Tilde

io.github.topskychen由 GitHub 账号 topskychen 发布v0.1.1更新于 Oct 24, 2026

Your AI agents' home directory — privacy-first MCP server for portable AI identity.

已验证STDIO仅桌面效率与工作流知识与记忆

概览

AI 生成的概览

本地运行的 MCP 服务器,为 AI 助手提供可移植的个人档案——身份、技术栈、知识、技能与团队上下文,数据保存在本机。

可以做什么
读取完整或部分的用户档案,涵盖身份、技术栈、知识来源、技能、工作经历、教育背景、项目与发表成果,以及团队上下文和编码规范,通过资源和 get_profile、get_team_context 等工具提供。提交档案更新建议,进入待用户审批的队列,并列出待审批的更新。通过命令行管理 Anthropic SKILL.md 格式的技能,可设为公开、私有或团队可见。导入文档、书籍或简历以提取要点并初始化档案,支持试运行和自动批准。可选择 YAML、SQLite 或 Mem0 存储后端,并导出档案。
适用场景
适合在多个支持 MCP 的助手之间切换、希望每处都能获得相同个人与团队上下文而无需重复输入的用户。也适合希望把偏好、技能和编码规范共享给智能体、同时让数据留在本地并自行审批改动的开发者。
运行要求
以 stdio 本地进程运行,可从 npm(tilde-ai)或 PyPI(tilde-ai)安装;README 在客户端配置中使用 npx tilde-ai。需先初始化档案。文档导入和语义搜索需要 GOOGLE_API_KEY(主要)以及可选的 OPENAI_API_KEY,通过环境变量设置。可选设置包括 TILDE_STORAGE、TILDE_PROFILE、TILDE_LLM_MODEL 和 TILDE_EMBEDDING_MODEL。仅支持桌面客户端。
安装前请注意
档案包含姓名、工作经历、教育背景和技能等个人数据,存放在 ~/.tilde 下,任何已连接的智能体都可读取;标记为私有的技能会被过滤,但仍应留意所存内容。智能体可以提交档案修改建议,应逐条谨慎审批。文档导入会把内容发送给所配置的 LLM 服务商(Google 或 OpenAI),使用 GOOGLE_API_KEY 或 OPENAI_API_KEY。团队同步可从 URL 或 git 仓库拉取配置。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Tilde,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

🏠 tilde

Your AI agents' home directory

tilde is a privacy-first Model Context Protocol (MCP) server that acts as the universal memory and profile layer for AI Agents.

Configure once. Use everywhere. Your data, your control.

Supports profile management, skills, resume import, and team sync.

The Problem

Every time you switch AI tools, you face the same issues:

  • 🔄 Repetition: "I'm a Senior SWE", "I prefer Python", "Don't use ORMs"
  • 🧩 Fragmentation: Preferences learned in Cursor aren't available in Claude
  • 🔒 Privacy Concerns: Unsure who has access to your personal context

The Solution

tilde acts as a "digital passport" that your AI agents can read:

┌────────────────────────────────────────────────────────────┐│  Claude Desktop  │   Cursor   │  Windsurf  │  Your Agent   │└────────┬─────────┴─────┬──────┴─────┬──────┴───────┬───────┘         │               │            │              │         └───────────────┴─────┬──────┴──────────────┘                               │                    ┌──────────▼──────────┐                    │   tilde MCP Server  │                    │   (runs locally)    │                    └──────────┬──────────┘                               │                    ┌──────────▼──────────┐                    │   ~/.tilde/profile  │                    │   (your data)       │                    └─────────────────────┘

Features

  • 🏠 Local-First: Your data stays on your machine by default
  • 📋 Structured Profiles: Identity, tech stack, knowledge, skills
  • 🔌 MCP Standard: Works with any MCP-compliant agent
  • ✏️ Human-in-the-Loop: Agents can propose updates, you approve them
  • 🔧 Extensible Schema: Add custom fields without modifying code
  • 🔒 Skills Privacy: Control which skills are visible to agents (public/private/team)
  • 🤖 Agent-Callable Skills: Define skills that AI agents can invoke on your behalf
  • 📄 Resume Import: Bootstrap your profile from existing resume/CV
  • 📚 Knowledge Sources: Books, docs, courses, articles - unified learning model
  • 👥 Team Sync: Share coding standards across your team

Quick Start

Installation

bash
# Install from PyPIpip install tilde-ai
# Initialize your profiletilde init
Development Installation
bash
# Clone the repositorygit clone https://github.com/topskychen/tilde.gitcd tilde
# Install with uvuv sync
# Run locallyuv run tilde init

Configure Cursor

Add to .cursor/mcp.json in your project (or ~/.cursor/mcp.json for global access):

json
{  "mcpServers": {    "tilde": {      "command": "npx",      "args": ["-y", "tilde-ai"]    }  }}

Once configured, you'll see tilde in your MCP servers with all available tools and resources:

[Cursor MCP Settings]

Configure Antigravity

Add to .gemini/antigravity/settings.json in your project:

json
{  "mcpServers": {    "tilde": {      "command": "npx",      "args": ["-y", "tilde-ai"]    }  }}

Configure Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

json
{  "mcpServers": {    "tilde": {      "command": "npx",      "args": ["-y", "tilde-ai"]    }  }}

Example Usage

Once configured, your AI agent can access your profile. Try asking:

"What is my name?"

