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psyXe MCP Server

作者:bjenkinsgit版本 0.1.10i★ –i在你的电脑上运行
注册名称io.github.bjenkinsgit/psyxe-mcp

安装

概览

作者提供的说明(英文原文)

Apple Notes, Reminders, and Contacts for AI assistants. BERT semantic search. macOS.

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: 文档、表格与办公

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)。
  • 注册中心没有列出需要填写的密钥。

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 …”。

下载作者的 .mcpb 文件

链接指向作者自己的文件;我们不托管也不重新打包它。打开文件后,Claude Desktop 会进行安装。

在终端中运行这条命令

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。

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。

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 bjenkinsgit 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“文档、表格与办公”中的其他服务器比较i

  • 星标数多于此分类中其他 2191 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 2191 个服务器的 6% 更新
  • 基础检查结果等于或优于此分类中其他 2191 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

psyXe MCP Server 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?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

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(0.1.10)于7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 MCPB。

有什么可以替代它?

同一分类中有:Agent-Native Calendar, Excel MCP Server, MCP Server for Excel

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

Agent-Native Calendar

作者:BuilderIO

Agent-Native Google Calendar - manage events, sync, and public booking

在云端运行★ 7,620MIT2个月前更新
安装

Excel MCP Server

作者:haris-musa

Create and edit Excel files with AI: charts, PivotTables, formulas. No Excel needed.

在你的电脑上运行★ 4,276MIT6天前更新
安装

MCP Server for Excel

作者:sbroenne

Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.

在你的电脑上运行★ 847MIT3天前更新
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。

psyXe MCP Server

An MCP server that gives AI assistants access to your Apple Notes, Reminders, and Contacts — with optional BERT-powered semantic search.

All tools run locally via macOS-native APIs (AppleScript, EventKit, Contacts framework). No data leaves your Mac. No API keys required.

New to MCP? Check out the FAQ for answers to common questions about what this is, whether it works with your setup, and how your data stays private.

Video Tutorials

Apple Notes & Semantic Search — Connect your AI to Apple Notes with BERT-powered semantic search
Apple Contacts — Search, create, and manage contacts from your AI assistant
Apple Reminders — Full CRUD for reminders and lists via any MCP client
Access Control — Configure exactly which data your AI can access

What Can It Do?

CategoryToolsDescription
Notessearch_notes, list_notes, get_note, open_note, notes_tags, notes_search_by_tag, notes_indexSearch, browse, and read Apple Notes
Notes (Semantic)notes_semantic_search, notes_smart_search, notes_rebuild_index, notes_index_statsBERT-powered semantic search across all your notes
Reminderslist_reminder_lists, search_reminders, list_reminders, get_reminder, create_reminder, create_reminders_batch, complete_reminder, delete_reminder, edit_reminder, edit_reminders_batch, open_reminders, create_reminder_list, delete_reminder_listFull CRUD for Apple Reminders
Contactslist_contact_groups, search_contacts, list_contacts, get_contact, create_contact, edit_contact, delete_contactSearch and manage Apple Contacts
Filesfile_search, read_file, write_fileSearch and read/write files in granted folders

Install

Homebrew (recommended)
brew tap bjenkinsgit/tap

brew install psyxe-mcp

This installs everything — binary, Swift helpers, FFmpeg, and the BERT model. No compilation required.

Build from Source
git clone https://github.com/bjenkinsgit/psyxe-mcp.git

cd psyxe-mcp ./build.sh

The build script handles everything automatically:

  • Installs Homebrew, Rust, FFmpeg, and pkg-config if missing
  • Builds the MCP server binary (Rust)
  • Builds Swift helpers for Reminders and Contacts
  • Copies helpers next to the binary
  • Pre-downloads the BERT model (~90MB) so first search is instant

Build without semantic search (skips FFmpeg and BERT):

./build.sh --no-memvid

Requirements: macOS 12+ (Monterey or later). Xcode Command Line Tools will be prompted if not installed.

