Overview

Connect Vruum to an agent harness, learn MCP, skills, plugins, and CLI, and run revenue workflows from chat.

Vruum is operated from the AI harness you already use. The browser is the control panel for Dashboard, Docs, and Settings. The actual work — people, accounts, deals, queues, campaigns, research, marketing, content, tasks, team skills, and proposals — runs through MCP tools and Vruum skills.

The clean mental model:

  • Plugin: the easiest install path when your harness supports one. It packages MCP connection details, skills, and instructions.
  • MCP: the live tool connection your agent calls to read and write Vruum.
  • Skills: repeatable operating workflows like pipeline fill, outreach triage, engagement triage, and deal review.
  • CLI: technical fallback for local setup, CI, local files, and debugging. Non-technical clients should not need it for day-to-day use.

Start here

  1. Quick Start — copy the install prompt, choose plugin, direct MCP, or technical CLI setup, then verify Vruum.
  2. Skills — the operating workflows agents should invoke.

Core references

PageWhat it answers
PluginWhich harnesses can install Vruum as a plugin, and what to use when plugin rails are unavailable.
MCPHow to connect the hosted MCP server, authenticate, verify setup, and when to use the local CLI.
SkillsHow to install, discover, invoke, and publish skills, plus the common operating workflows.
CLI ReferenceThe technical fallback command tree, --json, and exit codes.

Workflow skills

Skills automate the workflows. Each skill page also shows the underlying MCP and CLI calls so an agent can inspect, verify, or recover.

WorkflowUse when
Pipeline fillSource, research, gate, import, and enroll qualified prospects.
Outreach triageReview pending email and LinkedIn outreach drafts.
Engagement triageReview LinkedIn warming, nurture, marketing engagement, and content drafts.
Deal triageReview the pipeline; surface at-risk deals and the next action for each.

Agent-readable docs

Agents should not scrape the rendered browser page. Use the text routes. There is one site-level llms.txt and one site-level llms-full.txt; individual pages are exposed as .md.

URLPurpose
https://vruum.ai/llms.txtSmall docs index for discovery.
https://vruum.ai/llms-full.txtFull public docs corpus in one response.
https://vruum.ai/docs/<page>.mdAny single docs page as clean Markdown.
https://vruum.ai/docs/skills/<skill>.mdAny skill page as clean Markdown.

Product boundary

If you want a list, ask the agent for the list. If you want a row changed, ask the agent to change it. If you want an explanation, ask the agent to fetch the object and summarize the evidence.

The web app intentionally stays minimal: Dashboard, Docs, Settings, and proof artifacts. That keeps operating work inside the harness where the agent has context, tools, and a transcript.