Sourcegraph website, code search, AI context, MCP, agents

Sourcegraph

A website and enterprise code intelligence platform for searching large codebases, giving AI agents repository context, tracking code insights, and coordinating cross-repository changes.

Main website

sourcegraph.com is the main public website for Sourcegraph.

Core model

Code intelligence platform with search, AI code context, MCP support, insights, batch changes, APIs, and enterprise controls.

Domain created

Who.is lists sourcegraph.com as created on November 25, 2012.

Sourcegraph is a code intelligence platform for code search, AI context, MCP-powered agents, insights, and cross-repository changes.View mark on Sourcegraph

What Sourcegraph is

Sourcegraph official site presents Sourcegraph as a platform for code understanding, oversight, and evolution. It is aimed at teams with large or complex codebases that need search, repository context, AI-agent support, analytics, and cross-repository change workflows.

Who uses Sourcegraph

Sourcegraph is used by enterprise engineering teams, platform groups, security engineers, developer productivity teams, support teams, and organizations adopting AI coding agents. It is especially useful when code is spread across many repositories, services, languages, and ownership boundaries.

How the website works

The website explains Sourcegraph products, links to documentation, public code search, security and compliance resources, pricing, case studies, guides, a changelog, and demo requests. It is both a marketing site and a navigation hub for the Sourcegraph product ecosystem.

Code search and codebase context

Code search is one of Sourcegraph's core jobs. The platform indexes repositories so people can find symbols, files, references, patterns, and changes across large codebases. That context helps engineers understand unfamiliar systems and trace the impact of a change before editing.

AI agents and MCP

Sourcegraph now frames much of its value around giving AI agents fuller codebase context. Its site highlights MCP support, code graph knowledge, and agent workflows that can search across repositories before planning or editing, reducing the risk that an agent misses related files or policies.

Batch changes and insights

Beyond search, Sourcegraph offers batch changes for coordinated edits across repositories and insights for higher-level code metrics. These tools help teams track migrations, measure patterns, remove deprecated APIs, or understand technology usage across a broad engineering organization.

Strengths and limits

Sourcegraph is strongest when a team has enough code, repositories, and developer activity for global search and context to matter. Smaller teams may not need the full platform, and organizations still need sound permissions, source control hygiene, review practices, and careful AI-agent rollout.

Why it matters

Modern software work often fails because teams cannot see the whole system. Sourcegraph matters because it treats codebase context as shared infrastructure for humans and agents, not just a search box, making large-scale maintenance and AI-assisted development less blind.

WHOIS domain data

Data pulled: May 24, 2026View current WHOIS record

Domain: sourcegraph.com
IP address: 172.64.155.69
Registrar: NameCheap, Inc.
WHOIS server: whois.namecheap.com
Referral URL: http://www.namecheap.com
Created: November 25, 2012
Updated: October 26, 2025
Expires: November 25, 2026
Nameservers: kay.ns.cloudflare.com (173.245.58.125); lakas.ns.cloudflare.com (172.64.33.194)
Domain status: clientTransferProhibited https://icann.org/epp#clientTransferProhibited
Contact privacy: Registrant, admin, and technical contacts are redacted for privacy and list Privacy service provided by Withheld for Privacy ehf.

Key concepts

Code intelligenceSearch and metadata that help people and tools understand relationships inside a codebase.
MCPModel Context Protocol, used to connect AI agents with external context such as code search and code graph information.
Batch changesCoordinated edits or migrations across many repositories instead of one repository at a time.

Common uses

Searching across many repositories to understand an API, dependency, error pattern, or ownership boundary.
Giving coding agents more context before they plan, edit, or review code in a large organization.
Running cross-repository migrations, deprecations, security fixes, or compliance checks.

Common misconceptions

Sourcegraph is not only a public code search website; it is also an enterprise platform for private codebases.
AI context does not replace code review, tests, permissions, or release discipline.
Global code search is most valuable when repositories are indexed, permissions are correct, and teams agree on how to use the results.

Open questions

How much codebase context should AI agents receive by default, and how should sensitive repositories be protected?
Which code intelligence signals best reduce mistakes in large cross-repository changes?
How should engineering teams measure whether AI-assisted workflows improve maintenance rather than simply producing more code?