AgentSwarms – self-hostable agentic AI/BI platform with sandboxed Python (ELv2)

AgentSwarms released a self-hostable, source-available (ELv2) agentic AI and business-intelligence platform featuring a visual multi-agent swarm canvas, RAG knowledge bases, sandboxed Python notebooks, and BI dashboards. The platform runs on users' own Supabase and Docker infrastructure with bring-your-own model provider keys, and includes agent chat with visual BI and document generation.

Deploy your own agentic AI & business-intelligence platform. Build agents, run multi-agent swarms, ground them in your data, and inspect every trace — on your own infrastructure, with your own keys. Screenshots a-look-at-it · Features features · Quickstart quickstart · Documentation documentation · Self-host vs. hosted this-repo-vs-agentswarmsfyi · Contributing /AgentSwarms-fyi/agentswarms/blob/main/CONTRIBUTING.md AgentSwarms is a complete, self-hostable, source-available agentic AI & business-intelligence platform: agent chat, a visual multi-agent swarm canvas, knowledge bases with RAG, tool use, MCP connections, connected databases & warehouses, dashboards, budgets, and full execution traces. It is designed for easy deployment : one Supabase project as the backend, one Docker command to run, and bring-your-own-everything — your data lives in your own Supabase project, and models run against your own provider keys OpenRouter, OpenAI, Anthropic, Gemini, Bedrock, Azure, OCI, Qwen, Grok, Groq, Ollama, vLLM… . Optionally set one instance-wide OpenRouter key so every user on your instance can start with zero setup. Swarm canvas — design a multi-agent workflow as a graph and run it end to end. Each node is a step agent, router, condition, loop, approval, tool call ; the inspector sets its provider, model, prompt, tools and knowledge. The same graph runs from the canvas, from the API and on a schedule. BI Workspace — multi-page dashboards over your connected tables and warehouses, with KPIs, cross-filtering, scheduled refresh, PDF export and publish-and-share links. Agent Chat, with Visual BI — ask a question in plain language and get a chart computed from your own data beside the answer. The SQL that produced it is shown as the source, so the number is checkable rather than asserted. Agent Chat, generating documents — turn the conversation and your data into a real, editable PowerPoint, Word document or Excel workbook. The Excel can pull every row with live formulas rather than a pasted snapshot. Developer workspace — Python notebooks on sandboxed server kernels with real langchain , langgraph and llama index installed. Model and knowledge-base calls are brokered by the platform, so no provider key ever exists inside the sandbox. Notebooks can call your deployed agents, and can themselves be published as callable APIs. Same UI, two different missions: This repository source-available, Elastic License 2.0 | | | |---|---|---| Focus | Easy deployment of the full agentic AI & BI platform on your own infrastructure — agents, swarms, RAG, connected data, dashboards, traces, budgets. | Learning first: a hands-on classroom for agentic AI — guided curriculum, build-along labs, interactive notebooks, presentations, and certification — fully managed. | Runs on | Your Supabase project, your provider keys, your Docker host or Cloudflare Workers . | Managed infrastructure, including an AI gateway with free-tier models — nothing to configure. | Extras | Headless control of your own data; no usage caps other than your own budgets. | Hosted-only surfaces: field-engineering blog, community galleries, voice agents, website embeds, and free standalone tools. | Best for | Teams and tinkerers who want to run an agentic AI platform they own. | Learners who want to study and practice agentic AI without setting anything up. | The "AgentSwarms" name and the hosted service remain with the project author. 🤖 Agent Chat | Build an agent, wire up tools, and chat with it in-browser under Build → Agent Chat , with full request/response traces. Flip on Visual BI to render a chart from your connected tables next to the answer, and generate a fully-editable PowerPoint, Word or Excel from your prompt + the conversation — the Excel can pull all rows with live formulas. See . | 🐝 Swarm canvas | Design multi-agent workflows visually built on checkpoint as they go, so a run survives a restart or deploy, and a human-approval step parks the run until someone decides rather than rubber-stamping it or failing. | Knowledge Base / RAG Data Sources PostgreSQL Supabase, RDS, Neon… , MySQL/MariaDB , Oracle Autonomous DB / ORDS , Amazon Redshift, Snowflake, Databricks, Google BigQuery, Azure Synapse, Trino / Starburst / Presto , and Amazon Athena — encrypted credentials, read-only. Query them from the Data Catalog SQL workbench, from SQL agents, and feed BI charts, ontologies and scheduled refreshes. See . Data sources & connectors /AgentSwarms-fyi/agentswarms/blob/main/docs/DATA SOURCES.md Secrets Manager {{secret:NAME}} — warehouse connections, provider keys. Superadmins share secrets with users/groups via IAM. Data Catalog Iceberg REST catalog through a wizard; the crawler lists every table and object, groups partitioned folders into datasets, infers CSV/JSON schemas by sampling, profiles columns null %, distinct counts, ranges , estimates row counts, and flags likely-PII columns. Schedule daily/weekly incremental crawls with schema-drift notifications, generate asset + column documentation with AI, certify or deprecate assets with owners and tags, trace lineage and usage which dashboards, prep flows and metrics consume each table , define a business glossary, and jump straight into the SQL workbench. Business Intelligence workspaces & folders with read-only group sharing, promote a personal draft into a shared workspace, and export model/dashboard definitions to a Git repo GitHub/GitLab . Observability Web search & browsing web search and web browse tools. Works out of the box with no key free DuckDuckGo fallback — limited ; for real workspace-wide search + full-page reads, connect Firecrawl on the Integrations page or set FIRECRAWL API KEY , or bring your own Brave / SerpAPI / Tavily / ScrapingBee key per agent. Every