原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Engram

作者:devinmlowe版本 0.5.0i★ –i在你的电脑上运行
注册名称io.github.devinmlowe/engram

安装

概览

作者提供的说明(英文原文)

Cognitive memory for coding agents: hybrid recall, remember/forget, knowledge graph, nightly dreams.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 搜索与 AI 记忆
  • 你需要填写:ENGRAM_MCP_TOKEN

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: ENGRAM_DB_PATH, ENGRAM_MCP_PORT, ENGRAM_MCP_TOKEN, ENGRAM_MCP_STANDALONE

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "engram": {
      "command": "npx",
      "args": [
        "-y",
        "@devinmlowe/engram",
        "mcp"
      ],
      "env": {
        "ENGRAM_DB_PATH": "your-value",
        "ENGRAM_MCP_PORT": "your-value",
        "ENGRAM_MCP_TOKEN": "your-value",
        "ENGRAM_MCP_STANDALONE": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add engram --env ENGRAM_DB_PATH=your-value --env ENGRAM_MCP_PORT=your-value --env ENGRAM_MCP_TOKEN=your-value --env ENGRAM_MCP_STANDALONE=your-value -- npx -y @devinmlowe/engram mcp

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "engram": {
      "command": "npx",
      "args": [
        "-y",
        "@devinmlowe/engram",
        "mcp"
      ],
      "env": {
        "ENGRAM_DB_PATH": "your-value",
        "ENGRAM_MCP_PORT": "your-value",
        "ENGRAM_MCP_TOKEN": "your-value",
        "ENGRAM_MCP_STANDALONE": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "engram": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@devinmlowe/engram",
        "mcp"
      ],
      "env": {
        "ENGRAM_DB_PATH": "your-value",
        "ENGRAM_MCP_PORT": "your-value",
        "ENGRAM_MCP_TOKEN": "your-value",
        "ENGRAM_MCP_STANDALONE": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • ENGRAM_DB_PATH env
    SQLite database path (default: /engram.db, i.e. ~/.local/share/engram/engram.db)
  • ENGRAM_MCP_PORT env
    Port of the optional engram HTTP daemon to bridge to (default 9907)
  • ENGRAM_MCP_TOKEN 机密 env
    Bearer token forwarded to the HTTP daemon when it requires one
  • ENGRAM_MCP_STANDALONE env
    Set to 1 to never bridge: always run the full server in-process

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 devinmlowe 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“搜索与 AI 记忆”中的其他服务器比较i

  • 星标数多于此分类中其他 7250 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 7250 个服务器的 46% 更新
  • 基础检查结果等于或优于此分类中其他 7250 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Engram 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

你需要填写:ENGRAM_MCP_TOKEN

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.5.0)于2个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:Context7, Codebase Memory, Exa

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Context7

作者:upstash

Up-to-date docs for AI agents

电脑或云端★ 64,224MIT今天更新
安装

Codebase Memory

作者:DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

在你的电脑上运行★ 48,148MIT20天前更新
安装

Exa

作者:exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

在云端运行★ 5,213MIT上个月更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Engram

*An engram is the hypothetical physical trace of memory in neural tissue — the biochemical change that encodes what we've learned.*

Local-first cognitive memory system that transforms raw LLM conversation history into structured, consolidated knowledge. Unlike traditional conversation search (which treats sessions as documents to retrieve), Engram mimics human memory architecture: episodic memories are captured, consolidated into semantic knowledge during "dream state" processing, and emergent connections surface through graph analysis — much like how a Zettelkasten's backlinks reveal Maps of Content that no individual note anticipated.

Designed as an MCP server for Claude Code and other LLM agents, with CLI and web visualization interfaces.

Install & first run

Prerequisites

  • Node.js 22 or newer (node --version)
  • macOS, Linux, or Windows for the CLI, MCP server, and web visualizer. Scheduled background consolidation ships an installer for each (launchd, systemd user timer, Task Scheduler); see the platform matrix below.
  • Claude Code if you want engram sync to ingest your conversation history from ~/.claude/projects
  • At least one LLM provider for extraction and dream consolidation (see Configuration). Search, remember, and the web visualizer work without one.

