page for exactly what each tier includes today rather than trusting a remembered number.

Symvanta pricing is per seat: Starter at $19/month for one seat, Pro at $29 per seat/month with a 7-day trial, and Enterprise at $99 per seat/month with a 15-seat minimum. The practical difference shows up at the margins: Augment's flat $20 or $100 pool is attractive for a team with predictable usage, and per-person cost then depends on how fast the shared pool burns, since LLM usage beyond it carries the 40% fee. A per-seat model is easier to forecast for a team that just wants to know what next month's bill looks like.

Deployment and MCP

Augment runs as cloud SaaS with two documented MCP modes (Context Engine MCP docs):

• Local server. Runs the Auggie CLI on the developer's machine, indexes the working directory in real time, and exposes the codebase-retrieval tool over stdio. Local edits are reflected immediately, with no manual sync.
• Remote server. Hosted by Augment over HTTP and connected through the Augment GitHub App. It indexes the selected repositories' default branches and provides cross-repo context, updating automatically when commits land on the default branch. The GitHub App supports GitHub Enterprise Cloud and github.com, with GitHub Enterprise Server as an enterprise-only feature (Augment GitHub App). GitLab, Bitbucket, and documentation-site indexing live in Context Connectors, which Augment labels an experimental open-source library built on its SDK, not a hosted Remote MCP feature (Context Connectors).

Client support is documented with quickstarts for Claude Code, Codex, Cursor, Zed, GitHub Copilot, OpenCode, Kilo Code, Kiro, AntiGravity, Gemini CLI, Roo Code, and Droid, and Augment's product page says any MCP-compatible agent can be pointed at the endpoint (Context Engine MCP). MCP queries draw from the same usage pool: LLM tokens at list price plus the 40% service fee, which Augment's docs estimate at roughly $0.03 to $0.06 per query.

On benchmarks, Augment publishes its own numbers. The Context Engine MCP page reports an 80% quality improvement for Claude Code with Opus 4.6 across 300 Elasticsearch pull requests and 900 attempts, with smaller gains for two Cursor configurations, measured across correctness, completeness, best practices, code reuse, and documentation (Context Engine MCP). Separately, an Augment blog benchmark from May 2026 puts its Auggie CLI at a 67.4% pass rate against Claude Code's 66.3% on Terminal Bench 2.0 with Opus 4.7, at roughly 33% lower cost (Augment benchmark). Both are vendor-run benchmarks on vendor-chosen tasks, and they should be read that way.

Symvanta is a hosted MCP endpoint by default, working with Claude Code, Cursor, Windsurf, and other MCP clients, with an on-prem bundle available for Enterprise customers. Cross-repo context comes from explicitly linking repositories, including cross-repo HTTP-call edges between services, and indexing is branch-aware, so an agent can pin a session to a feature branch or even query uncommitted working-tree edits.

Enterprise security and self-hosting, precisely

Augment's published Enterprise feature list includes SOC 2 Type II, customer-managed encryption keys, ISO 42001 compliance, SIEM integration, data residency options, granular access controls, comprehensive audit trails, and SSO, OIDC, and SCIM (Augment Code pricing, Security).

On deployment, the current docs document self-hosted compute for Augment's Cosmos agents, where customers run daemons on their own infrastructure, plus self-hosted Kubernetes as an early-access path. They do not describe a VPC-hosted or air-gapped Context Engine index: the Remote MCP is hosted by Augment, and the Local server is a developer-machine process. If a fully air-gapped code index is a hard requirement, treat it as a sales question; the public docs we checked in September 2026 do not state it.

The 40% fee, worked through

The fee structure is worth sitting with for a second, because it changes how a team should think about the flat price. The monthly price buys a matching amount of pooled usage; usage beyond the pool continues pay-as-you-go, and every dollar of LLM inference carries the 40% service fee on top of the provider's list price. Augment's docs give a worked example for the Business plan: $70 of LLM tokens, plus $28 of service fee (40% of the $70), plus $2 of compute lands exactly at the included $100 (Token-based pricing). Compute itself carries no fee. A team running heavy agentic workloads (long sessions, big context windows, frequent tool calls) will burn the pool faster than a team doing light autocomplete-style usage, and the fee scales with LLM usage rather than flattening out. None of that makes the pricing bad; it makes it usage-shaped, which is a different thing to budget for than a flat per-seat number. The other lever on an inference-shaped bill is what the agent re-sends every turn; we work that side of the equation in Sonnet plus a code graph vs Opus alone.

Side by side

Who should pick Augment

If your team wants a single flat monthly number with pooled usage across up to 50 people, and you prefer context retrieval to happen behind the scenes rather than as tool calls the agent composes itself, Augment is a mature product with real org-wide indexing, an expanding agent platform in Cosmos, and a steady stream of published benchmarks. The $20 Standard plan also makes it inexpensive to trial the Context Engine across a small team, and the 40% fee is transparent, if usage-shaped.

Who should pick Symvanta

If you want the agent to be able to ask "who calls this" and get an actual graph traversal back (a retrieved chunk still needs interpreting), and you would rather pay per seat than manage a shared usage pool with a service fee on top, that is the fit. The difference in one line: the graph is the interface itself, the thing the agent queries directly, and search sits beside it as one more tool. The MCP server page lists the tools, and pricing lists every plan.

Frequently asked questions

Both of these are claims worth testing on a codebase you actually maintain. Book a 15-minute demo on your own repository and see what the graph returns, or start a free trial and point your agent at the endpoint. To see how Symvanta compares with the rest of the category, read code graph MCP servers compared.