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remnic MCP工具
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MCP工具

remnic MCP工具

基于 TypeScript · 让 AI 助手直接操作你的系统与工具
英文名:remnic
⭐ 73 Stars 🍴 11 Forks 💻 TypeScript 📄 MIT 🏷 AI 7.5分
7.5AI 综合评分
记忆管理上下文保留AI智能体对话系统信息追溯
✦ AI Skill Hub 推荐

经 AI Skill Hub 精选评估,remnic MCP工具 获评「推荐使用」。这款MCP工具在功能完整性、社区活跃度和易用性方面表现出色,AI 评分 7.5 分,适合有一定技术背景的用户使用。

📚 深度解析

remnic MCP工具 是一款基于 MCP(Model Context Protocol)标准协议的 AI 工具扩展。MCP 协议由 Anthropic 开发并开源,旨在建立 AI 模型与外部工具之间的标准化通信接口,目前已被 Claude Desktop、Claude Code、Cursor 等主流 AI 工具采纳。

通过安装 remnic MCP工具,你的 AI 助手将获得额外的工具调用能力,可以用自然语言直接操控该工具的功能,无需学习复杂的命令行语法。MCP 工具的核心价值在于"一次配置,永久增强"——配置完成后,每次与 AI 对话时都可以无缝调用这些工具。

在技术实现上,MCP 工具通过标准的 JSON-RPC 协议与 AI 客户端通信,工具的功能以"工具列表"的形式暴露给 AI 模型,AI 可以按需调用。remnic MCP工具 提供了结构化的工具调用接口,使 AI 模型能够精确地理解和使用每个功能点,显著降低 AI 在工具使用上的错误率。

与传统的 API 集成相比,MCP 工具的优势在于无需编写代码——用户只需在配置文件中添加几行 JSON,即可让 AI 获得全新能力。AI Skill Hub 将 remnic MCP工具 评为 AI 评分 7.5 分,属于同类工具中的优质选择。

📋 工具概览

remnic MCP工具 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。

GitHub Stars
⭐ 73
开发语言
TypeScript
支持平台
Windows / macOS / Linux
维护状态
轻量级项目,按需更新
开源协议
MIT
AI 综合评分
7.5 分
工具类型
MCP工具
Forks
11

📖 中文文档

以下内容由 AI Skill Hub 根据项目信息自动整理,如需查看完整原始文档请访问底部「原始来源」。

remnic MCP工具 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。

📌 核心特色
  • 通过标准 MCP 协议与 Claude、Cursor 等主流 AI 客户端深度集成
  • 提供结构化工具调用接口,显著降低 AI 集成复杂度
  • 支持 Claude Desktop 和 Claude Code 无缝接入,开箱即用
  • 可与其他 MCP 工具组合叠加,构建完整 AI 工作站
  • 轻量无侵入设计,不影响现有系统架构
🎯 主要使用场景
  • 在 Claude Desktop 对话中直接调用本地工具,实现 AI 与系统的深度联动
  • 通过自然语言驱动复杂的多步骤自动化任务,代替繁琐手动操作
  • 将多个 MCP 工具组合使用,构建个人专属 AI 工作站
以下安装命令基于项目开发语言和类型自动生成,实际以官方 README 为准。
安装命令
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/joshuaswarren/remnic

# 方式二:手动配置 claude_desktop_config.json
{
  "mcpServers": {
    "remnic-mcp--": {
      "command": "npx",
      "args": ["-y", "remnic"]
    }
  }
}

# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
📋 安装步骤说明
  1. 确认已安装 Node.js(v18 或以上版本)
  2. 打开 Claude Desktop 或 Claude Code 的 MCP 配置文件
  3. 按「交给 Agent 安装 → Claude Desktop」标签中的 JSON 配置填入 mcpServers 字段
  4. 保存配置文件并重启 Claude 客户端
  5. 重启后,在对话中即可使用本工具
以下用法示例由 AI Skill Hub 整理,涵盖最常见的使用场景。
常用命令 / 代码示例
# 安装后在 Claude 对话中直接使用
# 示例:
用户: 请帮我用 remnic MCP工具 执行以下任务...
Claude: [自动调用 remnic MCP工具 MCP 工具处理请求]

# 查看可用工具列表
# 在 Claude 中输入:"列出所有可用的 MCP 工具"
以下配置示例基于典型使用场景生成,具体参数请参照官方文档调整。
配置示例
// claude_desktop_config.json 配置示例
{
  "mcpServers": {
    "remnic_mcp__": {
      "command": "npx",
      "args": ["-y", "remnic"],
      "env": {
        // "API_KEY": "your-api-key-here"
      }
    }
  }
}

// 保存后重启 Claude Desktop 生效
📑 README 深度解析 真实文档 完整度 89/100 查看 GitHub 原文 →
以下内容由系统直接从 GitHub README 解析整理,保留代码块、表格与列表结构。

Remnic

npm version License: MIT Sponsor

Open-source memory and context for user-aware agents.