Quick start — three commands

npx @devinmlowe/engram preflight    # is this node/platform/arch/libc covered by prebuilt native modules? (fix per OS if not)

npm install -g @devinmlowe/engram # puts engram on your PATH; the postinstall hook runs the same preflight engram setup # doctor → init → sync (asked) → register every host present → install the three services → doctor --fix → one real extraction → summary

engram setup walks a bare install to running and ends by telling you which LLM tier did the extraction (extraction smoke: tier=ollama memories=3). Every step prints what it did and the manual command it stands for, so nothing is hidden. It installs all three services — the MCP HTTP daemon, the nightly dream timer and the web visualizer (port 3001, loopback) — by default (decision #62); --no-daemons or --daemons=mcp,dream narrows that, --host claude narrows host registration, --no-sync / --sync skip or force indexing, --no-smoke skips the extraction, --yes answers every question for scripts (the Linux loginctl enable-linger prompt is never implied), --json prints the result. With no LLM provider configured the dream timer is still installed and setup ends with [warn] dream timer installed but no LLM tier is reachable … naming the variables to set — exit 0; only a required doctor failure (or a failed init) exits 1. Later, engram doctor --fix repairs whatever is red — the service env file, a model cache inside node_modules, a missing Ollama model (asked first), a stopped MCP daemon, an unregistered host — printing the manual equivalent of each; a second run says nothing to fix. See CLI and docs/api-reference.md.

The same, by hand

engram mcp install claude           # registers engram with Claude Code (codex | cursor | hermes | --all); restart the host

engram mcp install edits the host's own config for you — ~/.claude.json (--project: .mcp.json), ~/.codex/config.toml, ~/.cursor/mcp.json, or deploys the Hermes plugin — atomically, with the previous content kept in .bak, never touching other servers, and re-running is a no-op. It prefers the HTTP daemon (http://127.0.0.1:9907/mcp) when GET /health answers and falls back to stdio (node …/dist/interfaces/cli/index.js mcp, which bridges to the daemon itself once one runs), printing which and why; --transport http|stdio overrides, --dry-run shows the path and diff. A daemon token is referenced as an environment variable (${ENGRAM_MCP_TOKEN} / bearer_token_env_var / ${env:ENGRAM_MCP_TOKEN}), never written; engram mcp status reports every host, whether it points at this install, whether its daemon answers and whether the variable resolves. See Registering hosts below.

From source

git clone https://github.com/devinmlowe/engram.git

cd engram node scripts/preflight.cjs # optional: the native-dependency verdict before anything is installed npm install # runs the same preflight as postinstall, then builds via the "prepare" script npm link # puts engram on your PATH (or run node dist/interfaces/cli/index.js directly)

Either way, continue with engram setup — or step by step:

engram preflight     # prebuilt / compiled locally / unsupported per native module, with the fix for this OS

engram doctor # node, platform/arch, native modules, model cache, ollama tier, llm providers, data dir, env file, install path, mcp daemon, hosts, extraction smoke — all [ok]? engram doctor --fix # apply the known remediations (env file, durable model cache, ollama pull with confirmation, start a stopped daemon, register a host) and re-check engram init # creates engram.db in the data dir (default ~/.local/share/engram; see Configuration) and downloads the embedding model engram sync # index conversations from ~/.claude/projects (optional) engram search "what did I decide about caching" engram mcp install --all # from a checkout: register every host present (~/.claude, ~/.codex, ~/.cursor, ~/.hermes) scripts/install-mcp-daemon.sh install; scripts/install-daemon.sh install; scripts/install-visualizer.sh install # the three services (what setup runs)

engram doctor ends with an extraction smoke line: one real extraction over your most recent conversation (or a bundled fixture when nothing is indexed yet) under a 60 s budget with a capped input, reporting tier= memories=N or every tier's reason when none answers. Memories it extracts from a real conversation are written like any other, stamped source=smoke (find them with engram memories list, remove them with forget); the fixture is never written. --no-smoke skips it; --strict exits 1 when any line is not [ok] (CI).

First run downloads models once. engram init (or the first search) pulls several hundred

MB of model weights into ~/.local/share/engram/models (or $ENGRAM_MODEL_CACHE_DIR /

$HF_HOME/hub), where they survive reinstalls and upgrades; see Model cache.

Set ENGRAM_RERANK_ENABLED=false to skip the reranker model.

