Out of the box, a model can only generate text. Tools change that: enable a tool and the model can search the web, run code, query a database, or look up papers on arXiv during a conversation. Skills work differently. Where tools connect to external services, skills provide specialized knowledge domains the model draws on without you modifying the system prompt. Think of tools as hands and skills as expertise.
- Native features: Built into Open WebUI and ready to use. Web Search, Image Generation, URL Fetch, and Memory require no setup.
- Workspace tools: Python scripts registered in the platform. These run on the server when the model calls them.
- MCP (Model Context Protocol): Anthropic's open standard for connecting AI models to external data sources and services. MCP servers expose structured capabilities that models discover and invoke automatically.
- OpenAPI servers: Any web service with an OpenAPI specification can be connected as a tool provider.
- Open a conversation
- Click the ➕ icon next to the input box
- Browse or search available tools
- Toggle on the tools you want for this session
- Tools enabled this way apply only to the current conversation
- Go to Workspace > Models
- Edit the model you want to configure
- Scroll to the Tools section
- Check the tools you want always available with this model
- Click Save
- Every conversation with this model will now have access to these tools
Open WebUI maintains a community library of pre-built tools. Some relevant to academic work:
- arXiv Search — query academic papers directly from chat. No API key required.
- Perplexica Search — web search with inline citations.
- Pexels Media Search — find stock photos and videos for presentations.
- YouTube Search & Embed — locate and embed instructional videos.
Tip: Browse the community library before building your own tool. Someone may have already solved your problem.
Some models support native function calling (indicated by a TOOLS tag in Ollama). These models determine when to call a tool, what arguments to pass, and how to incorporate results without extra prompt engineering. If your model supports function calling, tool use becomes more reliable and natural.
Skills are specialized knowledge domains you bind to models. Unlike system prompts (which define general behavior), skills provide on-demand access to detailed procedural instructions for specific topics.
- Go to Workspace > Models
- Edit the model
- Scroll to the Skills section
- Select the skills you want to bind
- Click Save
When a user's question falls within a skill's domain, the model loads the relevant instructions automatically. You do not need to anticipate every possible question in your system prompt.
- Quantitative Methods: statistical analysis, research design, SPSS and R guidance
- Academic Writing: scholarly conventions, citation practices, genre awareness
- Research Ethics: IRB compliance, data privacy, informed consent protocols
- Digital Humanities: text analysis, corpus methods, visualization techniques
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If the community library does not have what you need, administrators can write custom tools. Each tool requires a name, description, and Python function body. The function runs on the server when the model invokes it.
Go to Workspace > Tools > + New Tool to get started. Consult with the AI Lab team if you are unsure about security implications.
Tools are Python scripts that execute on the server. A poorly written or malicious tool can access system resources, exfiltrate data, or disrupt service. Only install tools from trusted sources. The AI Lab maintains an approved tool list. Contact the team before adding community tools to the instance.
- Open WebUI Tools Documentation — official reference for tool development and configuration
- Model Context Protocol (MCP) — Anthropic's specification for connecting AI models to external data
- Open WebUI Community Tools — browse and download pre-built tools
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