# Machine Relations Index (remote · machinerelations.ai)

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

- Trust score: 83/100 (high trust)
- Change this week: +1
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-11-04

## Components

- remote · `machinerelations.ai`: 83/100 (this document), [markdown](https://verifymcp.io/servers/ai-machinerelations-mri/machinerelations.md), [page](https://verifymcp.io/servers/ai-machinerelations-mri/machinerelations)

## Channel facts

- Endpoint: `https://machinerelations.ai/mcp`
- Transports: `streamable-http`
- Auth: `none`
- Version: `1.1.0`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-11-04.

- **Endpoint Security**: 80/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - No authorisation is required to call this server. Every tool declares its destructiveHint and none is destructive, so open access doesn't expose one.
  - HTTPS is enforced; there's no plaintext access path.
  - The HSTS (Strict-Transport-Security) header is present.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 58/100
  - AI-judged instruction clarity (good).
  - Context-footprint check failed: tool/resource definitions use about 1793 tokens (~298/item across 6 items; 6 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 97/100
  - Stability observed for 29 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 91/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 73% of tool parameters carry a description.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 6 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 7 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 100/100
  - Implements a current MCP spec version (2026-07-28).

## Install

### How do I install the Machine Relations Index MCP server?

Machine Relations Index is a hosted endpoint at https://machinerelations.ai/mcp, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

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

### Cursor

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

### VS Code

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

### Codex

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

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "ai-machinerelations-mri": {
      "type": "remote",
      "url": "https://machinerelations.ai/mcp",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add ai-machinerelations-mri --url 'https://machinerelations.ai/mcp' --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  ai-machinerelations-mri:
    url: "https://machinerelations.ai/mcp"
```

### Netclaw

```json
{
  "McpServers": {
    "ai-machinerelations-mri": {
      "Transport": "http",
      "Url": "https://machinerelations.ai/mcp"
    }
  }
}
```

### Vellum

```bash
assistant mcp add ai-machinerelations-mri -t streamable-http -u 'https://machinerelations.ai/mcp'
```

### Other

```json
{
  "mcpServers": {
    "ai-machinerelations-mri": {
      "type": "http",
      "url": "https://machinerelations.ai/mcp"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-11-04 (score 83, −1)

- [functional] Stability: pass → 0.97

### 2026-11-03 (score 84, 0)

- [security] The server rewrote its instructions, which are the text every model session reads

### 2026-11-01 (score 84, +1)

- [security] Stability: 0.97 → pass

### 2026-10-31 (score 83, 0)

- [functional improvement] Tool coverage: 64% → 73%
- [cosmetic] “mri_get_cited_sources” added an optional parameter “cursor”
- [cosmetic] “mri_get_engine” added an optional parameter “cursor”
- [cosmetic] “mri_list_categories” added an optional parameter “release”
- [cosmetic] “mri_list_engines” added an optional parameter “release”

### 2026-10-30 (score 83, +1)

No change was recorded against any check on this day. Stability & Change Management went from 90 to 93. That category is still filling its 30-day observation window: 27 days of observed history at the previous scan, 28 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-10-28 (score 82, 0)

- [security] The server rewrote its instructions, which are the text every model session reads
- [functional regression] Schema quality: 235 → 274

### 2026-10-27 (score 82, +1)

No change was recorded against any check on this day. Stability & Change Management went from 80 to 83. That category is still filling its 30-day observation window: 24 days of observed history at the previous scan, 25 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-10-26 (score 81, −1)

- [security] The server rewrote its instructions, which are the text every model session reads
- [security] Tool “mri_get_cited_sources” rewrote its description, which is the text the model reads
- [security] Tool “mri_get_domain” rewrote its description, which is the text the model reads
- [functional regression] Schema quality: 957 → 1410
- [functional regression] Tool coverage: 71% → 64%
- [functional] Schema quality: excellent → good
- [functional] New tool “mri_get_engine”
- [functional] New tool “mri_list_engines”

## MCP tools (6)

### `mri_list_categories` (~82 tokens)

List MRI categories

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.

Input parameters:

- `release` (string): Optional release id. Any release other than the current one returns release_unavailable.

### `mri_get_category` (~77 tokens)

Get an MRI category

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.

Input parameters:

- `category` (string, required): Category key from mri_list_categories, e.g. cybersecurity.

