Finance Pulse

Finance Pulse: Python client and MCP server

Financial news as structured, sourced data. Finance Pulse reads financial news as it is published and turns every article into statements: one-sentence facts with sentiment, importance, tickers, sector, source and publication time. Statements about the same development are clustered into topics, and topics into 19 themes. fintopic.news is a front page built on the same API.

The same setup guide, with the other guides and the API reference, is on the docs site: Use Finance Pulse from Claude, Cursor or Python.

This package gives you two ways to use it:

• a Python client for scripts, notebooks and pipelines;
• an MCP server, so Claude, Cursor and other MCP clients can query the news directly.

You need a RapidAPI key that is subscribed to Finance Pulse. Create a RapidAPI account, open the plans page and subscribe to a plan: Basic is free and is enough to try everything below. Then copy your X-RapidAPI-Key from the API's page on RapidAPI (the endpoint playground shows it). A key that is not subscribed to a plan is answered with 403.

Use it from Claude or Cursor (MCP)

The server runs with uvx, which is part of uv: install uv first. The package itself needs no separate install.

Claude Code

claude mcp add --env RAPIDAPI_KEY=YOUR_RAPIDAPI_KEY --transport stdio finance-pulse -- uvx finance-pulse

Claude Desktop and Cursor

• Claude Desktop: Settings > Developer > Edit Config opens claude_desktop_config.json (macOS ~/Library/Application Support/Claude/, Windows %APPDATA%\Claude\). Quit and restart Claude Desktop completely afterwards.
• Cursor: ~/.cursor/mcp.json

{  "mcpServers": {    "finance-pulse": {      "command": "uvx",      "args": ["finance-pulse"],      "env": { "RAPIDAPI_KEY": "YOUR_RAPIDAPI_KEY" }    }  }}

If the server does not start in Claude Desktop, it usually cannot find uvx: put the full path (the output of which uvx, or where uvx on Windows) in "command".

uvx keeps the version it installed first. To move to a new release, use finance-pulse@latest in place of finance-pulse once, or run uv cache clean finance-pulse.

Then ask things like:

• "What is the news saying about Nvidia today? Only the key facts, with sources."
• "Which tickers are suddenly getting more coverage than yesterday?"
• "What are the top developing stories in Energy, and how did the biggest one grow?"
• "Show me Tesla's daily news sentiment for the last two weeks."

Tools

Each tool call is one API request. Results are trimmed and default to small pages, so the free plan goes a long way.

Use it from Python

pip install finance-pulseexport RAPIDAPI_KEY=YOUR_RAPIDAPI_KEY

The MCP SDK is installed with the package even if you only use the client.

from datetime import datetime, timedelta, timezone
from finance_pulse import FinancePulse
fp = FinancePulse()          # or FinancePulse("YOUR_RAPIDAPI_KEY")
# The newest key facts about a tickerfor s in fp.statements(symbol="NVDA", importance_min="high", limit=5)["data"]:    print(s["published_at"][:16], s["sentiment"], s["statement"], f"({s['source_domain']})")
# Which tickers are suddenly in the news (kind= leaves out rates, central banks, countries, ...)for row in fp.symbols(period="d", sort="change", kind=["equity", "etf"], limit=10)["data"]:    print(row["id"], row["mentions"], row["change"])
# Daily news volume and sentiment, last two weekssince = (datetime.now(timezone.utc) - timedelta(days=14)).strftime("%Y-%m-%dT00:00:00Z")for b in fp.series(symbol="TSLA", interval="day", since=since)["data"]["buckets"]:    print(b["t"][:10], b["count"], b["score"])
# What most outlets are reporting right nowfor t in fp.trending(kind="live")["data"][:10]:    print(t["sources"], "sources:", t["name"])

Every method returns the API's JSON unchanged: {"data": ..., "next_cursor": ..., "snapshot": {...}}. The snapshot block says how fresh the data is.

Follow the news without missing anything

poll_feed yields every new statement in the order it entered the API and keeps its position in a file, so it survives restarts: after a crash nothing is skipped and only the statement you were working on is delivered again. The first run, with no saved position, starts 24 hours back, and the position is first stored once that first page has been handled. After a long pause the poller reads the whole backlog since its saved position, one request per 100 statements; delete the cursor file to start 24 hours back instead.

for s in fp.poll_feed(sector="Energy", importance_min="high", cursor_file="energy.cursor.json"):    print(s["indexed_at"], s["statement"], s["source_url"])

The API builds new data about every 2.5 minutes, so the poller waits 150 seconds between polls by default. One poller at that rate makes about 576 requests a day. Timeouts and server errors are retried; a used-up quota (429) is raised.

More than one page

rows = list(fp.iter_statements(symbol=["NVDA", "AMD"], importance_min="medium", max_items=1000))

Each page of 100 is one request. Without max_items it stops after 500 rows; max_items=None reads to the end of the window.

Errors

from finance_pulse import FinancePulseError
try:    fp.statements(symbol="S&P")except FinancePulseError as e:    print(e.status, e.title, e.detail, e.param)    # 400 | Invalid symbol | 'S&P' is not a ticker | symbol

A 429 means the plan's request quota or rate limit is used up. Timeouts and network failures are raised as FinancePulseError too, with status 0; e.transient is true for those and for 5xx answers.

Methods

The package targets Finance Pulse API 2.0 (the /v2 endpoints). Parameters and response fields are documented in the API reference, and the guides show complete worked examples.

What the data is, and is not

• Symbols are canonical entity codes with a kind. Equities and ETFs appear under their ticker (NVDA, 0700.HK); indices, rates, FX, crypto, commodities and organisations under short codes (SPX, US10Y, USD, BTC, GOLD, FED). Use kind=["equity", "etf"] for tradable tickers only.
• Sentiment describes the statement, not a price forecast. A symbol's sentiment is the count of its statements' labels.
• The window is a rolling 62 days. meta() lists known outages and delays under incidents.

See the docs for the full list of caveats.

Development

pip install -e ".[dev]"pytest

The tests use canned responses and make no API requests.

Releasing

1. Set the new version in src/finance_pulse/__init__.py and in server.json (two places).
2. Build and upload to PyPI (uv build && uv publish). From GitHub Actions, use pypa/gh-action-pypi-publish v1.14.2 or newer: older versions reject the metadata version this build writes.
3. Only then run mcp-publisher publish: the registry verifies the package on PyPI (it looks for the mcp-name line in its description), so the release must be there first.

Licence

MIT