Comparisons / Eve vs LangChain

Eve vs LangChain: Which Agent Framework to Use?

Eve vs LangChain, head to head

Eve and LangChain 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.

Eve is Vercel's open-source TypeScript agent framework, launched June 17 2026.

LangChain is the most popular agent framework.

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 Eve if

Pick Eve if eve earns its keep when you want durable execution, sandboxed code exec, and multi-model routing without wiring three separate services. If you're already on Vercel, it composes; if not, the runtime pieces are the value and they don't travel. For a single-loop tool-using agent, plain TypeScript ships faster. The tradeoffs in its intro should match how your team already thinks about agents; LangChain will feel like translation if they don't.

Full Evecomparison →

Pick LangChain if

Pick LangChain if langChain adds value when you need production integrations (vector stores, specific LLM providers, deployment tooling). But if you want to understand what's happening — or your use case is straightforward — the plain Python version is easier to debug, modify, and reason about. The tradeoffs in its intro should match how your team already thinks about agents; Eve will feel like translation if they don't.

Full LangChaincomparison →

What both add

Whichever you pick, you're inheriting a dependency tree and a vocabulary your team has to learn before they ship anything. Eve has its own class hierarchy and tool registration conventions; LangChain has its. Either way, when something misbehaves you'll be reading framework source before you reach the actual HTTP call.

If the real workload is one model and a handful of tools, both can feel like a workbench for driving a nail. The lesson below builds the same pattern in plain Python — useful as a comparison point even if you ultimately keep the framework.

By the numbers

By the numbers

Eve

GitHub Stars

3.5k

Forks

180

Language

TypeScript

License

Apache-2.0

Created

2026-06-17

Created by

Vercel

Backed by

Vercel (public)

Cloud/SaaS

Runs on Vercel Sandbox + AI Gateway; deploys anywhere Node runs

Production ready

Yes

github.com/vercel/eve

LangChain

GitHub Stars

132.3k

Forks

21.8k

Language

Python

License

MIT

Created

2022-10-17

Created by

Harrison Chase

Backed by

Sequoia Capital, Benchmark

Funding

$25M Series A (2023), $25M Series B (2024)

Weekly downloads

3.5M

Cloud/SaaS

LangSmith (observability), LangServe (deployment)

Production ready

Yes

Used by: Notion, Elastic, Instacart

github.com/langchain-ai/langchain

GitHub stats as of April 2026. Stars indicate community interest, not necessarily quality or fit for your use case.

ConceptEveLangChain
AgentA directory with `agent.ts` + `instructions.md` + subfolders — the framework wires them together`AgentExecutor` with `LLMChain`, `PromptTemplate`, `OutputParser`
ToolsEach file in `tools/` exports one tool; schema comes from a Zod export`@tool` decorator, `StructuredTool`, `BaseTool` class hierarchy
DurabilityVercel Workflow SDK checkpoints every step so a crashed agent resumes where it left off
Sub-agentsEach `subagents/*.ts` becomes a callable sub-agent the parent can hand off to
Sandboxed execVercel Sandbox runs untrusted code in isolated micro-VMs, one API call away
Schedules`schedules/*.ts` exports a cron expression + handler; Vercel runs it
Agent Loop`AgentExecutor.invoke()` with internal iteration
Conversation`ConversationBufferMemory`, `ConversationSummaryMemory`
StateLangGraph state channels with typed reducers
Memory`VectorStoreRetrieverMemory`, `ConversationEntityMemory`
Guardrails`OutputParser`, `PydanticOutputParser`, custom validators

Or build your own in 60 lines

Both Eve and LangChain 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 →