Agent Desk
Open-source AI customer support with human handoff.
AgentDesk is a strong open-source option for teams wanting an AI-first support system with real human handoff and ticket management. It's best for those willing to self-host and configure; less ideal for non-technical teams or those needing a fully managed SaaS.
- Customer support teams wanting to reduce repetitive workload with AI
- Operations teams needing observable AI-human collaboration
- Developers building custom AI support systems on open source
- Small to medium businesses seeking free, self-hosted support software
- Teams requiring a fully managed SaaS with zero setup
- Enterprises needing advanced analytics or CRM out of the box
- Non-technical users unable to deploy Docker Compose or configure models
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In short
Agent Desk — Open-source AI customer support with human handoff. Best for Customer support teams wanting to reduce repetitive workload with AI, Operations teams needing observable AI-human collaboration, Developers building custom AI support systems on open source. Free to use.
What's new in Agent Desk
Checked 14 days agoAcross the latest 3 updates: 3 feature updates.
Agent Desk v1.5.3 released with visual workflow editor, workflow runtime, and audit pages
Added visual workflow capabilities for AI Agents including DSL validation, node mapping, and conditional branches. Introduced workflow runtime for LLM, handoff, ticket creation, etc. Added audit pages with execution graphs.
Agent Desk v1.5.2: improved agent workbench layout and realtime infrastructure
Added workbench layout components, new entry points /workbench and /workbench/tickets, AgentRealtimeProvider for realtime events, and migrated configuration to Viper with health check endpoint.
Agent Desk v1.5.1: added LanceDB vector database provider
Added LanceDB vector database support with Docker Compose, SQLite + LanceDB config, Dockerfile build support, and Makefile options.
Viability Score
How likely is Agent Desk to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- AI-first conversation runtime with session state
- RAG-backed knowledge base retrieval
- AI agent with customizable skills and MCP tools
- Human handoff preserving full context
- Ticket lifecycle from conversation to closure
- Web widget for customer chat
- Customer chat page and embed SDK
- Agent workspace for live conversations
- WeChat Official Account support
- WeCom Customer Service support
- OIDC, WeCom, and password login options
- Model configuration for OpenAI-compatible models
- Knowledge base FAQ and vector index management
- Open API and Open IM integration
- Docker Compose deployment
About Agent Desk
AgentDesk is an open-source AI customer support system that unifies live chat, knowledge retrieval, ticket workflows, and human handoff into a single AI-first runtime. Designed for customer support teams, it handles inbound chat, AI replies, retrieval, escalation, and follow-up work end to end. The system features a conversation runtime with session state, a RAG-backed knowledge base for accurate answers, an AI agent runtime with customizable skills and MCP protocol support, and seamless human handoff that preserves full context. Tickets connect follow-up work back to the original conversation, enabling complete issue resolution. Unlike chatbot shells, AgentDesk is a full support platform—open source under Apache 2.0, deployable via Docker Compose, and configurable with OpenAI-compatible models. It includes a web widget, customer chat page, embed SDK, agent workspace, and OIDC/WeCom login. This makes it a practical choice for teams wanting AI-first support with observable, maintainable operations, though it lacks a managed cloud offering and advanced out-of-the-box analytics.
Behind the Verdict
AgentDesk hits a sweet spot for support teams that want AI automation without losing control. Its architecture—conversation runtime, RAG knowledge, AI agent with MCP tools, handoff, and ticket lifecycle—covers the full support flow better than many open-source alternatives. The fact it's Apache 2.0 licensed and supports OpenAI-compatible models makes it flexible and vendor-neutral. We'd reach for this when you need a transparent, customizable system where you can see every AI decision and intervene. The handoff preserving context is a real time-saver; support agents don't have to re-read history. Where it bites: setup requires Docker and model configuration, so non-technical teams will struggle. There's no cloud version—you host it. Integrations are limited to WeChat and WeCom out of the box; other CRMs need manual work via MCP. Compared to something like Zendesk AI, AgentDesk is far cheaper (free) but demands ops effort. For a small dev-savvy team, it's a solid foundation. For a large enterprise needing Salesforce sync and advanced analytics, it's not ready.
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Use Cases
- Deploy an AI-first customer support widget on your website to handle common queries automatically.
- Configure RAG-backed knowledge base to ground AI answers in your FAQ and documentation.
- Set up human handoff rules to escalate complex or policy-bound conversations to agents.
- Use ticket workflows to turn resolved chats into tracked follow-up tasks across teams.
Limitations
- As an open-source project, setup requires Docker Compose knowledge and manual configuration of AI models and integrations.
- The number of pre-built integrations is limited; teams may need to custom-build connectors.
- The tool is relatively new with limited community size and documentation depth.
12-month cost
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Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
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