The finance-pulse package wraps the API twice: as a Python client
for scripts, notebooks and pipelines, and as an MCP server that lets an AI assistant ask the news questions
itself. Its source is on GitHub, and the server is listed in
the official MCP registry as io.github.SlothyAfk/finance-pulse.
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. In 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. In Cursor, the file is ~/.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".
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."
The assistant picks from eight tools:
| Tool | What it does |
|---|---|
search_statements |
Statements by symbol, sector, theme, topic, sentiment, minimum importance and time range |
trending |
The developments most outlets are reporting now, or per 2-hour slot over 7 days |
find_topics |
Developments for a symbol, sector or theme, by velocity, size or recency |
get_topic |
One development: counts, its mix of news, analysis and reddit statements, newest statements with their outlets |
sentiment_series |
Daily or hourly news volume and sentiment for a symbol, sector, theme or topic |
screen |
Symbols (optionally only equities and ETFs) or sectors ranked by news attention and its change against the previous period |
themes |
The standing subjects with their volume and sentiment, optionally only those a symbol or sector appears in |
reference |
The data window, known data incidents, theme ids and accepted filter values |
Each tool call is one API request. Results are trimmed and default to small pages, so the free plan goes a long way.
From Python
pip install finance-pulse
export RAPIDAPI_KEY=YOUR_RAPIDAPI_KEY
from datetime import datetime, timedelta, timezone
from finance_pulse import FinancePulse
fp = FinancePulse() # or FinancePulse("YOUR_RAPIDAPI_KEY")
# The newest key facts about a ticker
for 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 weeks
since = (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 now
for 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, and the reference documents every field.
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.
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. The feed guide explains what the cursor guarantees and why the log it builds is your own point-in-time history.
Run this yourself: get a free API key on RapidAPI ↗. The free plan is enough for every example in this guide.