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Haystack

Open-source AI orchestration framework from deepset for building context-engineered, production-ready LLM applications. Pipeline-first architecture gives explicit control over retrieval, routing, memory, and generation.

Editorial Score
4/5
Visit HaystackGitHub →← All Frameworks
4/5
Editorial score
MCP SUPPORTED
Latest: v2.27.0
License
Open Source
Hosting
Self-hosted
Languages
Python
MCP Support
Yes
// Our Verdict

Haystack is the production-grade RAG framework for teams that want explicit, composable control over every step of their retrieval and generation pipeline. Hayhooks makes it uniquely suited for serving agents as MCP infrastructure.

Best for: Enterprises that need explicit, auditable pipeline control for RAG and agents — especially where Apache 2.0 licensing matters or MCP server deployment is needed
// Strengths
+Explicit pipeline architecture — nothing is hidden, every step is composable and auditable
+Production RAG gold standard with deep enterprise pedigree from deepset
+Hayhooks: deploy pipelines and agents as REST APIs or MCP servers
+SearchableToolset: dynamic tool discovery from large catalogs via BM25
+Apache 2.0 license — the most permissive in this category
// Weaknesses
1.3k dependents — lowest adoption count in this set
More niche positioning — requires pipeline thinking from day one
Smaller community than LangChain or LlamaIndex
Fewer off-the-shelf integrations than the broader LangChain ecosystem
// Agentic AI Audit
NOT SURE IF HAYSTACK
FITS YOUR STACK?

We map your agent system requirements, evaluate which framework fits your constraints, and give you a prioritised build plan. No fluff. Just a clear stack decision with rationale.

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