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Star count
15 ★ · AliceLJY/recallnest · read from the repository page · (checked 2026-10-16 20:00:20)
Source
collected from the punkpeye/awesome-mcp-servers list · type: MCP server
Harvest history
first seen 2026-10-09 · last seen 2026-10-16 · seen 32× · listed by 7 sources
Score
score 703 · 15 ★ · 7 sources · mcp
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repository AliceLJY/recallnest;first catalogued 2026-10-09;last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.
**Shared Memory Layer for Every AI Client — CLI agents, desktop apps, your own scripts** *One memory. Every client. Context that survives across windows — and across machines.* A local-first memory system backed by LanceDB that turns scattered conversation history into reusable knowledge — shared across your coding agents, recalled automatically. **English** | 简体中文 | Roadmap | Website --- Why RecallNest? Coding agents forget everything between windows. Your context — project configs, debugging decisions, entity mappings — is scattered across Claude Code, Codex, Kimi, Antigravity — and every other terminal you open — with no shared memory. RecallNest is **one LanceDB-backed memory layer that all of them read and write**. Context stored in one window is recalled in another. Sessions checkpoint on exit and resume on start. Memory decays, evolves, and self-organizes — it is not a log you grep. What a recall actually looks like Three things in that block carry most of the design: - **Source cc · Age 2d** — this came out of a Claude Code window two days ago and you are reading it from a different terminal, possibly on a different machine. That is the premise the whole project is built on. - **prov : evidence/…** — every row states which layer it sits on. A fragment scraped out of a transcript never gets to pose as a decision you actually made; moving to durable memory is a separate, gated step with its own evidence requirement. - **imgs : …** — that session contained 52 images. **Not one of them is in the database.** The line exists so you know there is something to go look at, and producing it cost no model call, no vector, and no storage. > The row above comes from transcript ingest. Since 2026-10-06 that step is off by default: > ingest no longer chunks conversation records into the store, so a default setup holds only > the memories you stored, distilled entries and memory files, and raw sessions are left to a > dedicated session-search tool. To get rows like this one back, see "Index existing > conversations" below. That last one is the approach in miniature: **store what makes a thing findable, not everything that could ever be asked about it.** The full reasoning — including the two places where the obvious implementation was wrong — is in Images: addressable, not embedded. Core Capabilities Access & Setup | Capability | Description | |---|---| | **CC Plugin** | Install in Claude Code with one command — no manual config | | **Shared Index** | One LanceDB store shared by every terminal that speaks MCP | | **Dual Interface** | MCP (stdio) for CLI tools + HTTP API for custom agents | | **One-Click Setup** | Integration scripts install MCP access and continuity rules | Recall & Continuity | Capability | Description | |---|---| | **Hybrid Retrieval** | 6-channel: vector + BM25 + L0/L1/L2 multi-vector + KG graph (PPR). The default mode is vector-only (since 2026-06); BM25 fusion and graph expansion are opt-in | | **Write-time Triggers** | Each memory can carry 2–6 "how will this be asked about later" phrasings (triggers), embedded separately and used only for recall — never rendered as evidence. Borrowed from Tencent T-Mem (EMNLP 2026). | | **4 Retrieval Profiles** | default, writing, debug, fact-check — tuned for different tasks | | **Session Continuity** | checkpoint_session + resume_context (full/light/summary modes) with repo-state guard | | **Session Distiller** | 3-layer conversation compression: microcompact → LLM summary → knowledge extraction | | **Conversation Import** | Import from Claude Code, Claude.ai, ChatGPT, Slack, and plaintext | | **Topic Tags** | Intra-scope topic partitioning — auto-detected, filterable in search | | **Related Scope Sidecar** | Opt-in includeRelatedScopes search over configured scopeRelations, shown separately from the main scoped ranking | Memory Lifecycle & Governance | Capability | Description | |---|---| | **Memory Evolution** | Supersede chains, decay scoring, LLM importance, consolidation, archival | | **Smart Promotion** | Evidence → durable memory with conflict guards, merge resolution, and audit trail | | **Privacy Tiers** | 4-tier (ephemeral / private / durable / shared) with cascade forgetting | | **Admission Control** | Write-time gating: noise filter, importance floor, dedup, rate limiting | | **Memory Lint** | Contradiction, duplicate, stale, and orphan detection with health score | | **Offline Consolidation** | dream command: clustering, merging, pruning of accumulated memories |