FastGPT is a self-hostable platform for building RAG knowledge-base assistants and visual AI workflow apps. Teams ingest documents into managed datasets, orchestrate answers through a flow-based canvas, and publish the result as chat assistants reachable through links, APIs, and embeds.[1][2]
Quick verdict
Teams building RAG knowledge-base assistants or support chatbots they must host themselves get the most from FastGPT. Its dataset pipeline plus visual workflow canvas, published through share links, OpenAPI endpoints, and MCP output, covers retrieval, orchestration, and delivery in one self-hosted package. The material constraint is operational and legal: production needs Docker with MongoDB, PostgreSQL, and your own model keys, and the custom license restricts public SaaS use and footer removal. If you have container-operations capacity and want RAG plus workflows under one roof, choose FastGPT; if you need zero-ops hosting or a permissively licensed core, evaluate the listed Dify or Langflow alternatives.[1][2][3][4]
Key features
Multimodal dataset ingestion Multimodal dataset ingestion: datasets accept documents, spreadsheets, images, audio, and URLs with managed parsing, chunking, and vector indexing for retrieval.[1][2]
Visual workflow canvas Visual workflow canvas: assemble AI apps from dialogue, dataset-search, plugin, code-execution, loop, and human-review nodes instead of wiring every step by hand.[1][2]
Tool use and MCP integration Tool use and MCP integration: workflows call HTTP tools and MCP services, with evaluation runs and scheduled execution for repeated or supervised jobs.[1][2]
Multi-channel publishing Multi-channel publishing: finished assistants ship through share links, OpenAPI-compatible endpoints, MCP server output, embedded widgets, and WeChat channels.[1][2]
Multi-model access with quotas Multi-model access with quotas: connect your own keys from dozens of supported LLM providers with per-model pricing, usage quotas, and usage statistics.[1]
Docker and cloud deployment Docker and cloud deployment: run locally with the Docker quickstart on port 3000, deploy on Sealos or managed cloud, or use the commercial single-package and multi-node cluster options.[1][2]
Commercial enterprise controls Commercial enterprise controls: paid licenses add OAuth2 and LDAP single sign-on, audit logs, branding control, implementation consulting, and priority support.[1][2]
RAG search and hybrid retrieval RAG search and hybrid retrieval: dataset search combines semantic, full-text, and hybrid recall with configurable chunking, so assistants answer from your own documents.[1]
Who will love it
Enterprises needing private knowledge assistants: datasets, retrieval, and deployment all stay inside your own infrastructure, which suits teams with data-control requirements.[1][2]
Support teams shipping chatbots broadly: one assistant can serve the web, embedded widgets, share links, and WeChat from a single workflow.[1]
Platform teams with container operations: if you already run Docker, MongoDB, and PostgreSQL, FastGPT puts RAG datasets and workflow orchestration under one self-hosted roof.[1][2]
Who should avoid it
Teams without operations capacity: production setup needs Docker, MongoDB, PostgreSQL with PGVector, config files, and model keys, which is more than a managed signup.[1][2]
Builders planning a public multi-tenant SaaS on the free edition: the custom license requires authorization for public SaaS use and forbids removing the Powered-by footer and logo.[1]
Non-technical users expecting pure no-code: the visual canvas still sits atop model configuration, dataset tuning, and self-hosted infrastructure.[1][2]
Alternatives and compatibility
Dify is the catalogue-listed alternative for teams comparing self-hostable AI app builders; weigh its hosting and licensing terms against FastGPT's custom license and container requirements before choosing.[1]
Langflow is the catalogue-listed alternative for flow-based AI orchestration; compare its canvas and deployment story against FastGPT's dataset-plus-workflow bundle for your retrieval workload.[1]
If FastGPT's workflow fits but the community terms do not, the paid commercial licenses add branding control, single sign-on, audit, and multi-node deployment without changing the underlying platform.[1][2]
Questions worth asking
What is the best FastGPT alternative for non-technical users?
Start with the catalogue-listed alternatives Dify and Langflow and compare their hosted onboarding against FastGPT's self-hosted setup. FastGPT assumes Docker, database, and model-key operations, so a team without that capacity should prefer whichever alternative offers the gentlest managed path; there is no evidence here for a universal winner.[1][2]
Is FastGPT really no-code?
How much does FastGPT cost per month?
The community edition is free to self-host under the custom FastGPT Open Source License, but you still pay your own infrastructure and LLM provider usage. Paid commercial licenses (single-node package, multi-node cluster with source package, and enterprise customization) are priced annually or perpetually on the commercial page; check the current page for numbers. Pricing structure checked October 9, 2026.[1][2][3]
Can you self-host FastGPT?
Yes. The README documents a local Docker quickstart and private deployment, the docs cover Docker Compose and private deployment, and the commercial page adds single-package and multi-node cluster deployment. Self-hosting needs MongoDB, PostgreSQL with PGVector, config files, and external model API keys, so it is moderate operational work, not one-click.[1][2][3]
Sources and editorial review
Source research. Reviewed on October 9, 2026. Written by Sanjib Sah. AI assisted; reviewed by a human editor.
We have not run or tested this product.
- FastGPT official site
official · Observed October 9, 2026
Official fastgpt.io homepage: enterprise AI knowledge-base and agent positioning, dataset processing, RAG retrieval, visual workflow orchestration, multi-model access, publishing channels, and paid training and delivery services.
- labring/FastGPT repository
official · Observed October 9, 2026
labring/FastGPT repository: knowledge-based LLM platform tagline, 29,787 stars observed October 9 2026, Docker and Sealos quickstart, MongoDB and PostgreSQL dependencies, custom license, active releases, not archived.
- FastGPT documentation
official · Observed October 5, 2026
Official documentation: quickstart, Docker Compose and private deployment, workflow and dataset guides, model access, publishing via API and MCP server, versioned releases, and FAQ.
- FastGPT license text
official · Observed October 5, 2026
Repository LICENSE file titled FastGPT Open Source License: Apache 2.0 text with added conditions requiring the Powered-by footer, forbidding logo removal, requiring authorization for public multi-tenant SaaS, and reserving all other rights.
- FastGPT commercial version
official · Observed October 5, 2026
Official commercial-edition page: three paid editions (single-node package, multi-node cluster with source package, enterprise customization) with annual and perpetual pricing, SSO and LDAP, audit logs, branding removal, implementation consulting, and priority support terms.
Compared with these products
No explicit proprietary baseline is recorded.