ContextPulse

Developer Preview (v0.1-alpha). ContextPulse is under active development. APIs and configuration may change between releases. Report issues.

ContextPulse is a desktop daemon that captures your screen, voice, and keyboard/mouse activity in real time, then delivers it to AI agents through the Model Context Protocol (MCP). One process, one tray icon, 35 MCP tools, zero cloud dependency.

Everything stays local. No cloud. No telemetry. Your data never leaves your machine.

┌─────────────────────────────────────────────────┐
│              ContextPulse Daemon                 │
│                                                  │
│  ┌──────────┐  ┌──────────┐  ┌──────────┐      │
│  │  Sight   │  │  Voice   │  │  Touch   │      │
│  │ Screen   │  │ Dictate  │  │ Keys +   │      │
│  │ OCR      │  │ Whisper  │  │ Mouse    │      │
│  │ Clipboard│  │ Vocab    │  │ Bursts   │      │
│  └────┬─────┘  └────┬─────┘  └────┬─────┘      │
│       └──────────────┼──────────────┘            │
│                      ▼                           │
│              ┌──────────────┐                    │
│              │  EventBus    │                    │
│              │  (Spine)     │                    │
│              └──────┬───────┘                    │
│                     ▼                            │
│              ┌──────────────┐                    │
│              │ activity.db  │                    │
│              │ SQLite+FTS5  │                    │
│              └──────────────┘                    │
└────────────────────┬────────────────────────────┘
                     │ MCP (streamable-http :8420)
        ┌────────────┼────────────┐
        ▼            ▼            ▼
   Claude Code    Cursor      Any MCP
                              Client

Quick Demo

> You: "What am I looking at right now?"

Claude calls get_screenshot → get_screen_text:

  Active window: VS Code, src/auth/middleware.ts
  OCR text: "export async function validateToken(req: Request)..."
  Clipboard: "Bearer eyJhbGciOiJIUzI1NiIs..."

> Claude: "You're editing the auth middleware in VS Code.
>          I can see the validateToken function, and you have
>          a Bearer token in your clipboard. Want me to help
>          debug the token validation?"

> You hold Ctrl+Space and say: "refactor this to use the new auth provider"

ContextPulse Voice transcribes → pastes into editor
Claude calls get_recent_transcriptions → get_screen_text:

> Claude: "I can see your dictation and the current file.
>          Here's the refactored middleware using AuthProvider..."

> You: "What was I working on before lunch?"

Claude calls get_activity_summary(hours=4) → search_history("auth"):

  10:15 AM  VS Code, auth/middleware.ts (45 min)
  11:00 AM  Chrome, JWT.io (12 min)
  11:15 AM  VS Code, auth/tests/test_middleware.py (30 min)
  11:45 AM  Slack, #backend channel (15 min)

> Claude: "You spent the morning on auth middleware: writing
>          the implementation, checking JWT specs, then adding
>          tests. You were in Slack #backend right before lunch."

Why ContextPulse?

AI coding assistants are powerful but blind. They can't see your screen, hear your voice notes, or know what you were just doing. ContextPulse bridges this gap:

• Local-first, zero cloud dependency. Your screen, voice, and input data never leave your machine. No accounts, no subscriptions, no third-party servers. Privacy by architecture, not by policy.

• MCP-native from day one. ContextPulse exposes all context as MCP tools. Any MCP client (Claude Desktop, Cursor, Windsurf, VS Code) gets full context without custom integrations.

• True multi-modal in a single daemon. Screen capture, voice dictation, keyboard/mouse input, and semantic memory run in one lightweight process (<1% CPU). No stitching multiple tools together.

• Open source (AGPL-3.0). Fully auditable, self-hostable, and extensible. No vendor lock-in, no SaaS dependency, no risk of acquisition-driven shutdowns.

What Makes ContextPulse Different

Platform Support

Installation

git clone https://github.com/ContextPulse/contextpulse
cd contextpulse
pip install -e packages/core -e packages/screen -e packages/voice -e packages/touch -e packages/project

# Optional: persistent memory + semantic search
pip install -e packages/memory

Configure your AI agent and install companion skills:

contextpulse --setup claude-code   # configures MCP + installs skills
# or: contextpulse --setup gemini  # for Gemini CLI
# or: contextpulse --setup all     # both

Start ContextPulse:

contextpulse       # starts the background daemon
contextpulse-mcp   # starts the MCP server on port 8420

That's it. Your AI agent now has tools for reading your screen, voice, activity, and memory.

Add to ~/.claude.json:

{
  "mcpServers": {
    "contextpulse": {
      "type": "http",
      "url": "http://127.0.0.1:8420/mcp"
    }
  }
}

MCP Tools

Sight (11 free tools)

Voice (3 free tools)

Touch (3 free tools)

Project (5 free tools)

Memory (5 free + 2 Pro tools)

Basic memory is free forever. No license required.

Memory uses a 3-tier hot/warm/cold architecture: in-memory LRU cache → SQLite WAL + FTS5 → compressed archive. The optional pip install contextpulse-memory package ships these tools.

Pro (4 tools, requires license or 30-day trial)

Free forever: 27 tools (Sight × 11, Voice × 3, Touch × 3, Project × 5, Memory × 5) Pro: adds 4 search tools: semantic memory search plus cross-modal event queries Trial: 30-day Pro trial on first use, no credit card required

Additionally, ContextPulse includes several background learning tools (vocabulary consolidation, correction detection) that run automatically to improve transcription quality over time.

Architecture

ContextPulse is a monorepo with modular packages:

All modules emit events to a shared EventBus (the "spine"), which writes to a local SQLite database with FTS5 full-text search. MCP servers are read-only processes that query this database.

Development

git clone https://github.com/ContextPulse/contextpulse
cd contextpulse
uv venv
.venv\Scripts\activate
uv pip install -e "packages/core[dev]" -e packages/screen -e packages/voice -e packages/touch -e packages/project
pytest packages/ -x -q

See CONTRIBUTING.md for guidelines.

Canary Health Check

A canary script exercises every exposed MCP tool and reports pass/fail. It runs automatically on a cron/Task Scheduler schedule to catch regressions before users do.

# Run manually
python scripts/canary_health_check.py

# Verbose (shows each tool as it runs)
python scripts/canary_health_check.py --verbose

# JSON output (for CI or external monitoring)
python scripts/canary_health_check.py --json

What it does:

• Auto-starts the ContextPulse daemon if it is not already running

• Calls all primary MCP tools with minimal valid arguments

• Prints a human-readable summary with per-server breakdown

• Appends results to logs/canary_results.json (last 100 runs retained)

• Exits 0 if all tools pass, 1 if any fail

Scheduling (Windows Task Scheduler):

1. Open Task Scheduler → Create Basic Task

2. Trigger: Daily, repeat every 4 hours

3. Action: Start a program

   • Program: <path-to-contextpulse>\.venv\Scripts\python.exe

   • Arguments: scripts/canary_health_check.py

   • Start in: <path-to-contextpulse>

License

ContextPulse is licensed under the GNU Affero General Public License v3.0 (AGPL-3.0).

• You can use, modify, and distribute ContextPulse freely

• If you modify and deploy it as a service, you must open-source your changes

• Commercial licensing available for embedding in proprietary products

For commercial licensing inquiries, visit contextpulse.ai.

Patent Notice

ContextPulse's unified multi-modal context delivery system is patent pending.