The agent will use the get_profile tool to fetch your identity and respond with your name and role:

[Cursor Demo]

Create Your Profile

Edit ~/.tilde/profile.yaml:

yaml
schema_version: "1.0.0"
user_profile:  identity:    name: "John Doe"    role: "Full Stack Developer"    years_experience: 10    # Add any custom fields you need:    timezone: "America/Los_Angeles"    pronouns: "they/them"
  tech_stack:    languages:      - TypeScript      - Python      - Go    frameworks:      - React      - FastAPI      - Next.js    preferences:      - "Prefer composition over inheritance"      - "Write tests before implementation (TDD)"      - "Use descriptive variable names over comments"    environment: "VS Code, Docker, Linux/MacOS"
  # Knowledge sources: books, docs, courses, articles, etc.  knowledge:    domains:      web_development: "Focus on performance and accessibility"      ml_ops: "Experience deploying ML models to production"        sources:      - title: "Clean Code"        source_type: "book"        insights:          - "Functions should do one thing"          - "Prefer meaningful names over documentation"      - title: "React Documentation"        source_type: "document"        url: "https://react.dev"        insights:          - "Prefer Server Components for data fetching"
  # Agent-callable skills (Anthropic SKILL.md format)  skills:    - name: "code-formatter"      description: "Format code using project conventions"      visibility: "public"      tags: ["automation", "code-quality"]    - name: "deploy-staging"      description: "Deploy current branch to staging environment"      visibility: "team"    - name: "expense-reporter"      description: "Generate expense reports from receipts"      visibility: "private"
team_context:  organization: "Acme Corp"  coding_standards: "ESLint + Prettier, PR reviews required"  architecture_patterns: "Monorepo with shared packages"  do_not_use:    - "jQuery"    - "Class components in React"

MCP Resources

tilde exposes these resources to agents:

Resource URIDescription
tilde://user/profileFull user profile
tilde://user/identityName, role, experience, custom fields
tilde://user/tech_stackLanguages, preferences, environment
tilde://user/knowledgeKnowledge sources, domains, projects
tilde://user/skillsSkills (filtered by visibility)
tilde://user/experienceWork history
tilde://user/educationEducation background
tilde://user/projectsPersonal/open-source projects
tilde://user/publicationsPapers and publications
tilde://team/contextTeam coding standards and patterns

MCP Tools

ToolDescription
get_profileRetrieve full or partial profile
get_team_contextGet team-specific context
propose_updateAgent proposes a profile update (queued for approval)
list_pending_updatesList updates awaiting user approval

CLI Commands

bash
tilde init                    # Create default profiletilde show                    # Display current profiletilde show skills             # Show skills section onlytilde show --full             # Show full content without truncationtilde edit                    # Open profile in $EDITORtilde config                  # Show current configurationtilde pending                 # List pending agent updatestilde approve <id> [id2...]   # Approve one or more updatestilde reject <id> [id2...]    # Reject one or more updatestilde approve --all           # Approve all pending updatestilde reject --all            # Reject all pending updatestilde approve --all -e <id>   # Approve all except onetilde log                     # View update historytilde ingest <file>           # Extract insights from a documenttilde export --format json    # Export profile

Document Ingestion

bash
# Ingest a book and extract insightstilde ingest "~/Books/DDIA.pdf" --topic data_systems
# Dry run to preview what would be extractedtilde ingest notes.md --dry-run
# Auto-approve high-confidence updatestilde ingest paper.pdf --auto-approve 0.8

Resume Import

Bootstrap your profile from an existing resume:

bash
# Import resume (PDF, DOCX, or text)tilde ingest ~/Documents/resume.pdf --type resume
# Preview what would be extractedtilde ingest resume.pdf --type resume --dry-run
# Auto-approve high-confidence itemstilde ingest resume.pdf --type resume --auto-approve 0.8

The resume importer extracts:

  • Identity: Name, role, years of experience
  • Experience: Work history with companies, roles, dates
  • Education: Degrees, institutions, graduation years
  • Tech Stack: Programming languages, frameworks, tools
  • Projects: Personal and open-source projects
  • Publications: Papers, patents, articles

Skills Management

Manage Anthropic-format skills with full bundling support:

bash
# Import skills from Anthropic skills directorytilde skills import /path/to/skills
# Import specific skills by nametilde skills import /path/to/skills -n mcp-builder -n pdf
# Dry run to preview importtilde skills import ./skills --dry-run
# Import as private skillstilde skills import ./skills --visibility private
# List all imported skillstilde skills list
# Export skills to Anthropic formattilde skills export ./my-skills
# Export specific skilltilde skills export ./output -n mcp-builder
# Delete skillstilde skills delete skill-nametilde skills delete --all --force

The skill importer bundles:

  • SKILL.md: Skill content with YAML frontmatter
  • scripts/: Python scripts and utilities
  • references/: Documentation files
  • templates/: Template files
  • assets/: Static assets
  • Root files: LICENSE.txt, etc.

