investorclaw

name	investorclaw
description	Deterministic-first portfolio analyzer for Claude Desktop via MCP-HTTP at localhost:18090. Holdings, performance, Sharpe + Sortino, FRED yields, bond duration, scenario rebalancing.
homepage	https://github.com/argonautsystems/InvestorClaw
user-invocable	true
metadata	{"license":"MIT-0","version":"4.7.7","runtime":"claude-desktop","image":"ghcr.io/argonautsystems/ic-engine:4.7.7-cpu","mcp-endpoint":"http://localhost:18090/mcp"}

InvestorClaw — Claude Desktop Reference

Powered by InvestorClaw (Apache 2.0). This reference doc is MIT-0-licensed; the underlying service is Apache 2.0.

What this is

InvestorClaw is a containerized, deterministic portfolio analysis service. It runs on your machine as two Docker containers (a Rust memory server and a Python analysis engine) and exposes its capabilities to Claude Desktop over MCP-HTTP.

Claude Desktop has no plugin system — instead, it connects to MCP servers declared in claude_desktop_config.json. Once you run docker compose up -d and add two short blocks to that config file (see INSTALL.md), Claude Desktop gains an entire portfolio-analysis toolkit that you can invoke just by chatting.

There is no marketplace step. There is no plugin to install. The service is the substrate; Claude Desktop is the interface.

Tools that become available after install

Once both MCP servers are wired up and Claude Desktop has been fully quit and relaunched, the model gains two new tool namespaces.

Portfolio analysis (investorclaw.*)

Tool	What it does
investorclaw.portfolio_ask	Natural-language question routed through the deterministic engine
investorclaw.portfolio_holdings	Current snapshot of positions, values, and weights
investorclaw.portfolio_performance	Sharpe, volatility, top/bottom performers, max drawdown
investorclaw.portfolio_bonds	Bond analytics — YTM, duration, FRED yield curve
investorclaw.portfolio_analyst	Analyst consensus ratings per holding
investorclaw.portfolio_news	News correlation for held positions
investorclaw.portfolio_lookup	Ticker / account lookup
investorclaw.portfolio_optimize	Modern Portfolio Theory (Sharpe / min-vol)
investorclaw.portfolio_rebalance	Current vs. target with tax impact
investorclaw.portfolio_scenario	What-if scenarios (rate moves, drawdowns)
investorclaw.portfolio_cashflow	Projected dividends and bond coupons
investorclaw.portfolio_peer	Peer comparison vs. benchmark
investorclaw.portfolio_setup	Auto-discover portfolio files in /data/portfolios/
investorclaw.portfolio_refresh	Refresh market data without re-uploading files
investorclaw.portfolio_guardrails	View / configure educational-only guardrails

Memory (mnemos.*)

Tool	What it does
mnemos.search_memories	Full-text + semantic search across saved observations
mnemos.create_memory	Record an observation about preferences, prior questions, or context
mnemos.list_memories	Browse memories by category or date

How to use it in Claude Desktop

You don't invoke tools by name — you just talk to Claude. Examples:

Intent	Phrasing
Holdings	"What's in my portfolio?" • "Show me my positions"
Performance	"How am I doing this year?" • "What's my Sharpe ratio?"
Bonds	"Show me my bond exposure and yield-to-maturity"
Allocation	"What's my sector exposure?"
Optimization	"Help me rebalance to a 60/40 target"
Market data	"What's the current price of NVDA?"
News	"Today's news on my holdings"
Reports	"Generate today's EOD report" • "Prepare a brief for my advisor"
Stress test	"What if rates rise 100 bps?"
Memory	"Remember that I treat BABA as a sentimental hold" • "What did we discuss about my bond ladder last time?"

Claude routes the request to the right tool, surfaces the structured result, and decorates it with narrative context. The first call after a cold cache may take 30–60 seconds while the deterministic pipeline builds the signed envelope; subsequent calls reuse the cache.

Recommended model split

Claude Desktop uses the agent's own LLM — no external API key required.

• Narrative: Haiku 4.5 — fast, cheap, ~10× lower output cost than Sonnet. With a clean signed envelope, narrative synthesis is mostly transcription, so the cheap model is sufficient.
• Validator: Sonnet 4.6 (default) or Opus 4.7 (escalation) — gates the Haiku output for fabrication, mis-quoted numbers, and training-leak drift. Validator output is short (~1 K tokens), so the smart-model bill stays low.

Cost-shaped: cheap model on the long output, smart model on the short safety check.

Important behaviors

• Deterministic by design. Portfolio math is not generated by an LLM. The Python engine in the ic-engine container computes every number. Claude reports those numbers; it does not invent them. If Claude ever appears to fabricate a holding or a return, that's a bug — file it.
• Educational only — never investment advice. All outputs include a disclaimer envelope. Claude will echo it when summarizing.
• Localhost-only by default. Both MCP servers bind to 127.0.0.1. Nothing leaves your machine unless you explicitly enable a remote deployment via the dashboard.
• What Claude sees vs what stays local. Claude Desktop's transcript receives the agent's tool-call inputs and outputs — that includes the user's question, the structured ic_result envelope (ticker symbols, asset-class breakdowns, computed metrics), and the narrator's prose answer. It does NOT receive raw broker CSVs — those stay on your local filesystem in the bind-mounted ./portfolios/ directory. Account numbers and SSNs are scrubbed at ingest. See PRIVACY.md for the full data-flow matrix.
• Unknown CSV format? The engine returns a structured error with detected columns. Claude will direct you to the column-mapping wizard at http://localhost:18092/portfolios/map rather than guessing.

What this does NOT do

• Does not place trades or move money
• Does not give personalized investment advice
• Does not connect directly to broker accounts (you upload CSV / XLS / PDF)
• Does not require an internet connection for portfolio math (only for market-data refresh, which gracefully degrades without API keys)

Install

Claude Desktop connects to InvestorClaw via MCP servers — there is no plugin to install from a marketplace. The service runs locally via Docker Compose.

Start the service:

git clone https://github.com/mnemos-os/mnemos-ic-runtime.git ~/.investorclaw
cd ~/.investorclaw
mkdir -p portfolios
docker compose up -d

Then add the MCP server blocks to claude_desktop_config.json and restart Claude Desktop. See INSTALL.md in this directory for the exact config snippet.

OpenClaw / ZeroClaw / Hermes users: install via ClawHub:

clawhub install investorclaw

Where to go next

• INSTALL.md in this directory — step-by-step install instructions including the exact Claude Desktop config edit.
• config-snippet.json in this directory — the JSON block to merge into claude_desktop_config.json.
• Dashboard at http://localhost:18092 once running — upload portfolio files, configure provider keys, manage memory retention, inspect MCP traffic.

Reporting issues

This SKILL.md describes the InvestorClaw service. If a tool returns an unexpected result, the issue is in the service (argonautsystems/InvestorClaw, Apache 2.0) or in the runtime bridge (mnemos-os/mnemos-ic-runtime, Apache 2.0), not in this MIT-0-licensed reference doc.