Rememb MCP server
io.github.LuizEduPP/rememb·v0.3.5·4 starsPersistent memory for AI agents — local JSON, zero config, no server required.
4 stars91 downloads/wk
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If you have run it, two minutes of your experience saves the next person an afternoon.
Rememb tools (7, 3 write)
write = sends, deletes, buys or postsRead from the package source without running it. The installed server may list more.
rememb_clearwrite actionDelete ALL memory entries. Use with caution.
rememb_deletewrite actionRemove a memory entry by ID.
rememb_editModify an existing memory entry by ID.
rememb_initInitialize rememb memory store in current directory.
rememb_readRead all memory entries or filter by section. Use this at the start of every session to load context.
rememb_searchSearch memory entries by content or tags using semantic similarity.
rememb_writewrite actionSave a new memory entry. Use this when you learn something worth remembering.
Public scan report
scanner v0.1.9 · 2026-09-27 · same rubric, same numbers if you re-run it
- Code scan5 source files scanned25/25
- –Live reliabilityno gateway calls yet and no remote to proben/a
- –Tool poisoningtools not inspected (local package is not executed); not countedn/a
- Auth qualitylocal package, no credentials required12/15
- Maintenancelast push 16 days ago15/15
- Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10
How Rememb compares
Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.
- Safety score
- 92/100
- higher than 95% of 48,255 servers
- Tools
- 7
- the typical server has 7
- Tools that change things
- 43%
- typical: 0%. Fewer write tools means less an agent can break
- GitHub stars
- 4
- more than 82% of 28,688 servers
- Downloads a week
- 91
- more than 61% of 12,191 servers with a package
What its tools let an agent do: 4 read · 3 change
Install Rememb in Claude Code, Cursor or VS Code
claude mcp add rememb -- uvx rememb
What the publisher says
From the Rememb repository's README, as published. We do not edit it. Read it on GitHub
<!-- mcp-name: io.github.LuizEduPP/rememb -->
Operate AI agents without losing context between sessions. rememb is a local-first persistent memory layer: structured entries, keyword search, versioning, diff, restore, and audit trail — no cloud service required.
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:
Session 1: "We're using PostgreSQL, auth at src/auth/, prefer async patterns."
Session 2: Agent starts from zero. You explain everything again.
Session 3: Same thing.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
pip install remembQuick Start
With MCP (recommended)
Zero friction. No CLI commands. Native IDE integration.
1. Add to your IDE's MCP config:
{
"mcpServers": {
"rememb": {
"command": "rememb",
"args": ["mcp"]
}
}
}2. Restart your IDE.
The agent can read stored context at session start, write durable memory when something changes, and search only when targeted recall is needed.
If you want rememb usage to stay consistent, add a rememb-specific instruction block in your IDE custom instructions or in the MCP client prompt that wraps the agent. The point is to make the agent route reads, writes, search, recovery, and maintenance through rememb instead of ad hoc prompt memory.
You can place that block in either of these places:
- IDE-level custom instructions
- the system prompt or instruction field of the MCP client that is calling rememb
In both cases, keep the scope explicit: these rules are about how the agent should use rememb, not about replacing the rest of your coding instructions.
For the exact copy-paste block, use the canonical rules section in MCP_TOOLS.md.
No extra storage setup, server config, or schema migration is required. In MCP mode, rememb resolves storage home-first and auto-initializes ~/.rememb when needed.
For the current public MCP tool list (17 tools) and descriptions, see MCP_TOOLS.md.
If you want multiple MCP clients on the same machine to reuse one already-running rememb process, start a persistent local SSE transport:
rememb mcp --transport sse --host 127.0.0.1 --port 8765This 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
Shortened. The full README is on GitHub.
Nothing above is checked by us. What we check is on the safety report.
Rememb: common questions
- Is Rememb MCP server safe?
- Yes, by our scan: it is graded A (92/100). Read the Rememb safety report
- How do I install Rememb?
- It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
- Does Rememb need an API key?
- Not as far as the registry entry and our scan can tell: no credentials are declared or required.
- Is Rememb maintained?
- The last commit was 53 days ago (2026-09-12). The latest release is v0.3.5.
- What can I use instead of Rememb?
- Servers from other publishers that do the same job: State Memory MCP server and Knowl MCP server.
- How does Rememb compare with other MCP servers?
- safety score 92/100 (higher than 95% of 48,255 servers); tools 7 (the typical server has 7); tools that change things 43% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.
Alternatives to Rememb
Same job from other publishers: the closest match first, then the best rated.
State Memory MCPPersistent workflow graph server tracking tasks, decisions, spatial entities, and blockers.not reviewedEstablishedA
KnowlPersistent memory for AI agents, for code, research and everyday life. Stale facts retire.not reviewedEstablishedA