life-agent-mcp

life-agent-mcp

Enables turning any personal-assistant REST backend into Claude-ready tools via a single MCP server, providing 38 tools for communications, finance, health, and more.

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README

life-agent-mcp

Turn any personal-assistant REST backend into 38 Claude-ready tools over a single MCP server.

What it is

A thin Model Context Protocol server built on FastMCP. Every tool is a small async function that forwards its arguments to a REST backend (X-API-Key auth) and formats the JSON response for Claude. No business logic lives here: the server is pure transport and shaping. It runs over the streamable-http transport, so a single long-lived process serves Claude Desktop, Claude mobile, and Claude Code alike.

The pattern is the point. If you already have a REST API for your own data, wrapping it as MCP tools is mostly this file: one decorated function per capability, two shared call_api / call_api_get helpers, and an entry point. This repo is a worked example of that pattern across a wide domain surface.

The backend itself is not included. The tools reference endpoints like /api/v1/message/inbound, /api/v1/brain/search, and /api/v1/social-brand/queue; you supply a service that answers them. Point API_URL at your own backend, or read the tool bodies as a template for wrapping your own.

Tool catalog

38 tools, grouped by domain.

General

Tool What it does
query_agent Send a free-form natural-language query, optionally with a domain hint
get_weekly_summary Cross-domain weekly digest (brain activity, cron health, stats)

Communications

Tool What it does
check_emails Email summary for a timeframe
check_messages SMS/text summary for a timeframe
send_text Send an SMS via the backend (Twilio)
check_calls Call log and voicemail summary
get_communication_summary Unified email + SMS + call summary

Finance

Tool What it does
log_expense Log an expense with amount, category, description
check_budget Budget status, overall or per-category
query_financials Natural-language finance questions (spending, net worth, investments)

Health

Tool What it does
log_health_metric Record a metric (weight, BP, steps, sleep, …)
check_health_trends Trends and recent readings

Home & inventory

Tool What it does
check_inventory Search or summarize home inventory
check_maintenance Upcoming home maintenance due

Infrastructure

Tool What it does
check_system_health CPU/memory/disk/service status
list_cron_status Recent cron executions and durations
get_cron_errors Recent cron failures

Social media

Tool What it does
create_social_post Post across platforms, now / scheduled / draft
check_social_schedule Upcoming scheduled posts

Social brand management

Tool What it does
generate_brand_posts AI-drafted posts per brand/platform
get_social_queue Draft queue awaiting review
approve_post Approve a draft and mark it scheduled
reject_post Reject a draft with a reason
schedule_post Send an approved post to Late for scheduling
get_brand_analytics Engagement analytics per platform
sync_social_analytics Pull latest engagement data from Late

Semantic memory ("brain")

Tool What it does
capture_thought Store a thought/decision/insight; auto-classified
search_brain Semantic search over captured entries
list_recent_thoughts Browse recent entries chronologically
brain_stats Topic/people/action-item patterns over time
get_brain_digest Digest of recent activity

Contacts

Tool What it does
get_contact_context Profile + recent history for a person
log_contact_interaction Record an interaction and capture notes
list_overdue_contacts Contacts overdue on their touch goal

Saved content

Tool What it does
summarize_youtube_video Transcribe and summarize a YouTube video
save_instagram_video Download, transcribe, and store an Instagram video
search_recipes Semantic search over saved Instagram transcripts
search_saved_content Search all saved content (IG, YT, TikTok, X, Reddit, articles)

Quick start

pip install .

cp .env.example .env      # then edit API_URL and BACKEND_API_KEY

export API_URL=http://localhost:8000
export BACKEND_API_KEY=your-key
export PORT=8001

life-agent-mcp

The server listens on http://0.0.0.0:$PORT (default 8001) and speaks the streamable-http MCP transport at the /mcp path.

Connecting Claude

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "life-agent": {
      "type": "streamable-http",
      "url": "http://localhost:8001/mcp"
    }
  }
}

Claude Code

{
  "mcpServers": {
    "life-agent": {
      "type": "http",
      "url": "http://localhost:8001/mcp"
    }
  }
}

Or via the CLI:

claude mcp add --transport http life-agent http://localhost:8001/mcp

Docker

docker build -t life-agent-mcp .

docker run -p 8001:8001 \
  -e API_URL=http://host.docker.internal:8000 \
  -e BACKEND_API_KEY=your-key \
  -e PORT=8001 \
  life-agent-mcp

Configuration

Variable Default Purpose
API_URL http://localhost:8000 Base URL of the REST backend the tools proxy to
BACKEND_API_KEY "" Sent as X-API-Key on every backend request
PORT 8001 Port the MCP server listens on

Architecture

Claude Desktop / Claude Code
        │  MCP (streamable-http)
        ▼
  life-agent-mcp  ── X-API-Key ──▶  your REST backend
   (this repo)                       (not included)

Two helpers, call_api (POST) and call_api_get (GET), carry the auth header and JSON handling; every tool is a @mcp.tool()-decorated coroutine that calls one of them and formats the result. The intelligence — routing, storage, embeddings, integrations — lives in the backend. This layer only defines the tool contracts and the transport.

Note

This is an extraction of the MCP layer from a personal assistant project, published to demonstrate MCP tool and transport design. It runs against a backend that is not part of this repo, so out of the box it exercises the MCP surface (tool discovery, schemas, streamable-http) rather than returning live data. Every tool listed above maps to real code in server.py — nothing here is aspirational.

License

MIT — see LICENSE.

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