Model Context Protocol (MCP)

Use Xoru from Claude, ChatGPT, and Cursor

Query your buying-intent opportunities, inspect brand and competitor mentions, and generate reply drafts in your own voice directly from your AI assistant.

Draft-only by design: You approve every reply

Drafts only. You approve every reply in Xoru before anything is posted. No automated posting. No Xoru MCP tool can publish a comment or send a direct message automatically. Every draft generated through MCP is saved for your review so you can edit and post from your own account.

WHAT IT IS

Your social listening inbox inside your assistant

The Model Context Protocol (MCP) lets desktop and IDE assistants call structured tools on your behalf. Instead of switching tabs, you can ask your assistant what buying-intent threads or competitor complaints Xoru found today and draft replies in the same conversation.

Auth method: Workspace API key (Bearer token via XORU_API_KEY in client config)

SUPPORTED CLIENTS

Works with MCP-compatible clients

Claude Desktop
Claude Code
Cursor
ChatGPT (Developer Mode / MCP connectors)

Available for Founder and Growth workspaces with API & integration access enabled.

SETUP

Client configuration

Example configuration

Add the Xoru MCP server entry to your client configuration file (for example claude_desktop_config.json or .cursor/mcp.json) using your workspace API key:

{
  "mcpServers": {
    "xoru": {
      "command": "npx",
      "args": ["-y", "@xoru/mcp-server"],
      "env": {
        "XORU_API_KEY": "xoru_sk_your_workspace_key"
      }
    }
  }
}

Note: Keep your XORU_API_KEY private. It grants read access to your workspace opportunities and mentions and allows creating reply drafts in your workspace queue.

TOOLS REFERENCE

Available MCP tools

Read & Draft Only

list_opportunities

Read-onlyNever auto-posts

Fetch recent buying-intent conversations and problem threads matching your search sources.

list_mentions

Read-onlyNever auto-posts

List recent brand names, competitors, and topics tracked with sentiment labels (positive, neutral, negative).

Parameters: category?: "brand" | "competitor" | "topic", sentiment?: "positive" | "neutral" | "negative"

get_thread_context

Read-onlyNever auto-posts

Read the original post body, top comments, and community rules before drafting a reply.

Parameters: opportunity_id: string

draft_reply

Creates draftNever auto-posts

Generate a reply draft in your trained voice and save it to your Xoru approval queue. Never posts directly to social networks.

Parameters: opportunity_id: string, angle?: string

WORKFLOW EXAMPLE

Inspecting threads and drafting a reply

You

What buying-intent conversations did Xoru find today?

list_opportunities({ intent: "buying_intent", limit: 3 })

1. [r/SaaS] “Looking for a social listening tool that drafts replies without sounding like ChatGPT” (Buying intent · 2h ago)

2. [Ask HN] “Ask HN: How are small B2B teams tracking competitor complaints on Reddit and X?” (Buying intent · 4h ago)

3. [r/startups] “Frustrated with alert-only tools flooding Slack with noise. What else works?” (Competitor complaint · Negative · 6h ago)

You

Draft a reply to the top one

draft_reply({ opportunity_id: "opp_9482" })

“We ran into the exact same wall with generic AI replies getting ignored in r/SaaS. What worked for us was training drafts on our past founder comments first, and keeping a strict manual approval step so nothing ever posts automatically. Happy to share how we structure our keyword filters if useful.” (Draft saved in Xoru. You approve every reply before posting.)

Start finding high-intent conversations

Try Xoru with a 5-day free trial on Pro, or upgrade to Founder or Growth for brand and competitor mention alerts within the hour.

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Your social listening inbox inside your assistant

Auth method: Workspace API key (Bearer token via XORU_API_KEY in client config)