Remnic is for agents that need to understand the people they work with over time.

Remnic helps AI agents understand the people they work with: their preferences, projects, constraints, decisions, patterns, and definition of good. The goal is simple: agents that remember responsibly, retrieve the right context, and ask fewer unnecessary questions.

Remnic is not just a memory store. It is an exploration of the systems layer around user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, and evals.

Features

Quick install (OpenClaw)

If you have OpenClaw installed, the fastest path to working Remnic memory is:

```bash

1. Install the plugin package

openclaw plugins install clawhub:@remnic/plugin-openclaw

Installation

Option 1: Install from the CLI

openclaw plugins install clawhub:@remnic/plugin-openclaw

Option 2: Ask your OpenClaw agent to install it

Tell any OpenClaw agent:

Install the @remnic/plugin-openclaw plugin and configure it as my memory system.

Your agent will run the install command, update openclaw.json, and restart the gateway for you.

Option 3: Developer install from source

git clone https://github.com/joshuaswarren/remnic.git \
  ~/.openclaw/extensions/remnic
cd ~/.openclaw/extensions/remnic
pnpm install && pnpm run build
Note: This repo uses pnpm workspaces. npm ci / npm install will fail on workspace: specifiers. Install pnpm first: npm install -g pnpm.

Verify installation

remnic doctor              # Health diagnostics with remediation hints
remnic connectors doctor   # Connector-specific health checks
remnic status              # Daemon status and local endpoint summary

Setup & diagnostics

openclaw engram setup # Guided first-run setup openclaw engram doctor # Health diagnostics with remediation hints openclaw engram config-review # Config tuning recommendations openclaw engram stats # Memory counts, search status openclaw engram inventory # Full storage and namespace inventory

Standalone Usage

Remnic also works as a standalone tool without OpenClaw. Install and run the CLI directly:

npm install -g @remnic/cli
remnic init                     # create remnic.config.json
export OPENAI_API_KEY=sk-...
export REMNIC_AUTH_TOKEN=$(openssl rand -hex 32)
remnic daemon start             # start background server
remnic query "hello"            # verify

The CLI provides 15+ commands for querying, onboarding projects, curating files, managing spaces, running benchmarks, and more. See the full CLI reference for all commands.

Trust-zone demos

openclaw engram trust-zone-demo-seed --dry-run # Preview the opt-in buyer demo dataset openclaw engram trust-zone-demo-seed --scenario agentic-commerce-v1 --dry-run openclaw engram trust-zone-demo-seed # Explicitly seed the demo dataset openclaw engram trust-zone-promote --record-id <id> --target-zone working --reason "Operator review" ```

Option 4: Standalone (no OpenClaw)

From npm (recommended):

npm install -g @remnic/cli      # Installs `remnic` plus the legacy `engram` forwarder
remnic init                     # Create remnic.config.json
export OPENAI_API_KEY=sk-...
export REMNIC_AUTH_TOKEN=$(openssl rand -hex 32)
remnic daemon start             # Start background server
remnic status                   # Verify it's running
remnic query "hello" --explain  # Test query with tier breakdown

From source (requires Node.js 22.12+ and pnpm):

git clone https://github.com/joshuaswarren/remnic.git
cd remnic
pnpm install && pnpm run build
cd packages/remnic-cli && pnpm link --global  # Makes `remnic` and `engram` available on PATH
cd ../..
remnic init                     # Create remnic.config.json
export OPENAI_API_KEY=sk-...
export REMNIC_AUTH_TOKEN=$(openssl rand -hex 32)
remnic daemon start             # Start background server
remnic status                   # Verify it's running
remnic query "hello" --explain  # Test query with tier breakdown
Note: remnic is the canonical CLI. The legacy engram binary is a compatibility forwarder to the same implementation. Running pnpm link --global from packages/remnic-cli/ (not the repo root) makes both names available on PATH. Alternatively, invoke directly: npx tsx packages/remnic-cli/src/index.ts <command>.

The standalone CLI provides 15+ commands for memory management, project onboarding, curation, diff-aware sync, dedup, connectors, spaces, and benchmarks -- all without requiring OpenClaw. See the Platform Migration Guide for the full command reference.

Option 5: Connect Other AI Agents

