aoci-code vs llmtrim
aoci-code: AOCI-CODE creates a persistent, Git-versioned map of your entire codebase, including database schemas, which coding agents can read to understand the system quickly and accurately. This infrastructure empowers AI agents to build and maintain large systems without repeatedly re-reading the repository, ensuring continuous understanding across tasks and sessions.; llmtrim: llmtrim is a local proxy that intelligently compresses LLM API requests by removing wasted tokens, significantly reducing billing costs without impacting the quality of the LLM's responses. It offers versatile deployment options, including a proxy, CLI, MCP server, or library for various programming languages.
TL;DR
- Your codebase or database schema is large and complex, causing coding agents to burn tokens and lose context across sessions.
- You want a local-first, Go-based, Git-versioned architectural knowledge map that coding agents read before touching any files.
- Your project is a simple small repo or script where agents can easily fit the whole tree in context without an index map.
- You need general conversational memory for chat logs or personal tasks rather than software architecture topology (use Mem0 or mcp-memory-service).
Reducing LLM API costs for AI agents (e.g., Claude Code, Cursor, Aider).
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