Install as a Claude Code plugin (recommended)

No clone, no absolute paths. In Claude Code:

/plugin marketplace add devinmlowe/engram

/plugin install engram@engram

This repo is its own marketplace (.claude-plugin/marketplace.json); the plugin (.claude-plugin/plugin.json) runs the published npm package as a stdio MCP server — npx -y @devinmlowe/engram@ mcp, version pinned to the release — and adds the /engram:recall, /engram:remember, /engram:explore-graph, /engram:reflect and /engram:engram-connect commands (bundled from commands/; their tools are mcp__plugin_engram_engram__ ). /mcp should list engram with 16 tools; the first recall downloads the embedding model once (see the note above). The plugin updates through the marketplace (/plugin update engram@engram after a release); engram update keeps handling the CLI, daemons and the Hermes plugin.

The very first start is slow. The first npx run installs the package and its prebuilt

native modules into the npm cache — once per pinned version, then it is a cache hit. If Claude

Code reports the server timed out during that install, raise its startup timeout (milliseconds):

MCP_TIMEOUT=120000 claude. Two warm paths: npm install -g @devinmlowe/engram first, so the

package (and engram doctor/engram init) is already on the machine; or run the HTTP daemon

(scripts/install-mcp-daemon.sh install, below) — engram mcp then bridges to it and the host

process never opens the database or loads the model (see Transports).

Registering hosts (`engram mcp install`)

engram mcp install claude            # ~/.claude.json  (--project: ./.mcp.json)

engram mcp install codex # ~/.codex/config.toml (--project: ./.codex/config.toml) engram mcp install cursor # ~/.cursor/mcp.json (--project: ./.cursor/mcp.json) engram mcp install hermes # deploys interfaces/hermes-plugin to ~/.hermes (+ profiles that already have it) engram mcp install --all --dry-run # every host whose config dir exists; print path + unified diff, write nothing engram mcp status # registered? this install? daemon answering? ENGRAM_MCP_TOKEN resolving? engram mcp uninstall codex # removes only the engram entry; .bak keeps the previous content

Decisions: HTTP when the daemon answers /health, else stdio (#51); the token is referenced by environment variable and never written unless you pass --inline-token (#52). With the Claude Code plugin installed, mcp install claude skips the user-scope entry (it would register the server twice) unless --force; mcp status lists the plugin as a registered Claude host. A GUI-launched host does not inherit a fish/zsh login shell, so when the daemon requires a token mcp status prints the platform fix (launchctl setenv ENGRAM_MCP_TOKEN … on macOS, ~/.config/environment.d/ on Linux, setx on Windows). No host process is restarted, and the command needs no network beyond the loopback probe.

Manual configuration (if you would rather edit the file yourself)

Add the server to your Claude Code MCP config (~/.claude.json, or a project-level .mcp.json). From npm:

{

"mcpServers": { "engram": { "command": "npx", "args": ["-y", "@devinmlowe/engram", "mcp"] } } }

or, for a source checkout, point at the compiled server with an absolute path:

{

"mcpServers": { "engram": { "command": "node", "args": ["/absolute/path/to/engram/dist/interfaces/mcp/server.js"], "env": {} } } }

The .mcp.json shipped in this repo does the same thing with a repo-relative path and is picked up automatically when you open the engram checkout itself in Claude Code (it is for developing engram; the plugin does not use it).

Optional: background consolidation and visualization

./scripts/install-mcp-daemon.sh install  # MCP HTTP daemon on 127.0.0.1:9907 via launchd (what the Hermes plugin talks to)

./scripts/install-daemon.sh install # nightly engram dream at 02:00 via launchd ./scripts/install-visualizer.sh install # macOS launchd visualizer

On Linux the same scripts detect uname -s and install systemd *user* units instead (no root; loginctl enable-linger $USER if you want them to run while logged out):

./scripts/install-mcp-daemon.sh install  # renders systemd/engram-mcp.service, enables it (Restart=always)

./scripts/install-mcp-daemon.sh status # unit state, GET /health, effective data dir, last log lines ./scripts/install-daemon.sh install # renders systemd/engram-dream.{service,timer}, enables engram-dream.timer ./scripts/install-daemon.sh status # systemctl --user list-timers + last log lines ./scripts/install-daemon.sh run-now # systemctl --user start engram-dream.service

macOS/Linux: MCP HTTP daemon lifecycle

scripts/install-mcp-daemon.sh has the same six verbs as its Windows sibling (install, uninstall, start, `stop

只显示了开头部分;其余内容请在仓库中阅读

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