Sourcegraph

Sourcegraph is the AI-powered code intelligence platform that gives coding agents complete codebase context.
Sourcegraph is an enterprise platform that indexes every repository in your organization and supplies coding agents with full, accurate context across the entire codebase. Instead of letting agents work with only a few open files, Sourcegraph delivers precise code search, deep semantic understanding, and structured context so AI agents produce more reliable results with fewer mistakes. Engineering teams use Sourcegraph to power internal AI agents, run large-scale code changes, ask complex questions about the codebase, and maintain control as the volume of AI-generated code grows. With Sourcegraph, agents stop missing cross-cutting changes and start operating with the same level of understanding that senior engineers have.

About Sourcegraph

Who It’s For
Sourcegraph is built for engineering organizations that manage large or multi-repository codebases and are adopting AI coding agents at scale. Sourcegraph is especially valuable for teams that need agents to understand the full system rather than isolated files, and for companies that must keep oversight, security, and consistency as AI-generated code increases. Platform teams, staff engineers, and engineering leaders responsible for code health and agent effectiveness benefit most from Sourcegraph.

What You Get

• Complete codebase indexing across all repositories
• Full context for any coding agent via MCP Server
• AI-powered Deep Search with grounded answers and citations
• Agentic Batch Changes for large-scale, multi-repo modifications
• Code Insights and monitoring to track migrations, risk, and adoption
• Enterprise-grade security, SSO, and deployment options

How It Works
Sourcegraph continuously indexes your repositories and builds a rich code graph. When a coding agent needs context, it queries Sourcegraph through search or the MCP Server and receives precise, relevant code and relationships instead of incomplete fragments. Deep Search lets humans and agents ask natural-language questions and receive answers backed by actual code citations. For large changes, Sourcegraph’s agentic batch capabilities plan and execute modifications across many repositories while keeping humans in control of review and merge.

Sourcegraph Features & Capabilities

Complete Codebase Context for Agents
Sourcegraph gives coding agents access to the entire codebase rather than limited open-file context. Through its MCP Server and search capabilities, Sourcegraph supplies agents with the files, symbols, and relationships they need to make correct cross-cutting changes and avoid the blind spots that cause incomplete or inconsistent work.

Deep Search
Sourcegraph Deep Search allows engineers and agents to ask complex questions in natural language and receive grounded answers with direct citations from the codebase. Sourcegraph makes this capability useful not only for developers but also for support, security, and other teams that need accurate information about how the system works.

Agentic Batch Changes
Sourcegraph enables large-scale code modifications through agentic batch changes. Teams can run migrations, modernizations, or security remediations across hundreds of repositories while Sourcegraph helps ensure the changes are complete and reviewable. Pricing for this capability can be tied to successfully merged changesets.

Code Oversight & Insights
Sourcegraph provides Code Insights and monitoring so teams can track patterns, migrations, risk, and adoption over time. Sourcegraph alerts can notify teams or agents when important code patterns change, helping organizations stay in control as both human and AI-generated code evolves.

Sourcegraph Use Cases

Making Internal AI Agents More Reliable
Companies that run their own fleet of coding agents connect them to Sourcegraph so every agent receives full codebase context. Sourcegraph dramatically reduces the number of incomplete changes and retries, improving both the quality and cost-efficiency of agent-driven work.

Large-Scale Migrations and Modernizations
When a team needs to update an API, migrate a framework, or apply a security fix across many repositories, Sourcegraph supports agentic batch changes that plan and execute the work systematically. Sourcegraph helps ensure that related files, tests, and dependent systems are not overlooked.

Answering Complex Codebase Questions
Engineers, security teams, and even non-engineering roles use Sourcegraph Deep Search to ask questions such as how a feature is deployed, where a particular pattern is used, or how authentication works across services. Sourcegraph returns answers grounded in actual code with citations.

Maintaining Oversight as AI Code Grows
As more code is generated by agents, Sourcegraph gives engineering leaders visibility into what is changing, where risk is accumulating, and whether migrations are progressing. Sourcegraph turns the growing volume of AI-assisted code from a source of uncertainty into something that can be measured and governed.