Assistants that know their job.
Define an agent's prompt, pin its tools, lock the model, share with your team. Use @-mentions to invoke it from any chat.
From idea to invoked in minutes.
- 01
Describe
Tell Wirebase what the agent does. One sentence is enough.
- 02
Tune
Refine the system prompt, pick the model, lock parameters.
- 03
Pin tools
Attach MCP servers, workflows, and knowledge bases.
- 04
Share
@-mention from any chat. Public, private, or org-wide.
Prompt. Tools. Done.
Describe your agent in one sentence and Wirebase drafts the system prompt, suggests tools, and recommends a model — you review and adjust. Fine-tune with markdown-formatted instructions, lock parameters like temperature and max tokens, and set visibility to private, org-wide, or public. Going from idea to a working agent takes minutes, not sprints.
- AI-generated agents from a one-line description
- Hand-tune the system prompt with markdown
- Pin a model and lock parameters (temperature, tokens)
- Visibility: private, organization, or public
Pre-equipped with tools.
Attach MCP servers, workflows, and knowledge bases to an agent and it arrives at every conversation already holding the right tools. Only the tools you attach are loaded — so the context window stays clean and costs stay low. Per-tool custom instructions tell the model exactly how to use each integration.
- Attach MCP servers and individual tools
- Link to workflows and knowledge bases
- Per-tool custom instructions
- Token-efficient: only attached tools are loaded
@-mention to call.
Type @agent_name in any chat to hand off to that agent's prompt, tools, and model without leaving the conversation. Agents can call other agents, so you can compose a support agent that escalates to a specialist agent when it hits a knowledge boundary. Public agents are discoverable in the Explore gallery, shareable via link.
- @-mention from any chat or workflow
- Agents can call other agents
- Public agents discoverable in the Explore gallery
- Shareable links with permission controls
A support team built a triage agent in 20 minutes — Zendesk MCP for ticket data, a knowledge base of past resolutions, GPT-4o for the model. Now they @-mention it from any chat to get drafted replies that cite past tickets.
Everything to ship a real agent.
System prompts
Full markdown, variables, tool instructions.
Tool pinning
Curate exactly which tools the agent uses.
Knowledge attach
Ground the agent in a knowledge base.
Sharing model
Private, org-wide, read-only, or public.
AI generation
Describe the agent, get a draft in seconds.
Per-org governance
Admin controls who can publish.