The binary and helpers are in target/release/. Use the full path when configuring your MCP client.

Install Apple Shortcuts (optional)

Two shortcuts enable linking Reminders to file artifacts:

./install-shortcuts.sh

This opens each shortcut in Shortcuts.app for you to approve.

Configure Your MCP Client

If you installed via Homebrew, the command is just psyxe-mcp (it's in your PATH). If you built from source, use the full path: /Users/yourname/src/psyxe-mcp/target/release/psyxe-mcp.

Claude Code (CLI)
claude mcp add psyxe -- psyxe-mcp

Or edit ~/.claude/claude_mcp_config.json:

{

"mcpServers": { "psyxe": { "command": "psyxe-mcp" } } }

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json:

{

"mcpServers": { "psyxe": { "command": "psyxe-mcp" } } }

Cursor

Open Settings → MCP Servers → Add new server:

{

"psyxe": { "command": "psyxe-mcp" } }

Windsurf

Edit ~/.codeium/windsurf/mcp_config.json:

{

"mcpServers": { "psyxe": { "command": "psyxe-mcp" } } }

OpenAI Codex CLI

Edit ~/.codex/config.toml:

[mcp_servers.psyxe]

command = "psyxe-mcp"

Note: If you built from source instead of using Homebrew, replace psyxe-mcp with the full path to the binary (e.g., /Users/yourname/src/psyxe-mcp/target/release/psyxe-mcp).

Access Control

By default, the MCP server has full access to all your Notes, Reminders, Contacts, and files. To restrict what your AI can see, use the built-in access control CLI to create and manage ~/.psyxe/access.toml.

No manual file editing is needed — the CLI creates the file with secure permissions (owner-only read/write) on first use.

Quick Start
# 1. See what's available

psyxe-mcp access discover reminders psyxe-mcp access discover notes

2. Grant access to only what the AI should see

psyxe-mcp access grant reminders "Work" psyxe-mcp access grant notes "Projects"

3. Verify your restrictions

psyxe-mcp access list

Once any rule is set for a category, only explicitly granted resources are accessible — everything else in that category is denied.

Discover What's Available
# See your reminder lists

psyxe-mcp access discover reminders

See your contact groups

psyxe-mcp access discover contacts

See your note folders

psyxe-mcp access discover notes

See common file locations

psyxe-mcp access discover files

Grant / Revoke Access
# Only allow access to specific reminder lists

psyxe-mcp access grant reminders "Work" psyxe-mcp access grant reminders "Shopping" --rw # read-write

Only allow access to a specific contact group

psyxe-mcp access grant contacts "iCloud"

Only allow access to specific note folders

psyxe-mcp access grant notes "Projects"

Grant file access to a folder

psyxe-mcp access grant files "/Users/you/Documents" --rw

Revoke access

psyxe-mcp access revoke reminders "Shopping"

See current restrictions

psyxe-mcp access list

Remove all restrictions (restore full access)

psyxe-mcp access reset

Access rules are stored in ~/.psyxe/access.toml with owner-only permissions (chmod 600). The server refuses to load the config if it is group- or world-readable, preventing other processes from tampering with access rights.

Semantic Search

When built with the memvid feature (enabled by default), the server includes BERT-powered semantic search for Apple Notes. This uses memvid-rs to encode your notes into a searchable vector index.

First Use

The first time you (or your AI assistant) run a semantic search, the server will build an index of all your notes. This takes a few minutes depending on how many notes you have. Subsequent searches are instant.

# Or ask your AI assistant: "search my notes for machine learning concepts"

It will automatically build the index on first use.

