Sourcegraph Cody Alternative: MCP Code Graph for Agents

This page is for engineering teams who evaluated Cody before it went enterprise-only, or who are now staring at a six-figure Sourcegraph quote and wondering what else gives an AI coding agent real code context. If you want a second opinion after a Sourcegraph sales call, read on.

What happened to Cody

Cody Free and Cody Pro are gone. Sourcegraph stopped new signups on June 25, 2025, and cut off access entirely on July 23, 2025, folding what remained into Cody Enterprise (Sourcegraph, changes to Cody Free, Pro, and Enterprise Starter plans). Enterprise Starter workspaces created after that date no longer include Cody at all, only Code Search.

Then on December 2, 2025, Sourcegraph and Amp split into two independent companies. Amp, the agentic coding product built by Sourcegraph co-founders Quinn Slack and Beyang Liu, is now its own company. Cody stayed with Sourcegraph as an Enterprise product. Cody was not rebranded to Amp: they are two separate products from two separate companies now, sharing a common origin and little else going forward.

If you evaluated Cody a year ago and lost track of it, that is the whole story: a consumer and pro tier that no longer exists, an enterprise tier that remains, and a spun-out agent product that is not the same thing.

What Sourcegraph costs today

Sourcegraph publishes one number: Enterprise pricing "starting at $16K," scaling with AI feature credits and team size, quote-only past that (Sourcegraph pricing). There is no self-serve tier and no public per-seat rate, as of July 2026. If you have seen a $59/user/month figure floating around older blog posts, that was the discontinued Cody Pro tier: it does not exist anymore and Sourcegraph does not publish anything like it today.

That is a deliberate positioning choice, not a mistake on their part. Sourcegraph sells to organizations that already run procurement processes for infrastructure this size. It is a mismatch for a five-person team that wants to wire an MCP server into Claude Code this afternoon.

How each one gives an agent context

Sourcegraph's engine is code search plus code graph: keyword, regex, and structural search over the codebase, layered with SCIP-based code intelligence for precise go-to-definition and find-references (Sourcegraph, code graph context). Cody Enterprise's own documentation describes this search-and-graph combination without describing an embeddings-based retrieval path, which lines up with Sourcegraph's public messaging that Search replaced embeddings as the default context mechanism for Cody.

Symvanta takes a different bet. It parses each repository into a live graph (nodes are symbols, edges are calls, imports, implements, and instantiates, each with a confidence score), stores embeddings in Qdrant for semantic search, and keeps literal text search as a third path. An agent asking "who calls this function" gets a graph traversal, not a search result it has to re-derive. That distinction is the subject of why AI coding agents fail on large codebases: the failure mode is rarely a missing search index, it is an agent that finds a plausible-looking match and guesses the rest. We go deeper on the tradeoff itself in code embeddings vs. code graph: search and embeddings tell you what looks related, a graph tells you what is actually connected.

One place Sourcegraph's documentation is quiet: neither the Cody nor the Search docs describe a named blast-radius or transitive-impact primitive, the kind of "what breaks if I change this" answer that comes from walking edges outward from a symbol. That does not mean Sourcegraph cannot answer that question through search and code intel combined; it means their public docs do not describe it as a first-class tool the way callers, dependencies, and blast radius are first-class relate operations in Symvanta.

MCP support

Both directions work here. Cody can consume external MCP servers, and separately, Sourcegraph ships its own MCP server exposing search, file browsing, go-to-definition, find-references, and commit history to any MCP client (Sourcegraph supports the Model Context Protocol, Sourcegraph MCP). Symvanta is MCP-first by design: the whole product is an authenticated MCP endpoint plus a dashboard for managing what is indexed. It works with Claude Code, Cursor, Claude Desktop, or any MCP client, same as Sourcegraph's server does.

Cross-repo and on-prem

Multi-repo context is core to Sourcegraph. It was built as a company-wide code search tool before AI agents existed, and cross-repository awareness is table stakes for that. Symvanta supports linked repositories with cross-repo edges, including HTTP-call edges between services, plus branch-aware indexing so an agent can query a feature branch instead of only the default branch.

On-prem is Sourcegraph's strongest ground. Self-hosted deployment covers Docker Compose and Kubernetes/Helm, with air-gapped, bring-your-own-key deployments supported for regulated environments (Sourcegraph self-hosted docs). This is a mature, years-old deployment story. Symvanta has a hosted MCP endpoint plus an on-prem bundle for enterprise customers, but Sourcegraph has more field experience running fully air-gapped.

What evaluating each one actually looks like

With Sourcegraph, evaluation starts with a sales conversation, because there is no public per-seat price and no self-serve signup to try against your own repository first. That is normal for infrastructure sold at this scale, but it means the first real signal you get is a demo someone else drives, not a tool you point at your own codebase on your own schedule.

With Symvanta, the path is the reverse: connect a repository, get an MCP endpoint, point your agent at it, and ask it a real question about your own code before anyone from Symvanta talks to you. That is a smaller test than a full Sourcegraph rollout, and it is meant to be: the goal is to see whether the graph answers correctly on the codebase you actually maintain, not a demo repo chosen to look good.

Side by side

Who should pick Sourcegraph

If you are a large organization that already needs air-gapped deployment, a mature multi-repo search platform, and a procurement process that can absorb a five- or six-figure annual contract, Sourcegraph Enterprise is a legitimate, battle-tested choice. Their code intelligence and search infrastructure predate the current wave of AI coding agents by years, and that maturity shows in the self-hosted story.

Who should pick Symvanta

If you want an MCP endpoint your agents can call this week, at a per-seat price a small team can expense without a sales call, and you want the agent asking "what calls this" or "what breaks if I change this" to get a graph answer instead of a search result it has to interpret, that is the gap Symvanta fills. Graph not grep, without the six-figure floor.

The fastest way to see the difference is on your own repository, not a demo repo built to look good. Book a 15-minute demo and bring a real question about a real codebase.