A repository is no longer where an AI coding tool's context has to end.

Modern software rarely maps cleanly to one repo. A frontend may depend on backend services, shared libraries, workers, infrastructure code, and configuration spread across several repositories.

So the interesting question is no longer "Which tool supports multiple repos?"

It is what replaces the repository boundary - and how that wider context is created, represented, reused, and acted on.

How We Compared These Tools

This comparison focuses on publicly documented capabilities available in October 2026 We compare the dominant context model each product emphasizes, not every feature it offers. Several capabilities overlap.

Context architecture

Context boundary - what replaces the repo?
Repository onboarding - how do repos enter context?
Representation - environment, index, graph, or organisation context?

How it is used

Persistence - is the context reused?
Agent integration - where does the context show up?
Execution - can the system change/test across repos?

1. Cursor: The Development Environment

Cursor treats cross-repository work as part of the development environment.

A single agent session can target a reusable multi-root workspace. Cursor's Cloud Agents can also use multi-repo environments where selected repositories are cloned into the same agent machine. The agent can inspect the full workspace, make coordinated changes, run tests, and open pull requests in the repositories it changes.

frontend ----┐
backend -----+--> Multi-repo development environment --> Cursor Agent
shared ------┘

The important distinction is that the repositories do not only become searchable together. They become part of the same working environment, so the agent can inspect and modify them together.

Source: Cursor - Cloud Environment Setup; Cursor - Multi-root Workspaces

2. Kiro: The Multi-Root Workspace

Kiro builds cross-repository context around the workspace.

Multiple projects can be added as roots of one workspace. Kiro's Codebase Indexing and Repository Maps include code from all root folders, while specs, steering files, hooks, and MCP configuration can retain their root-level identity.

Multiple roots
      |
      v
Codebase index + repository maps
      |
      v
Requirements -> Design -> Tasks -> Implementation

Kiro therefore combines multi-root code context with its spec-driven development workflow. The workspace is both the context boundary and the place where structured implementation work happens.

Source: Kiro - Multi-root Workspaces

3. Graphify: The Persistent Graph

Graphify takes a graph-first approach.

Its open-source tooling parses code into a structural graph and exposes relationships such as calls, imports, inheritance, and symbols. Multiple repository graphs can be merged into a cross-repository graph, and the resulting graph can be queried directly or exposed through MCP.

repo-a -> graph --┐
repo-b -> graph ---+--> Cross-repo graph --> Query / MCP / coding assistant
repo-c -> graph --┘

The main abstraction here is not a working environment. It is a persistent, queryable representation of the code structure. Graphify can also run its extraction locally, which gives it a different deployment profile from managed development environments.

Source: Graphify GitHub; Cross-repo merge reference

4. CodeZero: Organisation-Level Context

CodeZero starts from a different boundary: the organisation.

Instead of asking a developer to assemble the repositories needed for a particular session, connected repositories are indexed and made available as shared engineering context. Cross-repository relationships can then be resolved from those indexes and exposed to supported coding clients through MCP.

Organisation
   |-- frontend
   |-- checkout-service
   |-- payment-service
   |-- invoice-worker
   `-- shared libraries
          |
          v
Shared repository indexes + dependency context
          |
          v
MCP / supported coding clients

The emphasis is on reusable organisation-level context rather than rebuilding the relevant repository set for every developer session. Claude Code also has a tighter product-specific integration path for per-prompt context.

Source: CodeZero product implementation and Frigga product documentation.

5. One Scenario, Four Context Models

Scenario: change the payment API without breaking the frontend, mobile app, or invoice worker.

The engineering task is the same. What changes is how each system establishes the cross-repository context around it.

Cursor

Put the relevant repositories into a multi-repo development environment. The agent can inspect, modify, test, and coordinate changes across that environment.

Kiro

Add the projects as workspace roots. They enter the shared codebase index and repository maps, then participate in Kiro's spec-driven workflow.

Graphify

Extract and merge the repository graphs. Query the resulting cross-repo graph to follow structural relationships and expose that graph to an assistant through MCP.

CodeZero

Use the organisation's existing repository indexes and dependency context to retrieve the repositories and code connected to the change, then expose that context to the coding client.

This is the distinction between context and execution. The same cross-repo problem can be represented as an environment, workspace, graph, or organisation-level context layer.

6. Side-by-Side

Important: the categories below describe each product's primary context model, not an exhaustive list of capabilities. Several products overlap.

	Cursor	Kiro	Graphify	CodeZero
Primary context model	Multi-repo development environment	Multi-root workspace	Persistent structural graph	Organisation-level engineering context
Repos enter context through	Selected repos / environment	Workspace roots	Graph extraction + merge	Organisation connection + indexing
Representation	Working development environment	Workspace index + repository maps	Queryable knowledge graph	Repository indexes + dependency context
Persistence model	Reusable environment	Workspace + index	Persistent graph	Shared organisation context
Agent interaction	Cursor agents	Kiro workflow	MCP / coding assistants	MCP / supported coding clients
Cross-repo execution	Yes - inside configured environment	Across workspace roots	Primarily context / query layer	Context / retrieval layer
Primary abstraction	Environment	Workspace	Graph	Organisation

7. So, Where Does Your Codebase End?

For the tools compared here, the Git repository is no longer the only meaningful context boundary.

What differs is the structure built around it.

Cursor
Development environment
Kiro
Multi-root workspace
Graphify
Persistent cross-repo graph
CodeZero
Organisation engineering context

The architectural trade-off depends on what the team wants the agent to do with wider context: work directly across repositories, follow a spec-driven workflow, query a persistent structural graph, or retrieve shared organisation-level context.

The important question is not simply whether an AI tool can see more than one repository.

It is what the system does with that additional context - how it represents relationships, how long that context persists, and how the agent uses it.

Explore CodeZero

See how CodeZero gives coding agents organisation-level context across connected repositories.

Explore CodeZero →

Sources checked 12 October 2026

Cursor: Cloud Environment Setup
https://cursor.com/docs/cloud-agent/setup
Cursor: Multi-root Workspaces
https://cursor.com/changelog/04-24-26
Kiro: Multi-root Workspaces
https://kiro.dev/docs/editor/multi-root-workspaces/
Graphify: project and MCP
https://github.com/Graphify-Labs/graphify
Graphify: cross-repository merge
https://github.com/Graphify-Labs/graphify/blob/v8/graphify/skills/codex/references/github-and-merge.md

Where Does Your Codebase End? Comparing Cursor, Kiro, Graphify, and CodeZero