How It Works
  1. All notes are fetched from Notes.app
  2. Each note is chunked and encoded with a BERT model (384-dimensional embeddings)
  3. Chunks are stored as QR codes in a ProRes video file (compact, durable archive)
  4. A vector index (HNSW) enables instant semantic similarity search
  5. The index auto-detects when notes change and prompts for rebuild
Try It Out

We've included sample notes designed to showcase semantic search:

# Load 10 sample notes into Apple Notes

./examples/load-sample-notes.sh

Then ask your AI assistant to rebuild the index and try queries like:

"retirement savings" → finds Tax Strategy (never mentions "retirement")

"Italian cooking" → finds Carbonara recipe (never says "Italian")

See examples/sample-notes.md for the full list of demo queries.

Choosing a Different BERT Model

The default model (sentence-transformers/all-MiniLM-L6-v2, 384 dimensions) balances speed and quality. You can swap in any HuggingFace BERT-family sentence-transformer model.

Via environment variable:

MEMVID_MODEL_NAME=BAAI/bge-small-en-v1.5 target/release/psyxe-mcp warmup

Via config file — create memvid_config.toml in the repo root or next to the binary:

[ml]

model_name = "BAAI/bge-small-en-v1.5"

After changing models, rebuild the index (ask your AI assistant or run warmup again).

Popular alternatives:

ModelDimensionsTrade-off
sentence-transformers/all-MiniLM-L6-v2384Default. Fast, good quality
BAAI/bge-small-en-v1.5384Retrieval-optimized, slightly better for search
sentence-transformers/all-mpnet-base-v2768Higher quality, ~2x slower
BAAI/bge-base-en-v1.5768Best retrieval quality, needs query prefix

For instruction-tuned models (like BGE), add query/document prefixes:

[ml]

model_name = "BAAI/bge-small-en-v1.5" embedding_query_prefix = "Represent this sentence for searching relevant passages: " embedding_document_prefix = ""

Remote Embedding API

Use any OpenAI-compatible embedding endpoint instead of local BERT:

[ml]

embedding_provider = "remote"

Then set the endpoint via environment variables:

export EMBEDDING_API_URL="http://localhost:11434/v1/embeddings"  # Ollama

export EMBEDDING_API_MODEL="nomic-embed-text"

Works with OpenAI, Ollama, vLLM, LM Studio, or any OpenAI-compatible endpoint.

Without Semantic Search

Build without memvid to skip the FFmpeg/BERT dependency entirely (no brew install needed):

cargo build --release --no-default-features

Notes tools still work — they fall back to AppleScript-based text search. All other tools (Reminders, Contacts, Files) are unaffected.

macOS Permissions

On first use, macOS will prompt you to grant permission for:

  • Notes — "osascript" wants to access Notes
  • Reminders — "reminders-helper" wants to access Reminders
  • Contacts — "contacts-helper" wants to access Contacts

Approve these in the dialog that appears. You can review/revoke them later in System Settings → Privacy & Security.

Architecture

┌─────────────────┐     stdio (JSON-RPC)     ┌──────────────┐

│ Claude Code / │ ◄─────────────────────► │ psyxe-mcp │ │ Claude Desktop │ │ (MCP server) │ └─────────────────┘ └──────┬───────┘ │ ┌────────────────┼────────────────┐ ▼ ▼ ▼ ┌────────────┐ ┌─────────────┐ ┌───────────┐ │ AppleScript │ │ Swift Helper│ │ memvid │ │ (Notes) │ │ (EventKit, │ │ (BERT + │ │ │ │ Contacts) │ │ ProRes) │ └──────┬──────┘ └──────┬──────┘ └─────┬─────┘ ▼ ▼ ▼ ┌────────────┐ ┌─────────────┐ ┌───────────┐ │ Notes.app │ │ EventKit │ │ NoteStore │ │ │ │ Contacts │ │ SQLite │ └────────────┘ └─────────────┘ └───────────┘

The MCP server is a thin stdio bridge. All the real work happens in psyxe-mcp-core, the open-source library that provides direct access to macOS-native APIs.

Configuration

Semantic Search (memvid)

Place a `memvid_config.to

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