Your AI Coding Agent Forgets Everything. I Fixed It With a Local MCP Memory Server
Описание и применение
Местный сервер памяти MCP позволяет AI‑ассистенту сохранять контекст между сессиями, уменьшая необходимость повторно объяснять код и решения. Он использует Markdown‑файлы и SQLite FTS5 для офлайн‑поиска, достигая Recall@10 98.6% без вызовов LLM.
Задача
AI coding agents lack persistent memory across sessions, forcing developers to repeatedly explain their codebase and project decisions.
Результат
The local MCP memory server achieves Recall@1 80.2%, Recall@3 92.8%, Recall@5 96.0%, Recall@10 98.6% on LongMemEval, outperforming single BM25 or vector methods by 3% with zero LLM calls on retrieval.
Рабочий процесс
- Run
npx @awareness.market/setupto install and start the local daemon on 127.0.0.1:37800. - The installer detects the IDE and wires the MCP server.
- The agent gains five tools: awareness_init, awareness_recall, awareness_record, awareness_lookup, awareness_get_agent_prompt.
- During a session, the agent calls awareness_init to load recent context.
- When needing information, the agent uses awareness_recall in two phases: first a summary, then full content for selected items.
- The agent records new decisions with awareness_record.
- The memory is persisted in .awareness/ as Markdown files and an SQLite FTS5 index.
- Retrieval uses hybrid BM25 + vector embeddings with RRF, no LLM calls.
- The agent can recall past migrations, decisions, and TODOs automatically.
- The process is fully offline and local-first.
Доказательства
I evaluated it on LongMemEval (ICLR 2025) — 500 human‑curated questions, ~115k tokens of history per question: Recall@1 80.2% Recall@3 92.8% Recall@5 96.0% ◀ primary Recall@10 98.6%
Retrieval code and scripts are in the repo, so you can re‑run it yourself rather than trust a table in a blog post.
Memory lives in .awareness/, as Markdown you can read, edit, diff, and commit: .awareness/ ├── memories/2026-03-22_decided-to-use-postgresql.md ├── knowledge/decisions/postgresql-over-mysql.md ├── tasks/open/implement-rate-limiting.md └── index.db # SQLite FTS5 index, rebuilt automatically
- Дата записи: 2026-10-06T18:55:51.751Z