Once the Remnic daemon is running, connect any supported agent:

remnic connectors install claude-code   # Claude Code (hooks + MCP)
remnic connectors install codex-cli     # Codex CLI (hooks + MCP + memory extension)
remnic connectors install pi            # Pi Coding Agent (extension + MCP + compaction)
remnic connectors install replit        # Replit (MCP only)
pip install --upgrade remnic-hermes     # Hermes Agent (Python MemoryProvider)
remnic connectors install hermes        # Writes Hermes config + token

For Codex CLI, installation also drops a phase-2 memory extension at <codex_home>/memories_extensions/remnic/instructions.md so Codex's consolidation sub-agent auto-discovers Remnic. Opt out with --config installExtension=false if you prefer to manage Codex extensions yourself.

For Pi Coding Agent, installation writes an auto-discovered extension under ~/.pi/agent/extensions/remnic/. The extension recalls context before turns, observes Pi messages and tool activity into Remnic/LCM, exposes Remnic MCP tools as Pi tools, and coordinates session_before_compact with Remnic LCM flush/checkpoint recording. See docs/integration/pi.md.

Each connector generates a unique auth token, installs the appropriate plugin/hooks, and verifies the connection. All agents share the same memory store — tell one agent your preference, and every agent remembers it.

Hermes uses Remnic as a Hermes MemoryProvider, not a context_engine. Automatic recall runs in pre_llm_call, observations run after each turn, and the provider now registers the full Remnic parity tool surface (remnic_lcm_search, recall explain/X-ray, memory CRUD, continuity, identity, governance, work-board, shared-context, compounding, day-summary, briefing, checkpoint, and profiling tools) plus legacy engram_* aliases. Lossless Context Management is delivered through the daemon recall envelope when lcmEnabled is on; no Hermes context_engine registration is required. See docs/plugins/hermes.md for the full reference.

PlatformIntegrationAuto-recallAuto-observe
**OpenClaw**Memory slot pluginEvery sessionEvery response
**Claude Code**Native hooks + MCPEvery promptEvery tool use
**Codex CLI**Native hooks + MCPEvery promptEvery tool use
**Pi Coding Agent**Native extension + MCPEvery turnEvery turn
**Hermes**Python MemoryProviderEvery LLM callEvery turn
**Replit**MCP onlyOn demandOn demand

Configure

After installation, add the Remnic bridge plugin to your openclaw.json:

{
  "plugins": {
    "allow": ["openclaw-remnic"],
    "slots": { "memory": "openclaw-remnic" },
    "entries": {
      "openclaw-remnic": {
        "enabled": true,
        "hooks": {
          "allowConversationAccess": true
        },
        "config": {
          // Recommended for OpenClaw: use the gateway model chain.
          "modelSource": "gateway",
          "gatewayAgentId": "remnic-llm",
          "fastGatewayAgentId": "remnic-llm-fast",

          // Optional: Use Remnic's local LLM path (plugin mode only; no API key needed):
          // "openaiApiKey": false,
          // "localLlmEnabled": true,
          // "localLlmUrl": "http://localhost:1234/v1",
          // "localLlmModel": "qwen2.5-32b-instruct"

          // Optional: Use OpenAI directly (plugin mode only):
          // "modelSource": "plugin",
          // "openaiApiKey": "${OPENAI_API_KEY}"
        }
      }
    }
  }
}
Gateway model source: When modelSource is "gateway", Remnic routes all LLM calls (extraction, consolidation, reranking) through an OpenClaw agent persona's model chain instead of its own config. Extraction starts on the gatewayAgentId chain directly in this mode; localLlm* settings do not control primary extraction order. Define agent personas in openclaw.json → agents.list[] with a primary model and fallbacks[] array — Remnic tries each in order until one succeeds. This lets you build multi-provider fallback chains like Fireworks → local LLM → cloud OpenAI. See the Gateway Model Source guide for full setup.

Restart the gateway:

```bash launchctl kickstart -k gui/$(id -u)/ai.openclaw.gateway # macOS

ChatGPT (OpenAI data export: saved memories + optional conversation summaries)

npm install -g @remnic/import-chatgpt remnic import --adapter chatgpt --file ~/chatgpt-export/memory.json --dry-run

Then (after enabling sources in config):

remnic wearables sync --days 7 remnic wearables transcript --date 2026-06-10 remnic wearables search "that solar quote" remnic wearables memories --source limitless --date 2026-06-10 ```

Memory creation defaults to smart mode — a fully automated trust pipeline: every candidate runs through Remnic's LLM extraction judge, gets a per-source transcription-quality prior, and earns corroboration boosts when a second wearable recorded the same content or an existing memory supports it. High-trust facts are written active, borderline facts go to the review queue, ASR garbage is dropped — and the trust evidence (score, judge verdict, corroborating sources) persists on every memory. Tune per source with sourceTrust, autoApproveTrust, reviewTrust, and maxMemoriesPerDay, or pick review/auto/off. MCP tools (remnic.transcript_day, remnic.transcript_search, remnic.transcript_memories, remnic.wearables_sync, remnic.wearables_statusengram.* aliases included) and HTTP routes expose the same surface to agents.

See docs/wearables.md for the full pipeline, configuration reference, speaker labeling, corrections, redaction, and per-provider setup.

mem0 (REST API — paginated; honors --rate-limit)

npm install -g @remnic/import-mem0 export MEM0_API_KEY=... remnic import --adapter mem0 --rate-limit 2

HTTP API

remnic daemon start

Key endpoints: GET /engram/v1/health, POST /engram/v1/recall, POST /engram/v1/memories, GET /engram/v1/entities/:name, and more. Full reference in API docs.

The HTTP server also hosts a lightweight operator UI at http://127.0.0.1:4318/engram/ui/ for memory browsing, recall inspection, governance review, trust-zone promotion, and entity exploration.

CLI Reference

```bash

Omi necklace (integration app: appId + uid + sk_ key)

npm install -g @remnic/connector-omi export OMI_API_KEY=...

Package Architecture

@remnic/core            — Framework-agnostic engine (re-exports orchestrator, config, storage, search, extraction, graph, trust zones)
@remnic/cli             — Standalone CLI binary (15+ commands)
@remnic/server          — Standalone HTTP/MCP server
@remnic/bench           — Benchmarks + CI regression gates
@remnic/hermes-provider — HTTP client for remote Remnic instances

Integrations & Extensions

  • Codex Marketplace — Install Remnic via codex marketplace add joshuaswarren/remnic. Marketplace manifest at repo root. (issue #418)
  • Memory Extension Publisher Contract — Pluggable contract for installing host-specific instruction files into any AI agent host's extension directory. Generalizes the pattern previously hard-coded for Codex. (issue #381)
  • Memory Extension Discovery — Third-party memory extensions provide structured instructions that influence consolidation, auto-discovered from extension directories. (issue #382)

Trust-zone demo workflow

Trust zones now ship with a dedicated admin-console view plus an explicit demo seeding path for buyer-facing walkthroughs.

  • Never automatic — Remnic does not seed sample trust-zone records on install, startup, or feature enablement.
  • Explicit only — demo records appear only after you run openclaw engram trust-zone-demo-seed or trigger the matching admin-console action.
  • Buyer-friendly story — the trust-zone view surfaces provenance strength, promotion readiness, corroboration requirements, and operator promotion actions in one place.

The default scenario is enterprise-buyer-v1, which creates a small, opinionated dataset covering:

  • quarantine records that are ready for review
  • working records that are blocked on missing provenance
  • working records that still need corroboration
  • work

Troubleshooting: hooks aren't firing

Symptom: Remnic appears installed but no memories are created. The gateway log shows no [remnic] lines after conversations.

Root cause: OpenClaw gates memory plugins on plugins.slots.memory. If this slot is not set to the plugin's id, OpenClaw skips register(api) entirely — no hooks fire, no memory is stored or recalled.

🇨🇳 中文文档镜像 AI 翻译 2026-05-30
英文原文章节由系统翻译为中文摘要,便于快速理解。完整原文见上方 "📑 README 深度解析"。
📌 简介

Remnic 是一个开源的内存和上下文管理系统,用于为用户感知的智能代理提供内存和上下文。它适用于需要了解人类行为和意图的智能代理。

⚡ 功能介绍

Remnic 的功能包括内存管理、上下文管理、智能代理连接、数据整合和分析等。

🛠 安装步骤(Docker/pip/源码)

快速安装 (OpenClaw):如果您已经安装了 OpenClaw,则可以使用以下命令快速安装 Remnic 内存:openclaw plugins install clawhub:@remnic/plugin-openclaw

🚀 使用教程

Remnic 可以作为一个独立工具使用,也可以与 OpenClaw 集成。独立使用方法:npm install -g @remnic/cli remnic init # 创建 remnic.config.json export OPENAI_API_KEY=sk-... export REMNIC_AUTH_TOKEN=$(openssl rand -hex 32) remnic daemon start # 启动后台服务器 remnic query "hello" # 验证

⚙️ 配置说明(含 MCP / env)

Remnic 支持多种配置方式,包括环境变量、MCP 和关键参数。例如:export OPENAI_API_KEY=sk-... export REMNIC_AUTH_TOKEN=$(openssl rand -hex 32)

🔌 API 说明

Remnic 提供 REST API 和 HTTP API 两种接口方式。REST API 支持分页和限速功能,HTTP API 支持健康检查、回忆、记忆和实体查询等功能。

🔄 工作流/模块

Remnic 的包架构包括 @remnic/core(框架无关的引擎)、@remnic/cli(独立 CLI 二进制)、@remnic/server(独立 HTTP/MCP 服务器)等模块。

❓ FAQ 摘要

常见问题包括:Remnic 安装后 hooks 没有激活。解决方法:检查 OpenClaw 的配置,确保 plugins.slots.memory 设置为插件的 ID。

🎯 aiskill88 AI 点评 B 级 2026-05-21

创新的AI智能体记忆解决方案,提供用户感知和溯源特性。文档和社区支持有限,适合有技术深度的开发者探索。

📚 实用指南(长尾问题)
适合谁
  • 需要 remnic 解决具体问题的开发者与运营人员
最佳实践
  • 先在测试环境跑通最小用例,再接入生产数据
常见错误
  • API key 直接提交到 git 仓库(请用 .env 并加入 .gitignore)
部署方案
  • 云端托管:可放在 Vercel / Railway / Fly.io 等 PaaS 平台
相关搜索
remnic 中文教程remnic 安装报错怎么办remnic 与同类工具对比remnic 最佳实践remnic 适合谁用

⚡ 核心功能

👥 适合谁
  • 需要 remnic 解决具体问题的开发者与运营人员
⭐ 最佳实践
  • 先在测试环境跑通最小用例,再接入生产数据
⚠️ 常见错误
  • API key 直接提交到 git 仓库(请用 .env 并加入 .gitignore)

👥 适合人群

Claude Desktop / Claude Code 用户AI 工具开发者需要扩展 AI 能力的专业人士自动化工程师

🎯 使用场景

  • 在 Claude Desktop 对话中直接调用本地工具,实现 AI 与系统的深度联动
  • 通过自然语言驱动复杂的多步骤自动化任务,代替繁琐手动操作
  • 将多个 MCP 工具组合使用,构建个人专属 AI 工作站

⚖️ 优点与不足

✅ 优点
  • +MIT 协议,可免费商用
  • +标准化 MCP 协议,生态互联性强
  • +与 Claude 官方生态无缝对接
  • +即插即用,配置简单快捷
⚠️ 不足
  • 依赖 Claude 客户端,非 Claude 用户无法使用
  • MCP 协议仍在持续演进,接口可能变更
  • 需要一定的配置步骤
⚠️ 使用须知

AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。

建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。

📄 License 说明

✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。

🔗 相关工具推荐

📚 相关教程推荐
📰 相关 AI 新闻
🍿 AI 圈相关吃瓜
🗺️ 相关解决方案
🧩 你可能还需要
基于当前 Skill 的能力图谱,自动补全的工具组合

❓ 常见问题 FAQ

提供作用域隔离、信息来源追溯和用户感知能力,确保记忆的准确性和可控性
💡 AI Skill Hub 点评

AI Skill Hub 点评:remnic MCP工具 的核心功能完整,质量良好。对于Claude Desktop / Claude Code 用户来说,这是一个值得纳入个人工具库的选择。建议先在非生产环境试用,再逐步推广。

⬇️ 获取与下载
⬇ 下载源码 ZIP

✅ MIT 协议 · 可免费商用 · 直接从 aiskill88 服务器下载,无需跳转 GitHub

📚 深入学习 remnic MCP工具
查看分步骤安装教程和完整使用指南,快速上手这款工具
🌐 原始信息
原始名称 remnic
原始描述 开源MCP工具:Open-source memory and context for user-aware agents: scoped memory, provenance,。⭐73 · TypeScript
Topics 记忆管理上下文保留AI智能体对话系统信息追溯
GitHub https://github.com/joshuaswarren/remnic
License MIT
语言 TypeScript
🔗 原始来源
🐙 GitHub 仓库  https://github.com/joshuaswarren/remnic

收录时间:2026-05-16 · 更新时间:2026-05-21 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。

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