
Rememb
io.github.LuizEduPPPublished by GitHub account LuizEduPPv0.3.5Updated Oct 24, 2026
Persistent memory for AI agents — local JSON, zero config, no server required.
Overview
Local-first long-term memory for AI agents: stores structured entries in JSON or SQLite on disk, with keyword search, versioning, diff, restore and an audit…
- What you can do
- Write, edit, soft-delete and restore memory entries organized into sections such as project, actions, systems, requests, user and context
- Search entries by keyword and token, then read full bodies by id
- Inspect version history, side-by-side diffs and an audit trail of changes
- Inject recent entries, tags and stats at session start, and record post-tool and stop events as handoff entries
- Browse memory, stats, settings and bundled agent skills in a local web UI
- When to use it
- Useful when an assistant keeps losing project facts, decisions and preferences between sessions and you want durable, inspectable memory without a hosted memory service or API keys. Fits solo developers and teams running agents daily who want a local store they can copy, audit and roll back.
- Requirements
- Runs as a local process installed from PyPI (pip install rememb); Python 3.11 to 3.14. No accounts, API keys or cloud services. The MCP server starts with the rememb mcp command over stdio, or optionally as a local SSE endpoint on a chosen host and port. The store auto-initializes at ~/.rememb, with optional per-project stores.
Installation
In SourceWeft
- Open Rememb in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
[Rememb MCP server] [MCP Badge]
Operate AI agents without losing context between sessions. rememb is local-first long-term memory: structured entries, keyword search, versioning, diff, restore, and audit trail — no cloud, no API keys.
[rememb chat demo]
The problem
Teams using agents at real velocity rarely fail because they lack generation. They fail because operating agents every day creates context debt:
- too much re-explaining project facts every session
- too little durable memory outside the chat window
- too little audit trail for why something changed
- too much noise when recalling the right context
Every team or solo developer operating agents professionally hits this wall:
Existing solutions often center on hosted memory layers, API keys, or opaque context pipelines. What you actually need is to resume the next session with the minimum correct context and a trail you can inspect.
rememb is built around four memory problems:
- durable facts and decisions instead of session-only chat memory
- keyword search instead of rereading everything (agents judge relevance)
- non-destructive versioning instead of silent overwrites
- local-first audit trail for AI work, not opaque cloud logs
Install
Quick Start
With MCP (recommended)
1. Install the door, or add the MCP block by hand:
That writes the MCP server, Memory Rules, and SessionStart / PostToolUse / Stop hooks when the host has them (Cursor and Claude today). Without --apply it only prints the plan. --host limits the target; omit it to write every host rememb install knows (cursor, claude, codex, vscode, copilot, windsurf, continue, gemini, opencode, zed, cline).
Or add this to your IDE's MCP config and paste the rules from MCP_TOOLS.md:
Add repeatable --project /path/to/repo args for per-project stores alongside global ~/.rememb. Details: MCP_TOOLS.md.
2. Restart your IDE.
SessionStart injects recent entries, tags, and a short stats block. The agent writes durable memory when something changes, and searches only when targeted recall is needed.
No extra storage setup is required. In MCP mode, rememb auto-initializes ~/.rememb and optional --project stores on first use. Public tools: MCP_TOOLS.md (18 tools).
If you want multiple MCP clients on the same machine to reuse one already-running rememb process, start a persistent local SSE transport:
This keeps one MCP process alive, so repeated clients can connect through http://127.0.0.1:8765/sse and http://127.0.0.1:8765/messages/.
Do not put --transport sse inside a stdio MCP client config. stdio clients expect JSON-RPC on stdin/stdout; the SSE mode exposes an HTTP endpoint and must be started separately.
Local usage without MCP
How it works
A local store on disk. Your agent can read prior decisions, search by keywords and tokens, update entries without losing history, and restore previous versions without depending on a cloud memory service. Copy ~/.rememb/ anywhere to move the store.
Writes, edits, and deletes go through rememb_write, rememb_edit, and rememb_delete. Host hooks also write into actions via rememb hook post-tool / stop. For the full MCP surface, see MCP_TOOLS.md.
Search uses keyword and token matching over entry content and tags. rememb_search returns id, score, tags, date, and a short excerpt (search_excerpt_chars, default 160). Full body is rememb_get / rememb_read on the ids the agent picked, or max_chars=0 on search. The agent applies semantic relevance judgment. No API keys, no cloud, no embedding model download at runtime.
config.json is written during initialization with all supported knobs:
Set storage_backend to sqlite for larger stores. The Web UI and MCP migrate existing JSON entries automatically when you switch backends.
entry_batch_size and entry_load_threshold control pagination in the web UI — how many cards load at once and when to trigger "load more".
Section names are normalized to lowercase, duplicates are ignored after normalization, and removing a section with existing entries automatically migrates those entries to uncategorized. meta.json is kept in sync with the current effective section list.
Older stores may still contain legacy embedding-related config keys; they are dropped the next time configuration is loaded or saved.
Memory sections
Web UI
rememb includes a local web interface for supervision — browse memory, inspect history, and tune runtime settings. The SPA has no create/edit/delete controls. The HTTP API still has write, delete, and restore routes.
Overview with entry totals and recent memory activity.
Stats with totals, section breakdown, date range, and recent entries.
Settings for limits, storage backend, section colors, and maintenance actions.
Skills browser for bundled agent skills included with rememb.
Views:
- Overview — entry totals, deleted count, store size, and recent memory
- Memory — browse, keyword search, filter by section, sort, and include deleted entries
- Stats — totals, backend, section bars, oldest/newest timestamps, and recent entries
- Settings — edit limits, storage backend, section colors, consolidate duplicates, and save runtime config
- Skills — browse bundled agent skills (61 skills shipped in the package)
Entry inspection from the UI includes version history and side-by-side diff. Entry mutations and restore are MCP (rememb_write, rememb_edit, rememb_delete, rememb_restore) or the HTTP API, not SPA controls.
CLI
Compatibility
The current compatibility surface is tracked explicitly in COMPATIBILITY.md.
Short version:
- Python 3.11 to 3.14 are covered by CI
- CLI contract and MCP tool schema (18 tools) have automated test coverage
- stdio MCP is the primary documented integration path
- SSE MCP is documented and partially tested at the route level
- release automation and Trusted Publishing are documented in RELEASE.md
Design
- Local first — plain JSON or SQLite on disk
- Portable — copy
~/.rememb/anywhere, it works - Agnostic — any agent, any IDE (MCP or CLI)
- No lock-in — no servers, no API keys, no accounts
Core capabilities:
- structured memory with sections and tags
- keyword search with agent-side relevance judgment (
rememb_searchis an index: id, score, excerpt; full body via get/read) - host door: SessionStart injects recent + tags + stats; PostToolUse / Stop write into
actions; Stop tagshandoffso the next host sees it first rememb installwrites MCP, Memory Rules, and hooks (hooks for Cursor and Claude)- non-destructive versioning, diff, restore, and soft delete
- duplicate consolidation (exact content) and store stats
- config and maintenance via Web UI (settings and consolidate; entry mutations via MCP or HTTP API)
- 61 bundled agent skills via Web UI and MCP
Contributing
PRs welcome. Issues welcome. Stars welcome. 🌟
License
MIT
Source: README.md at commit ab6f4dc
Tools
0Version history
1- v0.3.5LatestSep 16, 2026
Score
50% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
- Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts