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FinnewsHunter
FinnewsHunter logo

FinnewsHunter

Active·★ 1.5k·Apache-2.0·Updated 2026-10-01
★ Essential★ Trending

FinnewsHunter is a multi-agent platform that turns financial news into investment research. Built on the AgenticX framework, it monitors Chinese financial news sources such as Sina Finance in real time, and deploys agent teams (a NewsAnalyst, a Researcher and others) to analyse sentiment and market impact, including a debate workflow in which agents argue different views before reaching a conclusion.

It is aimed at developers and quantitative researchers interested in agent-driven analysis of the Chinese A-share market. It combines news analysis with market data from akshare, showing daily and minute K-line charts, supports fuzzy search across more than 5,000 A-share stocks, and offers keyword search over news with highlighting. It supports five LLM providers (Alibaba Bailian, OpenAI, DeepSeek, Kimi and Zhipu) switchable from the front end, and uses a full stack of FastAPI, PostgreSQL, Milvus, Redis and React with background vectorisation.

Getting started: start the infrastructure (PostgreSQL, Redis and Milvus) with Docker Compose, install the backend Python dependencies, start the Celery workers, and run the React front end, following the project's quick-start guide.

This write-up is based on the project's README and public repository data. We have not hand-tested the tool. Data as of 2026-10-24.

License
Apache-2.0
Latest release
No GitHub releases
Last commit
2026-10-01
Contributors
2
Forks
341
Open issues and PRs
12
First published
2018-02-25

Source: GitHub, npm and PyPI public APIs.

#Multi-Agent System#Financial Analysis#LLM#Quantitative Trading#Docker#Data Analysis
$ Install
$ pip install -e .
↗ Visit site★ GitHub
01

Features

01Deep integration with AgenticX framework for agent-driven workflows.
02Multi-agent team (e.g., NewsAnalyst) for automated news sentiment and market impact analysis.
03Supports 5 major LLM providers with one-click switching.
04Integrated real-time stock K-Line analysis with Akshare data.
05Production-ready deployment via Docker Compose.
02

Why choose it

+Combines real-time news, sentiment analysis, market data and multi-agent debate in one system.
+Supports major Chinese and international model providers.
+Complete, production-style stack with search and background vectorisation.
+Apache-2.0 licensed.
03

Trade-offs

!Outputs are model-generated analysis, not investment advice; verify everything before making financial decisions.
!Focused on Chinese news sources and the A-share market.
!Heavy deployment: PostgreSQL, Milvus, Redis and Celery workers are all required.
05

Maintenance check

SlowingChecked: 2026-10-25
Last commit
2026-07-05
Commits, last 90 days
0
Releases, last 90 days
0
Latest release
—
Open issues
12
Recent issues with at least one comment
2/11
Commits per week, last 12 weeks
Commits per week, last 12 weeks: 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0

Oldest week on the left; the latest four weeks are orange. Source: GitHub commit activity.

Status rule: archived on GitHub = Archived; last commit within 90 days = Active; 91 to 365 days = Slowing; older = Stale. All figures come from the GitHub API on the date shown.

Most discussed open issues

  • #1 FileNotFoundError: [Errno 2] No such file or directory: 'stock_daliy/000416.txt'3 comments · 2018-10-29
  • #13 智能体监控 - 无执行触发0 comments · 2026-01-15
  • #12 局域网访问0 comments · 2026-01-15
  • #11 急需爬取新浪新闻的代码0 comments · 2025-11-18
  • #8 import joblib instead of from sklearn.externals import joblib0 comments · 2023-12-25

Issue titles are quoted from GitHub. Open the link to check whether a problem still applies to the version you use.

04

Who it fits

Pick it if
  • You research the Chinese A-share market and want real-time news from sources such as Sina Finance analysed by agent teams.
  • You want news sentiment combined with akshare market data and K-line charts.
  • You want to switch between Bailian, OpenAI, DeepSeek, Kimi and Zhipu from the front end.
Look elsewhere if
  • You trade markets other than A-shares, or need English news sources.
  • You cannot run PostgreSQL, Milvus, Redis and Celery workers.
  • You want trade execution: it produces research, not orders.
06

How it differs

tradingview-mcp logovs tradingview-mcp★ 5.2k

TradingView MCP works from technical indicators on many exchanges. FinnewsHunter starts from news and sentiment for A-shares.

Full comparison →
07

Compatibility

AgenticX
Native
Verified via docs
Bailian
Supported
Verified via docs
OpenAI
Supported
Verified via docs
DeepSeek
Supported
Verified via docs
Kimi
Supported
Verified via docs
Zhipu
Supported
Verified via docs
08

Quick start

1
$ pip install -e .
09

Use cases

↳Providing decision-level alpha signals for quantitative trading.
↳Real-time monitoring and deep analysis of financial news across multiple sources.
↳Identifying potential investment opportunities and risks through sentiment analysis and knowledge graphs.
10

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On this page
01Features02Why choose it03Trade-offs05Maintenance check04Who it fits06How it differs07Compatibility08Quick start09Use cases10Alternatives
DemonDamon /
FinnewsHunter
↗

Multi-agent platform turning financial news into research

1.5k341Apache-2.0
Last commit3w ago
StatusActive
CategoryData Processing
Contributors2
Links
Documentation↗Discussion↗Issues↗Releases↗
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