mcp-server

Haystack: Build Scalable LLM Apps with 27k+ GitHub Stars

Haystack lets founders quickly assemble modular pipelines and agent workflows for retrieval‑augmented generation, multimodal AI, and semantic search—perfect for production‑ready LLM products.

From the repo · “Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.”

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26,804 stars+63★ this week3,316 forksPythonGuide quality 8/10 · reviewed Oct 5Updated 10/21/2026100% free · open source
What it is

Build modular AI pipelines with Haystack to create scalable large language model applications.

Real use case example

"A founder of a startup wants to build a conversational chatbot that can answer customer questions about their products. They use Haystack to design a modular pipeline that integrates with their product database and a large language model. After setting up the pipeline, the founder can test the chatbot and refine its performance to provide accurate and helpful responses to customers."

When to use it
  • •Creating enterprise search systems with semantic document retrieval
  • •Building conversational AI agents with context-aware memory and routing
  • •Developing RAG (Retrieval-Augmented Generation) applications with custom knowledge bases
Ready-to-paste prompt
from haystack import Pipeline
pipeline = Pipeline()
pipeline.add_node(retriever, name='retriever', inputs=['Query'])
pipeline.add_node(reader, name='reader', inputs=['retriever'])
result = pipeline.run(query='What are the key benefits of AI for startups?')
Saves to your device
Use with Claude
New

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⚡ Runs out of the box

A prompt/skill package — nothing to install beyond adding it to your AI tool.

Try it instantly — no install
Claude Code
mkdir -p ~/.claude/skills/haystack && curl -fsSL https://workflowstacks.com/api/skills/haystack/claude-skill -o ~/.claude/skills/haystack/SKILL.md
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Connect the whole catalog (MCP)
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How Haystack: Build Scalable LLM Apps with 27k+ GitHub Stars works
Codeflow
Free to inspect

Haystack: Build Scalable LLM Apps with 27k+ GitHub Stars is mostly documents (8613 doc files, 301 small scripts) — something you read, not something you run. There is nothing to install. Last commit this month, Apache-2.0 license.

Size
Mostly documents
8613 documents · 301 small scripts · days to read — use, don't read
Setup
Nothing to install
A guide / curated list. Just read it and follow the links.
Runs on
Nowhere — you read it
A reading resource, not a program.
Python 98%HTML 1%
Where to start reading
  1. 1
    README.md
    Start here — what it does and how to install it
  2. 2
    AGENTS.md
    The instructions the AI actually follows
  3. 3
    haystack/__init__.py
    Inside haystack/ — the main logic begins here
  4. 4
    examples/README.md
    A worked example — copy this to get going
What's in each folder
haystack/Core code — the actual logic288 files
docs-website/src/Core code — the actual logic23 files
docs-website/api/Backend / API4 files
docs-website/plugins/Sub-packages / plugins1 files
docs-website/docs/Documentation450 files
examples/Examples you can copy1 files
READMEHas testsDocumentedCI checksExamples includedApache-2.0 licenseUpdated this month
Quick Actions
Details
Creator
deepset-ai
Language
Python
Category
mcp-server
Published
11/14/2019

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Featured on WorkflowStacks
[![Featured on WorkflowStacks](https://workflowstacks.com/api/badge/haystack.svg)](https://workflowstacks.com/skills/haystack?utm_source=github&utm_medium=badge)
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