rivomirivomi API and MCP documentation
Connect an AI agent to rivomi, find people showing buying intent on LinkedIn, and run outreach from your own account over MCP or REST.
rivomi finds people who are showing buying intent on LinkedIn, scores each one against what your workspace sells, drafts a message that cites what they said, and sends it from your own LinkedIn account once a human approves. Every action in the app is available to an AI agent over MCP and to scripts over REST.
https://rivomi.com/api/mcpThe MCP server uses Streamable HTTP. Hosted connectors sign in with OAuth 2.1. Anything you configure yourself can send an API key as a bearer token instead.
Choose the shortest path
| Goal | Start here |
|---|---|
| Connect an agent for the first time | Connect over MCP |
| Configure a specific client | Claude, Claude Code, Cursor, ChatGPT, VS Code, Codex, or another client |
| Create a key or understand scopes | API keys and OAuth |
| Learn the nouns: agent, list, run, sequence | How rivomi works |
| Choose or inspect a tool | Tool reference, then the live tools/list schema |
| Call rivomi from a script | REST API |
| Complete a job end to end | Use cases |
| Handle an error or a cost question | Errors and limits, Credits |
The agent workflow
Connect and authorise
Point a Streamable HTTP client at /api/mcp, then sign in through OAuth or send
Authorization: Bearer <key>. A credential belongs to exactly one workspace.
Read the workspace
Call rivomi_get_workspace first. It returns the three facts every later decision depends on: the
credit balance (and whether spending is blocked), the LinkedIn senders and their headroom
today, and whether a human has accepted the sending terms.
Discover the live tools
Use MCP tools/list. Tool schemas are the source of truth for arguments, defaults, and limits.
A description that starts with $ spends credits.
Act, then poll
Reads return at once. Anything long (a search, an import, a scoring pass) returns a run_id; poll
rivomi_get_run until finished is true. Sending always returns "queued": a sender paces the
work inside its working hours.
The connection is ready when rivomi_get_workspace returns your workspace's real name and plan.
A job is complete when every run it started reports finished: true, and the result
(people found, drafts approved, replies sent) is confirmed by a read tool rather than assumed from a
write's response.
What the server exposes
| Capability | Tools cover |
|---|---|
| Workspace | Plan, credits, senders, sending consent, the funnel dashboard |
| Agents | Create, target, write the sequence, launch, pause, run now, review the queue |
| Prospects | Search, read in full, label fit, write a research brief |
| Lists and imports | Make lists, move people, import a post's engagers, enrich, score and draft |
| Runs | List, poll, abort long jobs |
| Outreach | Queue people into sequences, pause or stop one |
| Inbox | Find threads that need a reply, read them, reply |
Machine-readable documentation
Every page has a markdown twin. Append .md to a docs URL, or request it with
Accept: text/markdown.
/docs/llms.txtindexes every page./docs/llms-full.txtcontains the whole manual in one file./api/v1/openapi.jsonis the REST surface as OpenAPI 3.1.