Data as of Aug 25, 2026 · Based on 5,688 AI responses · See how Parse measures this
LLM Agent Frameworks and Tooling
Parse
https://parse.gl
| # | Brand | What AI says | Mention rate |
|---|---|---|---|
| 1 | The foundational, most-cited framework for general-purpose agent and RAG development. | 67% | |
| 2 | A fast-growing favorite for orchestrating role-based, multi-agent teams. | 47% | |
| 3 | Consistently cited for building collaborative agents that solve tasks through conversation. | 37% | |
| 4 | 24% | ||
| 5 | Dropped significantly in rank, now cited for its broader AI ecosystem. | 22% | |
| 6 | 14% | ||
| 7 | 11% | ||
| 8 | 11% | ||
| 9 | 10% | ||
| 10 | A popular open-source visual builder for composing | 9% | |
| 11 | The specialist framework for advanced RAG strategies like sentence-window retrieval. | 9% | |
| 12 | A leading no-code choice for non-technical users automating business workflows. | 8% | |
| 13 | 8% | ||
| 14 | 7% | ||
| 15 | A rising low-code platform with a visual builder for agent workflows. | 6% | |
| 16 | 6% | ||
| 17 | 6% | ||
| 18 | 6% | ||
| 19 | 6% | ||
| 20 | 5% | ||
| 21 | 5% | ||
| 22 | 5% | ||
| 23 | The dominant recommendation for the browser automation layer in web research agents. | 5% | |
| 24 | 5% | ||
| 25 | 5% |
Who wins on each AI
The same market, seen by two models.
Sources AI cited
medium.com is the page AI reaches for most here, cited in 41% of analyzed answers.
“The default framework for all agentic tasks.” → “The foundational ecosystem, with specific tools like LangGraph recommended for complex needs.”
Emerged as a dominant choice for multi-agent orchestration between November and January.
Dropped from #2 to #7 overall, with specific products like AUTOGEN now cited instead.
Became the go-to recommendation for stateful and human-in-the-loop systems by December.
| Brand | ChatGPT Search | Google AI Mode | Comparison |
|---|---|---|---|
| 59% | 62% | ||
| 56% | 53% | ||
| 23% | 27% | ||
| 34% | 12% | ||
| 22% | 22% |
The two models disagree most about Anthropic (ChatGPT #25, Google #14) and Google Agent Development Kit (ADK) (ChatGPT #16, Google #10).
LangChain continues its leadership as the framework most cited by AI assistants for building agentic applications. However, the most significant trend is the rapid rise of multi-agent and orchestration-focused tools like CrewAI and Microsoft's AutoGen, which now dominate discussions about building collaborative agent teams.
Across 5,688 AI responses, LangChain is mentioned most, named in 67% of them, followed by CrewAI (47%) and Microsoft AutoGen (37%).
Parse measures each brand's mention rate — the share of answers naming it — across 5,688 AI responses to this market's buyer questions. Answers are collected daily and the ranking is published weekly.
Brands enter the ranking when AI answers mention them. Parse collects answers daily and publishes the re-measured set weekly, so new brands appear as AI starts recommending them.
Best agent framework for tool use + human review?
LangChain is the foundational recommendation, but by early 2026,
CrewAI and LangGraph became equally prominent answers. LangGraph is favored for explicit control and state, while
CrewAI is suggested for its role-based human-in-the-loop design.
While LangChain and are consistently mentioned, quickly became the dominant recommendation for this use case. Between October and January, AI assistant responses solidified around as the top choice for its intuitive, role-based approach to building collaborative agent teams.
Brands mentioned
While LangChain and
Microsoft AutoGen are consistently mentioned,
CrewAI quickly became the dominant recommendation for this use case. Between October and January, AI assistant responses solidified around
CrewAI as the top choice for its intuitive, role-based approach to building collaborative agent teams.
The market map
Recommended by need