description: Explore Spring AI Playground features: Tool Studio, MCP Server, Vector Database, Agentic Chat, Observability, and the safe local execution architecture.
Features
Spring AI Playground is organized around five product surfaces, designed to be understood in this order. The first four are the author / consume surfaces; Observability is the operator surface that watches them.
- :material-tools:{ .lg .middle } **[Tool Studio](/spring-ai-playground/docs/features/tool-studio/)**
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Low-code authoring environment for JavaScript-based tools.
Deny-first sandbox, Draft state, MCP server preset catalog, per-tool sandbox capability overrides.
- :material-connection:{ .lg .middle } **[MCP Server](/spring-ai-playground/docs/features/mcp-server/)**
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Built-in MCP server over Streamable HTTP, external connections via HTTP / SSE / STDIO / OAuth 2.1, a multi-tab Inspector for tools, resources, prompts, and client primitives, and a preset catalog of 57 preset MCP servers (49 vendor-official remote + 8 community stdio) activatable from the sidebar - see the [MCP Catalog directory](/spring-ai-playground/docs/features/default-mcp-catalog/).
- :material-database-search:{ .lg .middle } **[Vector Database](/spring-ai-playground/docs/features/vector-database.html)**
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Document ingestion, chunking, embedding, storage, and similarity search across Spring AI vector stores - the RAG validation surface.
- :material-chat-processing:{ .lg .middle } **[Agentic Chat](/spring-ai-playground/docs/features/agentic-chat/)**
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Unified runtime that composes tools and RAG context in one conversational interface - chain workflows and agentic tool-use side by side.
- :material-chart-line:{ .lg .middle } **[Observability](/spring-ai-playground/docs/features/observability/)**
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Fourteen in-app dashboards across four groups (AI Usage · AI Stack · Runtime · Overview) covering token economics, tool and MCP behaviour, RAG quality, host runtime, and a live trace tail - the operator surface that watches the other four.
The first four surfaces are intentionally connected. A tool authored in Tool Studio is exposed by the built-in MCP server, verified through the MCP Inspector, and consumed by Agentic Chat together with documents indexed in the Vector Database - without restart or redeploy at any step. Every chat turn, tool call, MCP exchange, and vector query is captured by Observability as it happens.
For a system-level view - runtime layers, data flows, and extension points behind these surfaces - see Architecture.
Further Reading
- Overview: return to the main product overview and documentation map
- Getting Started: install the app, configure providers, and choose a runtime
- Architecture: runtime layers, data flows, and extension points
- Tutorials: follow end-to-end workflows for tools, MCP, vector search, and agentic chat