#1313th of 26 in RAG and knowledge

docsgpt

Builds agents and workflows that answer from your documents with citations

Stars
18.3k
License
MIT
Last commit
Oct 2026
Last release
Oct 2026
Language
Python

Missed the latest GitHub check; these facts may be older.

Overview

DocsGPT ingests documents, web pages and synced sources such as Google Drive, Confluence, GitHub and S3, and runs agents that answer with cited sources. Agents can use tools, MCP servers and sandboxed code, and can be chained in a visual workflow builder. It is served through a web app, an embeddable widget, an OpenAI-compatible /v1 API and an MCP server, with OIDC SSO, teams and quotas.

Who it is for: Teams self-hosting document-grounded agents and support bots

Strengths

  • Connectors sync Google Drive, SharePoint, Confluence, GitHub and S3, with GraphRAG
  • Exposes agents via widget, OpenAI-compatible API, webhooks and MCP server
  • SSO (OIDC/SCIM), roles, quotas and audit log are all MIT licensed
  • Works with OpenAI, Anthropic, Google, Groq, Ollama, vLLM; air-gapped install documented

Weaknesses

  • Stack needs API, Celery worker, Postgres, Redis and a vector store
  • README gives no RAM or GPU sizing for local models
  • Wide scope (workflows, guardrails, connectors) means a large surface to operate
  • Quick install is a curl-pipe-to-shell script that requires Docker

What it needs

  • GPU optional
  • Docker + Compose
  • Needs Docker, PostgreSQL, Redis, Vector store (FAISS, pgvector, Elasticsearch, Qdrant, Milvus or MongoDB)
  • Models: OpenAI, Anthropic, Google, Groq, OpenRouter
  • port 7091

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