model-driven fetch is SSRF-guarded. See . Web search & browsing /AgentSwarms-fyi/agentswarms/blob/main/docs/INSTALL.md web-search--browsing-optional BYOK + MCP + A2A MCP Builder FastMCP under Build → MCP Builder , deploy it to the same sandboxed kernel the Developer workspace uses, and get a real Streamable-HTTP endpoint. It scales to zero by default or stays warm , registers itself so your own agents can call it, and can be exposed publicly with hashed API keys that support expiry, per-tool and per-IP limits. Secrets bind as environment variables without ever entering the container environment, and a redeploy that changes any tool name, description or schema blocks calls until you re-approve — the anti "rug pull" control MCP's own security guidance asks for. Needs the server runtime enabled. IAM Developer workspace sandboxed server kernels — real CPython with working pip install and genuine LangChain , LangGraph and LlamaIndex imports, not a browser emulation. Ships with read-only, runnable samples for each plus a mixed agentic-stack capstone knowledge base, tools, skills, guardrails, MCP — fork any of them to edit. The built-in agentswarms helper calls your connected models, searches your knowledge base and runs your saved agents and swarms , all governed by IAM rules and logged in Traces — no provider key ever exists inside the sandbox. A notebook can also be published as a callable API , and versioned to Git as plain Python. Operators enable the runtime under Admin → Developer runtime ; see . the runtime guide /AgentSwarms-fyi/agentswarms/blob/main/docs/DEVELOPER WORKSPACE RUNTIME.md Guardrails & evals One-command setup — after you've created a Supabase project and put its keys in .env see below , a script handles the rest secrets, deps, migrations, and bringing up the stack : cp .env.example .env fill in your Supabase keys, then: bash scripts/setup.sh Docker stack → http://localhost:8080 bash scripts/setup.sh --dev local dev server instead bash scripts/setup.sh --docgen + server-side PowerPoint / Word / Excel renderer Windows PowerShell: powershell -ExecutionPolicy Bypass -File scripts\setup.ps1 Or do it by hand — there is no separate backend to install, since Supabase is the backend Postgres + Auth + Storage , run as a free-tier hosted project rather than installing anything yourself: git clone https://github.com/AgentSwarms-fyi/agentswarms.git cd agentswarms npm install cp .env.example .env fill in your Supabase + provider keys apply the database schema once: npx supabase login && npx supabase link && npx supabase db push npm run dev → http://localhost:8080 Self-host with Docker any Node-capable host — VPS, Fly, Railway, Render, K8s : cp .env.example .env fill in Supabase + keys, apply migrations once docker compose up --build → http://localhost:8080 First time? Follow the full installation guide — it covers every step on macOS, Linux, and Windows, including the Supabase dashboard clicks and a troubleshooting section for the errors people actually hit. The docs live in docs/ /AgentSwarms-fyi/agentswarms/blob/main/docs , one focused guide per topic: | Guide | What it covers | |---|---| | Complete local setup on macOS / Linux / Windows: prerequisites, Supabase project, environment variables, first run, and troubleshooting. | | Every path: local desktop, a single cloud VM OCI/AWS/GCP , autoscaled VMs behind a load balancer, Cloudflare Workers, and Kubernetes — plus TLS, scheduling/cron, health checks, backups, and PWA install. | | Chatting with a saved agent, per-agent Visual BI answers, and generating fully-editable PowerPoint / Word / Excel from your prompt with Sample vs. full-data scope and live Excel formulas — plus embedding an agent on your own site. | | Every database / warehouse / lakehouse connector PostgreSQL, MySQL, Oracle, Redshift, Snowflake, Databricks, BigQuery, Synapse, Trino, Athena : fields, the read-only + encrypted-credential model, {{secret:NAME}} references, and how sources feed the catalog, BI and agents. | | Dashboards and the AI analyst: 19 visual types incl. the AI-built ontology, drill-down & forecasting, scheduled refresh + data alerts, AI-generated dashboards, workspaces & folders, dev→prod promotion, Git export, publishing / embedding / export, data prep, and connectors. | | Governed metrics + dimensions defined once and consumed by both BI and AI agents the metric query tool , so business definitions compute consistently and the AI picks names instead of writing SQL. | | Superadmins, groups, user provisioning, model allow-lists, read-only resource sharing, invite-only mode, and SAML SSO. | | Standing up the sandboxed Python kernels behind notebooks: the Docker/Kubernetes/E2B backends, the threat model and hardening, the egress allow-list, and how model and knowledge-base calls are brokered so no key reaches the sandbox. | | Adding skills markdown skill.md capabilities, no code and built-in tools definition + handler + gate in the registry , plus how tool-routing guidance keeps source selection sane. | | Tech stack and project structure. | Contributions are welcome — see CONTRIBUTING.md for the workflow, and please read the first. Code of Conduct /AgentSwarms-fyi/agentswarms/blob/main/CODE OF CONDUCT.md Found a vulnerability? Please see SECURITY.md for how to report it responsibly instead of opening a public issue. AgentSwarms is source-available under the Elastic License 2.0 ELv2 . In plain terms: you may freely use, self-host, modify, and redistribute it — but you may not offer it to third parties as a hosted or managed service , and you may not remove the licensing/copyright notices. A separate commercial license is available from the author for use cases ELv2 doesn't permit including running it as a SaaS — reach out if that's you. The "AgentSwarms" name, logo, and the hosted service are trademarks of the project author and are not licensed for your use; ELv2 covers the code, not the brand. Every direct dependency uses a permissive license MIT / Apache-2.0 / ISC / BSD , compatible with redistribution under ELv2 — the full audit and credits for the open-source projects AgentSwarms builds on live in ACKNOWLEDGEMENTS.md . Built with TanStack Start and Supabase — an agentic AI & BI platform you own.