Your coding agent starts blank every session.
Without durable memory, Claude Code and Codex re-learn project conventions, re-ask about preferences, and lose track of what was completed. Each session is a fresh start — wasteful and frustrating.
Claude Code, OpenAI Codex, and Cursor agents lose context between sessions. Bilinc persists project decisions, conventions, and histories so every session starts with the full picture.
Without durable memory, Claude Code and Codex re-learn project conventions, re-ask about preferences, and lose track of what was completed. Each session is a fresh start — wasteful and frustrating.
# Agent commits what it learned
bilinc commit --key PROJECT_CONVENTION \
--value '{"use_pytest":true,"type_hints":"strict"}' \
--memory-type semantic
# Next session recalls everything
bilinc recall --query "project conventions"
# > {"use_pytest":true, "type_hints":"strict"}Coding agents naturally lose context between sessions — they forget project conventions, user preferences, past decisions, and prior completion state. Long-term memory lets agents persist goals, code conventions, testing preferences, dependency choices, and architectural decisions so every session starts with full project context.
Configure Bilinc as an MCP server in Claude Code's config. Tools like commit_mem and recall become available directly in the agent loop. Claude Code can save design decisions to memory and recall them in later sessions, maintaining context across multi-day development projects.
Yes. OpenAI Codex CLI supports MCP servers. Add the Bilinc MCP adapter to Codex's configuration, and commit/recall tools appear automatically. Codex agents can store project context, test results, and dependency decisions that persist across restarts.
Install bilinc from PyPI, run bilinc start to start the 7-day Cloud trial, create a hosted API key, and configure the MCP adapter. For Claude Code: add bilinc to claude_dot_config.json MCP servers. For Codex: add to .codex/config.json. For Cursor: add to .cursor/mcp.json.
Commit project decisions and why they were made, user preferences (theme, testing framework, package choices), completed task summaries, coding conventions adopted for the project, dependency version decisions, and architectural patterns. Avoid committing raw code or API secrets.