MCP server

Machine Relations Index Official

ai.machinerelations/mri

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Which source domains AI answer engines cite, by buyer category and question shape.

Website

At a glance

Type

MCP server

Publisher

machinerelations.ai (verified by the MCP Registry)

Status

Working at last check

Tools

6

Token cost

About 1,234 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http mri https://machinerelations.ai/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.mri]
url = "https://machinerelations.ai/mcp"

Gemini CLI

{"mcpServers":{"mri":{"httpUrl":"https://machinerelations.ai/mcp"}}}

Cursor

{"mcpServers":{"mri":{"url":"https://machinerelations.ai/mcp"}}}

VS Code

{"servers":{"mri":{"type":"http","url":"https://machinerelations.ai/mcp"}}}

Antigravity

agy mcp add mri https://machinerelations.ai/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"mri","server_url":"https://machinerelations.ai/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"mri","server_url":"https://machinerelations.ai/mcp"}

Tools

• mri_get_category ~136 tokens
  Return one category's question shapes (best tools, how buyers choose, comparisons, top lists, problem-first research, is it worth it, news) and the evidence state of each: published with rates, collecting, or not collectable.
• mri_get_cited_sources ~369 tokens
  Ranked source domains that AI answer engines cite, pooled across engines, for one category and question shape, with citation rate (share of monitored answer runs citing the domain), rank, percentile and source role (editorial publication, vendor-owned, analyst research, community, academic/governmen
• mri_get_domain ~230 tokens
  For one domain or URL, return how often AI answer engines cite it: overall citation rate, the rate on each engine (overall.byEngine: cited runs, that engine's observed runs, and whether the engine's sample clears the evidence floor), confidence tier, rank among all cited domains and within its sourc
• mri_get_engine ~295 tokens
  Ranked sources one answer engine cites, by that engine's citation rate across the whole window. Pass category to limit the list to sources with a published segment in that category; the rate stays the whole-window rate and is not a rate inside the category. Collecting categories and engines below th
• mri_list_categories ~108 tokens
  List every Machine Relations Index category (e.g. cybersecurity, fintech, enterprise-software, ai-visibility-geo) with the question shapes that have published citation rates, plus the source-role vocabulary. Call this first to get a valid category key.
• mri_list_engines ~96 tokens
  List each answer engine with the model the release roster names, the engine's observed runs and days, whether that sample clears the evidence floor, and the most-cited source on that engine across the whole window.

Browse

• Perplexity tools
• Databases
• Calling other AI models
• Research papers
• News

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