🏠 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:

Code

┌────────────────────────────────────────────────────────────┐
│  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 PyPI
pip install tilde-ai

# Initialize your profile
tilde init

Development Installation

bash

# Clone the repository
git clone https://github.com/topskychen/tilde.git
cd tilde

# Install with uv
uv sync

# Run locally
uv run tilde init

Configure Cursor

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

config.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:

config.json

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

Configure Claude Desktop

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

config.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 URI	Description
`tilde://user/profile`	Full user profile
`tilde://user/identity`	Name, role, experience, custom fields
`tilde://user/tech_stack`	Languages, preferences, environment
`tilde://user/knowledge`	Knowledge sources, domains, projects
`tilde://user/skills`	Skills (filtered by visibility)
`tilde://user/experience`	Work history
`tilde://user/education`	Education background
`tilde://user/projects`	Personal/open-source projects
`tilde://user/publications`	Papers and publications
`tilde://team/context`	Team coding standards and patterns

MCP Tools

Tool	Description
`get_profile`	Retrieve full or partial profile
`get_team_context`	Get team-specific context
`propose_update`	Agent proposes a profile update (queued for approval)
`list_pending_updates`	List updates awaiting user approval

CLI Commands

server.ts

tilde init                    # Create default profile
tilde show                    # Display current profile
tilde show skills             # Show skills section only
tilde show --full             # Show full content without truncation
tilde edit                    # Open profile in $EDITOR
tilde config                  # Show current configuration
tilde pending                 # List pending agent updates
tilde approve <id> [id2...]   # Approve one or more updates
tilde reject <id> [id2...]    # Reject one or more updates
tilde approve --all           # Approve all pending updates
tilde reject --all            # Reject all pending updates
tilde approve --all -e <id>   # Approve all except one
tilde log                     # View update history
tilde ingest <file>           # Extract insights from a document
tilde export --format json    # Export profile

Document Ingestion

bash

# Ingest a book and extract insights
tilde ingest "~/Books/DDIA.pdf" --topic data_systems

# Dry run to preview what would be extracted
tilde ingest notes.md --dry-run

# Auto-approve high-confidence updates
tilde 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 extracted
tilde ingest resume.pdf --type resume --dry-run

# Auto-approve high-confidence items
tilde 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:

server.ts

# Import skills from Anthropic skills directory
tilde skills import /path/to/skills

# Import specific skills by name
tilde skills import /path/to/skills -n mcp-builder -n pdf

# Dry run to preview import
tilde skills import ./skills --dry-run

# Import as private skills
tilde skills import ./skills --visibility private

# List all imported skills
tilde skills list

# Export skills to Anthropic format
tilde skills export ./my-skills

# Export specific skill
tilde skills export ./output -n mcp-builder

# Delete skills
tilde skills delete skill-name
tilde 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 team
tilde 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 repo
tilde team sync https://example.com/team.json --activate
tilde team sync git@github.com:myorg/team-config.git --activate

# List and manage teams
tilde team list
tilde team show
tilde team edit
tilde team deactivate

Storage Backends

tilde supports multiple storage backends:

Backend	Use Case	Command
YAML (default)	Human-readable, git-friendly	`TILDE_STORAGE=yaml`
SQLite	Queryable, memories, faster at scale	`TILDE_STORAGE=sqlite`
Mem0	Semantic search via embeddings	`TILDE_STORAGE=mem0`

server.ts

# Use SQLite backend
export TILDE_STORAGE=sqlite
tilde init

# Query profile fields (SQLite only)
uv run python -c "
from tilde.storage import get_storage
storage = 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

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

Environment Variables

Variable	Description	Default
`GOOGLE_API_KEY`	Google/Gemini API key (primary)	Required
`OPENAI_API_KEY`	OpenAI API key (fallback)	Optional
`TILDE_LLM_MODEL`	LLM model for document ingestion	`gemini-3-flash-preview`
`TILDE_EMBEDDING_MODEL`	Embedding model for semantic search	`gemini-embedding-001`
`TILDE_STORAGE`	Storage backend (yaml, sqlite, mem0)	`yaml`
`TILDE_PROFILE`	Custom profile path	`~/.tilde/profile.yaml`

Managing Configuration

bash

# View current configuration
tilde config

# Save settings to config file (for syncing across devices)
tilde config --save

# Modify a setting and save
tilde config --set llm_model=gemini-1.5-pro

# Show config file path
tilde config --path

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

Quick Setup

server.ts

# Minimal setup (just one API key!)
export GOOGLE_API_KEY="your-google-api-key"

# Save your settings for this device
tilde config --save

# Now you can use all features
tilde ingest paper.pdf

Syncing Across Devices

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

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

Example config file:

yaml

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

Programmatic Configuration

server.ts

from tilde.config import get_config, call_llm, get_embedding, save_config

# Check current config
config = get_config()
print(f"Provider: {config.provider}")
print(f"LLM Model: {config.llm_model}")

# Use directly
response = call_llm("Summarize this document...")
embedding = get_embedding("Some text to embed")

Roadmap

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

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

License

MIT

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