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.
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
