How enterprise engineering organizations capture multi-agent developer workflows across Gemini CLI, Antigravity, Claude Code, Cursor, Codex, and API proxies with zero code changes and pre-execution endpoint DLP secret masking.
Before an organization can monitor spend or enforce security governance, it must capture every developer AI interaction across all execution surfaces without introducing developer friction.
Developers today use a diverse spectrum of AI tools: Gemini CLI and Claude Code for terminal debugging, Antigravity and Cursor for IDE refactoring, Codex for automated loops, and custom internal scripts via LiteLLM proxies.
Without a unified capture plane, organizations face severe data risks: proprietary source code, internal schemas, and .env credentials leak to external LLMs, while high-value debugging breakthroughs disappear when terminal windows close.
Standard API proxies only see HTTP JSON strings. They miss three critical elements of developer AI workflows:
pip install rclm && rclm-hooks-installexport OPENAI_BASE_URL="http://localhost:8000/v1"rclm-sync --allReclaimLLM native hooks recursively inspect files matching .env, *.env, and .envrc on the developer laptop. Credentials and API keys are redacted locally and replaced with [REDACTED:API_KEY] before prompts or tool results ever touch the network.
ReclaimLLM provides an official RCLM MCP Server (10 native tools including search_sessions, handoff, transfer_session, and file_brief) to query captured organizational memory directly from inside any coding assistant.