Why Repobase

To effectively code using AI agents, having access to correct and up-to-date documentation is crucial. Currently, developers often rely on a few imperfect methods:

1. Web Search: This is essentially delegating a Google search to the agent. It is often limited, unreliable, and restricted by website paywalls or anti-bot measures. You have to “hope” the agent finds enough relevant details.
2. Copy-Pasting: While effective, it kills productivity. You have to manually find, copy, and paste context into prompts or reference files. These files quickly become outdated and are hard to manage across multiple projects.
3. Specialized MCPs: Using individual MCPs for every library adds overhead and bloats the agent’s context window.
4. Remote Services (e.g., Context7): Centralized MCPs solve some issues but introduce latency, require an internet connection, and raise InfoSec concerns regarding private repositories (often a paid feature).

So I thought: wouldn’t it be great to have all the repositories I care about indexed locally and easily searchable by my tools?

You could manually clone repositories and let an agent use grep, but that is messy and high-maintenance. You constantly need to tell the agent where files are, manually sync updates, and—crucially—you lose the ability to perform semantic search. grep finds strings, but it can’t answer “Where is the Google OAuth flow defined?”

This is where Repobase shines.

It acts as a seamless, centralized inventory of your important repositories.

• Seamless Integration: The agent simply runs list_repos to see what’s available and search to find code semantically or by keyword.
• Source of Truth: The code itself is the ultimate documentation, containing the latest usage patterns and implementation details often missing from docs.
• Local & Private: Everything stays on your machine. Indexing uses a local model, ensuring maximum performance and privacy for both public and private code.