99% token reduction for AI agents querying your codebase. The MCP-native way to index once, query infinitely.
Your codebase is valuable context for AI agents. But shipping entire files to Claude burns tokens like gasoline in a sports car. Full-repository grounding becomes expensive and slow. And cached context expires in long-running agentic workflows.
Codebase Memory solves this by indexing your repository as a Model Context Protocol resource. Agents query by function, class, dependency, or intent. No more context bloat. No more token waste.
Ship full source files to Claude for each query.
~45,000 tokens
per agent turn (large repo)
Query indexed codebase via MCP.
~450 tokens
per agent turn (cached)
Point to a GitHub repo, GitLab project, or local directory. Codebase Memory scans the repository structure, extracts function signatures, dependency graphs, and docstrings. Creates a queryable knowledge base in seconds.
Built on the MCP standard. Works with Claude, other LLMs, and agent frameworks that support MCP tools. No wrapper or adapter needed. Drop it into your existing stack.
Ask about functions by intent ('error handlers for network timeouts'), files by responsibility ('authentication middleware'), or dependencies by license. Get precise results, not full files.
Indexed repositories are cached across agent turns. Updates are incremental. Long-running agents maintain context without re-indexing or token re-spend.
Pay for repositories indexed, not queries run.
$29/mo
$99/mo
Custom
Existing codebase tools built for humans (IDE plugins, search engines). Codebase Memory is built for agents. It understands what LLMs need: structured knowledge, compressed context, fast retrieval. Your codebase becomes a reusable tool, not a liability.
Agents spend less time reading code, more time solving problems. Your API bills go down. Your agent reliability goes up.
Register interest
This is not a purchase and there is no card field. It puts your address, this product, and whatever you write below in front of a person, and you get a written answer about what finishing it, or handing it over for you to run yourself, would actually take.