Open Settings → Larkup Server, switch the toggle to Agent, and select Launch server. Restart it after changing the Agent’s prompt, skills, or tools so the generated runtime picks up the new configuration.
Settings → Larkup Server showing the local endpoint and API key
Copy the endpoint and Server API key from this page. Every request must include the key in the Authorization header.
Open Settings → Agent Customization. It has five tabs that control what the Agent knows and can do.
Prompt
Tools
Skills
MCP
Sandbox
Write the system prompt the Agent follows. Larkup combines it with its own retrieval and tool safety rules.
Agent Customization: Prompt tab
Turn built in tools on or off: semantic search, tabular data queries, chart generation, the Python sandbox, indexed data lookup, corpus analysis, and form filling.
Agent Customization: Tools tab
Add a Skill in the open SKILL.md format: metadata plus task instructions and optional resources. Upload a local file or add a remote one.
Agent Customization: Skills tab
Connect a remote Model Context Protocol server. Add its URL, test it to discover its tools, then enable it. Its tools become available to this Agent, namespaced by connection so they never override a built in tool.
Agent Customization: MCP tab
Give your Agent access to a computer, so it can run code instead of just describing it. Run it locally with Local Sandbox or Local Docker, or hand it to a remote provider such as E2B, Vercel Sandbox, Modal, Daytona, Fly.io Sprites, or Northflank. A remote sandbox is required for a serverless deployment that needs code execution.
Agent Customization: Sandbox tab
Select Verify after saving to confirm the chosen sandbox is reachable.
import { LarkupAgentClient } from '@larkup/sdk';const agent = new LarkupAgentClient({ baseUrl: 'http://localhost:8080', apiKey: 'your-api-key' });console.log(await agent.chatText('What can you find in our knowledge base?'));
from larkup import LarkupAgentClientagent = LarkupAgentClient(base_url="http://localhost:8080", api_key="your-api-key")print(agent.chat_text("What can you find in our knowledge base?"))
The full endpoint list is in the API Reference tab. To connect from the Vercel AI SDK, see Vercel AI SDK.
/health, /readiness, /reference, and /openapi.json stay public for operations and discovery. Every other Knowledge and Agent request needs Authorization: Bearer <key>.
Open Settings → Larkup Server → Server and select Deploy to choose a cloud provider. Larkup generates the runtime from the same Agent configuration used locally, including skills, MCP connections, and model settings. Use the same SDK client with the deployed URL. See Deploy Your Server for provider details.