### `mri_get_cited_sources` (~236 tokens)

Which sources AI engines cite

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/government, market database, wire distribution). This rate is not split by engine. For one engine, use mri_get_engine.

Input parameters:

- `category` (string, required): Category key, e.g. cybersecurity.
- `cursor` (string): Page token from the previous response's next.cursor. When set, offset is ignored.
- `limit` (integer)
- `offset` (integer)
- `question_shape` (string, required): Buyer question pattern: best_x (best X tools), how_choose (how to choose), is_x_worth (is it worth it), news_topic (recent news), problem_first (how to solve a problem), top_list (top platforms), x_v…
- `source_role` (string): Optional filter, e.g. editorial_media for publications only, vendor_owned, analyst_research, community_social.

### `mri_get_domain` (~157 tokens)

How often AI engines cite a site

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 source role, and per-category segment rates. Use to answer 'does ChatGPT cite <site>' or 'what share of Perplexity runs cite <site>'. A published byEngine row with runsCited 0 means that engine did not cite the domain. byEngine is the whole window, not a rate inside one category.

Input parameters:

- `domain` (string, required): A domain (techcrunch.com) or any URL on it.

### `mri_list_engines` (~75 tokens)

List MRI answer engines

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.

Input parameters:

- `release` (string): Optional release id. Any release other than the current one returns release_unavailable.

### `mri_get_engine` (~201 tokens)

Sources one answer engine cites

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 the evidence floor withhold the ranking. Use to answer 'what sources does Perplexity cite most?' or 'which sources does Google AI Overviews cite among published <category> sources'.

Input parameters:

- `category` (string): Optional category key. Limits the ranking to sources with a published segment in that category.
- `cursor` (string): Page token from the previous response's next.cursor. When set, offset is ignored.
- `engine` (string, required): Engine key from mri_list_engines: chatgpt, claude, gemini, google_ai_mode, google_ai_overviews, perplexity.
- `limit` (integer)
- `offset` (integer)

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/ai-machinerelations-mri/machinerelations#diagnostics

## Score history

- 2026-11-04: 83
- 2026-11-03: 84
- 2026-11-02: 84
- 2026-11-01: 84
- 2026-10-31: 83
- 2026-10-30: 83
- 2026-10-29: 82
- 2026-10-28: 82
- 2026-10-27: 82
- 2026-10-26: 81
- 2026-10-25: 82
- 2026-10-24: 81
- 2026-10-23: 81
- 2026-10-22: 81
- 2026-10-21: 80
- 2026-10-20: 80
- 2026-10-19: 79
- 2026-10-18: 79
- 2026-10-17: 78
- 2026-10-16: 78
- 2026-10-15: 77
- 2026-10-14: 77
- 2026-10-13: 77
- 2026-10-12: 76
- 2026-10-10: 75
- 2026-10-07: 74
- 2026-10-06: 73
- 2026-10-04: 74
- 2026-10-03: 73
- 2026-10-02: 73

## Common questions

### What is the Machine Relations Index MCP server?

Machine Relations Index is an MCP server listed in the public MCP registry as ai.machinerelations/mri. Which source domains AI answer engines cite, by buyer category and question shape. This page covers its hosted endpoint (https://machinerelations.ai/mcp).

### Is the Machine Relations Index MCP server safe to use?

Machine Relations Index scores 83 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the Machine Relations Index MCP server expose?

Machine Relations Index exposes 6 tools: mri_list_categories, mri_get_category, mri_get_cited_sources, mri_get_domain, mri_list_engines, mri_get_engine. Their descriptions and schemas cost roughly 828 tokens of context every time the server is loaded.

### Does the Machine Relations Index MCP server require authentication?

No. We connected to Machine Relations Index without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.

### Is the Machine Relations Index MCP server still maintained?

Machine Relations Index is still listed as active in the MCP registry. We last reached this channel on 4 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

## Links

- Remote endpoint: https://machinerelations.ai/mcp
- Repository: https://github.com/Bramwell-Inc/machinerelations-plugins
- Website: https://machinerelations.ai/machine-relations-index
- Changelog RSS feed: https://verifymcp.io/servers/ai-machinerelations-mri/machinerelations.xml
- Changelog JSON feed: https://verifymcp.io/servers/ai-machinerelations-mri/machinerelations.json
- HTML version of this page: https://verifymcp.io/servers/ai-machinerelations-mri/machinerelations