haystack
★ 26.8k
vs
screener-mcp
★ 15
haystack vs screener-mcp
haystack: Haystack is deepset's open-source Python framework for building LLM applications from modular pipelines and agents with explicit control over retrieval, routing, memory and generation. It is model- and vendor-agnostic and is widely used for RAG, semantic search, question answering and production agents.; screener-mcp: Screener-mcp is an MCP server that integrates Claude with live financial data from Screener.in, NSE, and MCX, transforming it into a research assistant for Indian stocks. It enables users to perform company research, stock screening, document analysis, and track portfolios using real, current market data.
01
TL;DR
haystackRAG / Knowledge Base · ★ 26.8k
When to choose:
- You need explicit, reproducible, and production-grade RAG pipelines in Python with granular control over document retrieval, reranking, and routing.
- You want vendor-agnostic LLM integration that can serve pipelines as REST APIs or MCP servers via Hayhooks under Apache-2.0.
When to skip:
- You want a visual no-code or low-code UI for business workflows without writing Python code; RAGFlow or MaxKB are much faster to deploy.
- You only need an end-to-end autonomous research agent that gathers sources and writes markdown reports; GPT Researcher is built for that out of the box.
screener-mcpRAG / Knowledge Base · ★ 15
Compare key ratios and financials between multiple companies.
02
Side-by-Side Comparison
Field
haystackscreener-mcpCategory
RAG / Knowledge Base
RAG / Knowledge Base
Stars
★ 26.8k
★ 15
License
Apache-2.0
MIT
Install Command
pip install haystack-ai
claude mcp add screener -s user -- uvx --from 'screener-mcp[ai]' screener-mcp
Updated
2d ago
3d ago
Open Source
Yes
Yes
Tags
rag, llm-orchestration, python
Financial Analysis, Stock Market, RAG
03
Features
haystack01Composable pipelines with loops, branches and conditional routing for retrieval and generation
02Agents with lifecycle hooks, step and token-usage tracking, and progressive skill loading via SkillToolset
03Native async pipelines with token streaming and concurrent tool calls
04Integrations with OpenAI, Anthropic, Mistral, Cohere, Hugging Face, Bedrock, local models and many vector stores
05Hayhooks to serve pipelines as REST APIs or MCP servers
screener-mcp01Comprehensive Company Research (financials, ratios, shareholding, peer comparison, red-flag detection)
02Advanced Stock Screening (custom queries and pre-built thematic screens)
03Local Document Analysis (annual reports, earnings calls via RAG pipeline)
04Corporate Events Tracking (NSE announcements, bulk deals, insider trading)
05Local Portfolio Management (private holdings tracker with live P&L)
04
Use Cases
haystack↳Building RAG systems over company documents
↳Semantic search and question answering services
↳Production agents that need traceable retrieval and tool use
↳Exposing an existing pipeline to other agents as an MCP server
screener-mcp↳Compare key ratios and financials between multiple companies.
↳Screen for investment opportunities based on custom financial criteria or pre-built themes.
↳Ask questions and summarize key risks from annual reports or earnings call transcripts.
↳Monitor recent corporate announcements, bulk deals, and insider trading activity for specific stocks.
↳Track and manage a local stock portfolio with live pricing and P&L.
05
Best For
haystackMost Popular
screener-mcp—
FAQ
FAQ
What is the difference between haystack and screener-mcp?
Both haystack and screener-mcp are in the RAG / Knowledge Base category. haystack has 26.8k stars, while screener-mcp has 15 stars.
Which is better, haystack or screener-mcp?
The best choice depends on your use case. Choose haystack if Building RAG systems over company documents, and screener-mcp if Compare key ratios and financials between multiple companies..
Is haystack free or open source?
Yes, haystack is open source on GitHub (Apache-2.0).
Is screener-mcp free or open source?
Yes, screener-mcp is open source on GitHub (MIT).
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