All bundled resources are preserved through import → persist → export.

Team Management

bash
# Create a teamtilde team create myteam --name "My Startup" --org "ACME Corp"
# Activate team context (applies to all profile queries)tilde team activate myteam
# Sync team config from URL or git repotilde team sync https://example.com/team.json --activatetilde team sync [email protected]:myorg/team-config.git --activate
# List and manage teamstilde team listtilde team showtilde team edittilde team deactivate

Storage Backends

tilde supports multiple storage backends:

BackendUse CaseCommand
YAML (default)Human-readable, git-friendlyTILDE_STORAGE=yaml
SQLiteQueryable, memories, faster at scaleTILDE_STORAGE=sqlite
Mem0Semantic search via embeddingsTILDE_STORAGE=mem0
bash
# Use SQLite backendexport TILDE_STORAGE=sqlitetilde init
# Query profile fields (SQLite only)uv run python -c "from tilde.storage import get_storagestorage = get_storage(backend='sqlite')print(storage.query('%languages%'))"

Configuration

tilde uses a centralized configuration for LLM and embedding settings. Configuration is stored in ~/.tilde/config.yaml and can be synced across devices.

Configuration Priority

  1. Environment variables (highest priority)
  2. Config file (~/.tilde/config.yaml)
  3. Built-in defaults (lowest priority)

Environment Variables

VariableDescriptionDefault
GOOGLE_API_KEYGoogle/Gemini API key (primary)Required
OPENAI_API_KEYOpenAI API key (fallback)Optional
TILDE_LLM_MODELLLM model for document ingestiongemini-3-flash-preview
TILDE_EMBEDDING_MODELEmbedding model for semantic searchgemini-embedding-001
TILDE_STORAGEStorage backend (yaml, sqlite, mem0)yaml
TILDE_PROFILECustom profile path~/.tilde/profile.yaml

Managing Configuration

bash
# View current configurationtilde config
# Save settings to config file (for syncing across devices)tilde config --save
# Modify a setting and savetilde config --set llm_model=gemini-1.5-pro
# Show config file pathtilde config --path

Note: API keys are NEVER saved to the config file for security. Always set them via environment variables.

Quick Setup

bash
# Minimal setup (just one API key!)export GOOGLE_API_KEY="your-google-api-key"
# Save your settings for this devicetilde config --save
# Now you can use all featurestilde ingest paper.pdf

Syncing Across Devices

The config file at ~/.tilde/config.yaml is designed to be synced:

  1. Via dotfiles repo: Add ~/.tilde/ to your dotfiles
  2. Via cloud sync: Dropbox, iCloud, or similar
  3. Manually: Copy the file to new devices

Example config file:

yaml
llm_model: gemini-3-flash-previewllm_temperature: 0.7embedding_model: gemini-embedding-001embedding_dimensions: 768storage_backend: yaml

Programmatic Configuration

python
from tilde.config import get_config, call_llm, get_embedding, save_config
# Check current configconfig = get_config()print(f"Provider: {config.provider}")print(f"LLM Model: {config.llm_model}")
# Use directlyresponse = call_llm("Summarize this document...")embedding = get_embedding("Some text to embed")

Roadmap

  • Phase 1: MVP with profile reading
  • Phase 2: Agent-proposed updates with approval flow
  • Phase 3: Document ingestion (books, PDFs)
  • Phase 4: Team sync for B2B use cases
  • Phase 5: SQLite and Mem0 storage backends
  • Phase 6: Skill Management (Anthropic SKILL.md format)
    • Batch import from directory with tilde skills import
    • Export to directory with tilde skills export
    • Full bundling of scripts, references, templates, assets
    • Deduplication by skill name

Why "tilde"?

In Unix, ~ (tilde) represents your home directory — the place where your personal configuration lives. tilde is the home for your AI identity.


Philosophy

  1. Your Data, Your Control: Local by default, sync only if you choose
  2. Human-in-the-Loop: Agents propose, humans decide
  3. Portable & Open: Export anytime, no lock-in, works with any MCP tool
  4. Progressive Disclosure: Start simple, add complexity as needed

License

MIT


Configure once. Use everywhere. Your data, your control.

来源:README.md,提交 0a9c925

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

1
  1. v0.1.1最新Sep 16, 2026

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