Comparisons / Anthropic Agent SDK vs Haystack
Anthropic Agent SDK vs Haystack: Which Agent Framework to Use?
Anthropic Agent SDK vs Haystack, head to head
Anthropic Agent SDK and Haystack both let you build an agent, but they sit in different parts of the stack and they assume different things about who's writing the code.
The Anthropic Agent SDK packages Claude Code's agent loop as a library.
Haystack by deepset is a framework for building NLP and LLM pipelines.
Underneath, both wrap the same thing: a model call, a tool dispatch, a loop. The decision is about which abstraction your team wants to think in day to day, and which ecosystem you're willing to inherit along with it. There's an honest, framework-free version of the same pattern in about 60 lines of Python in the lesson at the bottom of this page — useful as a baseline regardless of which framework wins.
Pick Anthropic Agent SDK if
Pick Anthropic Agent SDK if the Anthropic Agent SDK's real value is packaging Claude Code's battle-tested agent loop with built-in tools and MCP integration. If you want a production agent that reads files, runs commands, and connects to services, it saves significant plumbing. For understanding how agents work, the plain version is more instructive. The tradeoffs in its intro should match how your team already thinks about agents; Haystack will feel like translation if they don't.
Pick Haystack if
Pick Haystack if haystack earns its complexity when you're building RAG pipelines with multiple retrieval stages, document processing, and production deployment needs. But for straightforward agents with a few tools, the plain Python version is simpler to write and debug. The tradeoffs in its intro should match how your team already thinks about agents; Anthropic Agent SDK will feel like translation if they don't.
By the numbers
By the numbers
Anthropic Agent SDK
3.1k
582
Python
MIT
2023-01-17
Anthropic
Google, Spark Capital
Yes
Haystack
24.7k
2.7k
Python
Apache-2.0
2019-11-14
deepset
GitHub stats as of April 2026. Stars indicate community interest, not necessarily quality or fit for your use case.
| Concept | Anthropic Agent SDK | Haystack |
|---|---|---|
| Agent | Claude agent with built-in tools, MCP servers, and system prompt | `Agent` component with `ChatGenerator`, tool definitions, and message routing |
| Tools | Built-in tools (`bash`, file read/write, web) + MCP server connections | `Tool` dataclass with function reference, name, description, parameters schema |
| Agent Loop | SDK's internal agentic loop with automatic tool dispatch | — |
| Sub-Agents | Agents invoke other agents as tools via the SDK | — |
| Lifecycle Hooks | 18 hook events: pre/post tool call, message, error, etc. | — |
| MCP Integration | One-line MCP server config for Playwright, Slack, GitHub, etc. | — |
| Pipeline Architecture | — | `Pipeline()` with `add_component()` and `connect()` — a directed graph of typed components |
| RAG / Retrieval | — | `DocumentStore` + `Retriever` + `PromptBuilder` + `Generator` wired in a `Pipeline` |
| Memory | — | `ChatMessageStore` with `ConversationMemory` component in pipeline |
| Deployment | — | Pipeline YAML serialization, `Hayhooks` REST server |
Or build your own in 60 lines
Both Anthropic Agent SDK and Haystack implement the same 8 patterns. An agent is a function. Tools are a dict. The loop is a while loop. The whole thing composes in ~60 lines of Python.
No framework. No dependencies. No opinions. Just the code.
Build it from scratch →