MCP server

PortfolioFit Official

fit.portfolio/portfoliofit

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Check normalized portfolios against mandates and calculate allocation constraints.

Website

At a glance

Type

MCP server

Publisher

portfolio.fit (verified by the MCP Registry)

Status

Working at last check

Tools

10

Token cost

About 6,193 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http portfoliofit https://portfolio.fit/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.portfoliofit]
url = "https://portfolio.fit/mcp"

Gemini CLI

{"mcpServers":{"portfoliofit":{"httpUrl":"https://portfolio.fit/mcp"}}}

Cursor

{"mcpServers":{"portfoliofit":{"url":"https://portfolio.fit/mcp"}}}

VS Code

{"servers":{"portfoliofit":{"type":"http","url":"https://portfolio.fit/mcp"}}}

Antigravity

agy mcp add portfoliofit https://portfolio.fit/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"portfoliofit","server_url":"https://portfolio.fit/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"portfoliofit","server_url":"https://portfolio.fit/mcp"}

Tools

• calculate_portfolio_constraints ~1186 tokens
  Calculate explicit portfolio constraints deterministically from normalized holdings. Use this for arithmetic checks, not for interpreting natural-language mandates.
• calculate_portfolio_statistics ~1770 tokens
  Calculate historical return, volatility, drawdown, risk-adjusted and benchmark-relative statistics from a confirmed portfolio series profile. The metrics parameter describes all available calculations and their required inputs. Use daily, weekly or monthly complete periods; results include coverage,
• cancel_portfolio_series_upload Deletes data · ~202 tokens
  Cancel a pending upload and permanently remove its staging chunks.
• evaluate_portfolio_alignment ~1212 tokens
  Compare a clean mandate with normalized holdings. Do not send PDF, CSV, spreadsheet, or factsheet files; extract them before calling.
• get_analysis ~100 tokens
  Read retained normalized inputs, operations, results and owner-scoped dataset references. This is not an external agent transcript.
• list_analyses ~267 tokens
  Read private calculation groups and independent operations. Filter by kind, portfolio, dates, ready/running/attention status or legacy open/finished status.
• list_analysis_portfolios ~62 tokens
  List owner-scoped portfolios, analytics datasets, and profile readiness.
• list_portfolio_series ~214 tokens
  Discover owner-scoped immutable series profiles and their exact dataset versions. This returns metadata and coverage only, never dataset rows.
• review_portfolio_series_profile ~297 tokens
  Create an immutable profile revision using revise, or explicitly confirm a warning-free proposal with confirmation=true.
• upload_portfolio_series_rows ~883 tokens
  Upload normalized series_key/date/value/distribution rows and commit a dataset version. For up to 5,000 rows, omit chunk_index and total_chunks to complete in one call. For larger inputs, declare total_chunks on every call, send chunks in order, and reuse upload_id and idempotency_key. The final chu

Browse

• PDF tools
• Spreadsheets
• Government and public data

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