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Driver is a context compilation platform for codebases, designed to provide AI coding agents with exhaustive, up-to-date, and structured context. Built by a team focused on agentic development, Driver solves the problem of AI agents making incorrect changes due to incomplete understanding of codebases. Its core capabilities include pre-computing architecture documents, symbol tables, call graphs, and dependency maps, which agents can retrieve via MCP (Model Context Protocol) or REST API. Driver supports any language and integrates with GitHub, GitLab, Bitbucket, and other SCM systems. It is used by enterprise teams and high-velocity startups for tasks like codebase migrations, support ticket resolution, legacy code understanding, and accelerating AI coding agent productivity. The tool reduces manual context management by up to 90% and increases agent effectiveness by 5x, making it ideal for engineering teams adopting agentic SDLC.
4.8/5
High, consistent, and deterministic
Clean and developer-focused
To compile exhaustive codebase context for AI agents, enabling accurate and efficient agentic development.
Integrates with GitHub, GitLab, Bitbucket, and any MCP-compatible client or REST API.
Contact sales for pricing; likely enterprise-tier with custom plans
Features with the highest value for users are highlighted here.
Pre-compiled codebase context
MCP integration for AI agents
Symbol-complete documentation
Dependency-aware call graphs
Auto deep context documents
Multi-language support
SCM integration (GitHub, GitLab, Bitbucket)
SSO and IdP group mapping
Engineering Teams
CTOs and VPs of Engineering
AI Coding Agent Users
Platform Engineering Teams
Enterprise Architects
QA Engineers
Support Engineers
Solutions Engineers
Startups with High-Velocity Development
Organizations Undergoing Codebase Migrations
Enterprise
Weekly intelligence on AI strategy, operations, and market shifts. No noise. No narrative. Direct to your inbox.
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