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PortfoliosLab MCP Overview

PortfoliosLab MCP Overview

Understand what the PortfoliosLab MCP server does, which tools it exposes today, and when it is useful in an AI workflow.

Getting Started
Portfolioslab MCP
Last updated: May 31, 2026

PortfoliosLab provides a Model Context Protocol server so AI assistants can query live portfolio and market data.

The user MCP server is mostly a read-only surface for discovery, inspection, and comparison workflows where you want an AI assistant to fetch fresh data from your PortfoliosLab account or from the platform's symbol database. It also lets an assistant manage your watchlists — creating them, deleting them, and adding or removing symbols.


What the User MCP Server Can Do

Search symbols

Use `search-symbols` to filter the symbol universe by category, sector, industry, asset class, issuer, type, and sort order.

Fetch one symbol

Use `get-symbol` when you know the ticker and want its identity and classification (type, currency, exchange, sector/industry/issuer, data coverage).

Fetch symbol metrics

Use `get-symbol-metrics` for curated performance indicators (returns, volatility, drawdown, Sharpe) and key fundamentals (valuation, profitability, technicals, dividends).

Inspect taxonomy-like lists

Use `get-symbol-categories`, `get-symbol-sectors`, `get-symbol-industries`, and `get-symbol-asset-classes` to retrieve the values accepted as `search-symbols` filters, with counts.

List your saved portfolios

Use `portfolios-list` to see the portfolios that belong to your authenticated PortfoliosLab account. Use `get-portfolio` to fetch the full details of a single portfolio by id or slug — holdings, recent transactions, rebalancing rules, and computed indicators. Works for any public portfolio or your own.

List your saved watchlists

Use `watchlists-list` to see the watchlists that belong to your authenticated PortfoliosLab account, with their tracked symbols. Use `get-watchlist` to fetch a single one by id.

Manage your watchlists

Use `watchlist-create`, `watchlist-delete`, `watchlist-add-symbols`, and `watchlist-remove-symbols` to create or delete watchlists and change the symbols they track.

Run stock comparison

Use `stock-comparison` to compare two or more symbols as a static portfolio.

Run portfolio analysis

Use `portfolio-analysis` to analyze an inline static portfolio with two or more holdings. It returns historical performance, risk, drawdown, allocation, correlation, and benchmark comparison data.

Run diversification analysis

Use `diversification-analysis` to analyze an inline static portfolio, including diversification metrics, correlations, clusters, and low-correlation suggestions.

Best Fit

Use the user MCP server when you want live access to PortfoliosLab data inside an AI workflow, with watchlist management when you need it.


When MCP Is Useful

MCP is especially helpful when you want an AI assistant to work with up-to-date data while staying inside the conversation.

Common use cases include:

  • Finding ETFs from a specific issuer or asset class
  • Pulling one symbol record before discussing a trade idea
  • Listing your saved portfolios before asking for commentary
  • Reviewing the symbols on your saved watchlists
  • Building or curating a watchlist by adding and removing symbols
  • Comparing a simple static portfolio allocation
  • Checking diversification, overlap, and low-correlation candidates for an inline allocation

Typical Workflow

1

Create an MCP key

Generate a PortfoliosLab MCP key from your account settings.

2

Connect the MCP server

Add the `portfolioslab` MCP entry to your coding assistant using the setup instructions.

3

Start with read-only prompts

Ask the assistant to search symbols, fetch one symbol, list your portfolios, or run stock comparison with a small inline payload.

For step-by-step setup instructions, continue to Connect PortfoliosLab MCP.

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