Directory · Agents
Mastra
TypeScript framework for AI agents — workflows, tool calling, RAG, evals, and deploy targets tuned for full-stack JS teams.
Best for
Next.js/TS teams building agents in the same repo as the product
Pros and cons
Pros
- TypeScript-native (fits Next.js stacks)
- Workflows + agents + evals in one toolkit
- Active development, good DX
Cons
- Younger ecosystem than LangGraph
- Fewer production war stories published
- Tied to the TS/Node runtime
Alternatives
More agents tools
CrewAI
Agents
Multi-agent orchestration framework — define roles, goals, and tasks; agents collaborate on research, writing, and analysis jobs.
Best for
Multi-agent prototypes, non-engineer experimentation, role-based task pipelines
Pros
- Fastest path to a multi-agent demo
- Role/goal/task model is intuitive
- Large community and template library
Cons
- Harder to debug than explicit graphs
- Production reliability needs extra discipline
- Token burn on chatty agent loops
Alternatives
Dify
Agents
Open-source platform for building AI apps — visual workflows, RAG pipelines, agents, and an embeddable chat UI.
Best for
Low-code AI apps, internal tools, RAG chatbots without writing a full stack
Pros
- Visual builder for RAG and agents
- Self-host or managed cloud
- API + embeddable widget out of the box
Cons
- Less flexible than code-first frameworks
- Self-host ops (Docker, workers, vector DB)
- UI can feel opinionated for power users
Alternatives
Flowise
Agents
Open-source visual builder for LLM chains and agents — drag-and-drop nodes for RAG, tools, and chatflows.
Best for
Quick RAG prototypes, visual chain debugging, teams allergic to YAML
Pros
- Fastest visual RAG demo
- Self-hostable
- Large node library
Cons
- Less polished than Dify for end-user apps
- Complex flows get messy on canvas
- Production hardening is on you
Alternatives