Machine Relations plugins
The official Machine Relations skill and plugin helps practitioners choose and draft an evidence-backed authority intervention for a brand or client. It supports AI visibility, GEO/AEO, SEO content discovery and digital PR work, with separate execution checks and intended-outcome tests. No AuthorityTech purchase is required.
The package includes the broader machine-relations skill alongside the existing machine-relations-index research skill. The Machine Relations Index (MRI) by Jaxon Parrott remains neutral public measurement of which source domains AI answer engines cite in sampled buyer answers, by category and question shape. Broader work can also use public or client-supplied evidence without MRI coverage.
The plugin retains the package identifier machine-relations-index and remote MCP server at https://machinerelations.ai/mcp (read-only, no account). Its four research tools are unchanged:
| Tool | What it answers |
|---|---|
mri_list_categories |
Which categories, question shapes and source roles the Index covers |
mri_get_category |
One category's question shapes and whether each has published rates |
mri_get_cited_sources |
The ranked source domains AI engines cite for a category and question shape |
mri_get_domain |
How often a site is cited, by which engines, and where it ranks |
Install
Codex
codex plugin marketplace add Bramwell-Inc/machinerelations-plugins
Then install the Machine Relations package (identifier machine-relations-index) from that marketplace. Published directory versions may still display Machine Relations Index; verify that your installed version includes machine-relations before expecting the broader workflow.
Claude Code
/plugin marketplace add Bramwell-Inc/machinerelations-plugins
/plugin install machine-relations-index@machinerelations
Any MCP client: add a remote (streamable HTTP) server with URL https://machinerelations.ai/mcp. It is also listed in the official MCP Registry as ai.machinerelations/mri.
No MCP: the same reads are a JSON API at https://machinerelations.ai/api/mri/v2 (OpenAPI).
An MCP connection alone supplies research tools; it does not install the skill. The broader skill is at plugins/machine-relations-index/skills/machine-relations/SKILL.md for compatible skill hosts. New instructions do not require changing Editor's private method, the App journey or the Index's measurement.
Data
Every response carries its release ID, the artifact hash and a citation string. MRI data is licensed CC BY 4.0. Dataset citation: Machine Relations Index (MRI) by Jaxon Parrott, Machine Relations Research — machinerelations.ai. https://machinerelations.ai/index. https://doi.org/10.5281/zenodo.23652423. Methodology: https://machinerelations.ai/machine-relations-index.
The plugin package in this repository is MIT licensed.
Use and interpretation
Start with the worked example and agent entry point. The example preserves one historical release; it is not a live leaderboard.
Every successful current data read includes source.guidance, the live interpretation rules. The skill directs agents there and to any field-specific method and limitations. Daily data and interpretation updates therefore do not require rebuilding this plugin. Missing or null question context is unavailable, never zero; the service describes what the current release actually contains.
Releases and citation
Every version is released once, from a reviewed pull request, and the release is the single source for everything else:
- A pull request that changes the package raises one version in both plugin manifests, every
SKILL.md(metadata.version),CHANGELOG.mdandCITATION.cff. The Validate and package check enforces that, the exact AuthorityTech descriptor, and that no internal identifiers or secrets reach the README, changelog, citation or packaged plugin files; it also proves fresh installs in Codex and Claude Code. Semver: a minor version adds or graduates a method, a patch corrects wording or metadata, a major version changes a tool or endpoint. - When the bump merges, the same workflow deposits the tested files on Zenodo (it rebuilds
library.jsonwith the reserved DOIs and refuses to continue if any other file differs from the tested build), which gives the version its own DOI, then publishes the GitHub release withlibrary.json(every skill, version, DOI and sha256), the plugin ZIP, one archive per skill andSHA256SUMS. - machinerelations.ai/skill and jaxonparrott.com/skills, and their
/.well-known/agent-skills/index.json, rebuild fromhttps://github.com/Bramwell-Inc/machinerelations-plugins/releases/latest/download/library.json. Nothing is copied by hand.
Cite the library with its concept DOI, 10.5281/zenodo.23749768 (all versions); cite a version DOI only for work that used that exact version. Both are in library.json and on each release. CITATION.cff gives the author record. The library's Wikidata item is Q141909117.
A skill can carry metadata.title and metadata.summary (a human name and a one-sentence practitioner summary; not the description trigger text). Pages use them when present.
Directory listings (Claude, ChatGPT) update through their own review and can lag the latest release. The remote MCP service owns the Index's data and interpretation; daily data never requires a plugin release. The review/ captures and video are dated evidence, not current API documentation.