---
title: "Murf.ai in the Machine Relations Index"
description: "Canonical domain: murf.ai"
canonical: "https://machinerelations.ai/index/domains/murf.ai"
---

# Murf.ai in the Machine Relations Index

Canonical URL: https://machinerelations.ai/index/domains/murf.ai
Canonical domain: murf.ai
Source role: Other observed source
Release mri_score_v2.1+2026-10-31+2349fd99615c; methodology mri_score_v2.1; generated 2026-10-31; window 2026-05-10 to 2026-10-31; artifact 49aaafd42df1.

murf.ai appeared as a cited source in 1 of 34,483 monitored answer runs (0.00%) from 2026-05-10 to 2026-10-31.

## Overall Evidence

- Citation rate: 0.00%
- Cited runs: 1 of 34,483
- Days cited: 1 of 168
- Engine breadth: 1 observed engines (claude)
- Confidence: Collecting
- Standing: collecting · 0.00% across 1/34,483 observed runs

## Observed Segments

| Category | Question shape | State | Cited runs | Observed runs | Run dates | Rate | Standing |
|---|---|---|---:|---:|---:|---:|---|
| [AI Infrastructure](https://machinerelations.ai/index/categories/ai-infrastructure) | [Best tools](https://machinerelations.ai/index/categories/ai-infrastructure/best_x) | published | 1 | 251 | 13 | 0.40% | #294 of 364 |

## Citation Record

murf.ai has been cited in one monitored answer run, on October 31, 2026, by Claude, in answers to AI Infrastructure / Best tools questions. Other sources cited for AI Infrastructure questions: https://machinerelations.ai/index/categories/ai-infrastructure

## Peers

Murf.ai holds its best segment rank, #294 of 364, in AI Infrastructure / Best tools, at 0.40%. 155 sources on that leaderboard share that rate, and their order inside the tie is not a measured difference. Listed here: the nearest sources cited more and less often than it, and the sources beside it that share this best segment. Leaderboard: https://machinerelations.ai/index/categories/ai-infrastructure/best_x

| Rank | Source | Source role | Segment citation rate | Against this source |
|---|---|---|---:|---|
| #183 of 364 | [Meegle.com](https://machinerelations.ai/index/domains/meegle.com) | Other observed source | 0.80% | +0.40 pts |
| #184 of 364 | [Miraheze.org](https://machinerelations.ai/index/domains/miraheze.org) | Other observed source | 0.80% | +0.40 pts |
| #185 of 364 | [Murraycole.com](https://machinerelations.ai/index/domains/murraycole.com) | Other observed source | 0.80% | +0.40 pts |
| #186 of 364 | [Netflixtechblog.com](https://machinerelations.ai/index/domains/netflixtechblog.com) | Other observed source | 0.80% | +0.40 pts |
| #187 of 364 | [Nisai.dev](https://machinerelations.ai/index/domains/nisai.dev) | Other observed source | 0.80% | +0.40 pts |
| #188 of 364 | [Oceanbase.com](https://machinerelations.ai/index/domains/oceanbase.com) | Other observed source | 0.80% | +0.40 pts |
| #293 of 364 | [Modelriver.com](https://machinerelations.ai/index/domains/modelriver.com) | Other observed source | 0.40% | Same rate |
| #295 of 364 | [N-ix.com](https://machinerelations.ai/index/domains/n-ix.com) | Other observed source | 0.40% | Same rate |

## Other Records

- [Murf AI on Presspool](https://presspool.ai/companies/murf-ai): Presspool keeps a company record for Murf AI. Its record reads: “Murf AI builds text-to-speech voice models and sells a TTS API, AI voiceover studio and conversational voice agents to developers and businesses.” Presspool is a related party to the publisher of this Index, and its record is not source evidence for this dataset.

## Citation

Machine Relations Index (MRI), Machine Relations Research — machinerelations.ai. Murf.ai (murf.ai), 0.00% citation rate, 1 of 34,483 monitored answer runs, 2026-05-10 to 2026-10-31. Release mri_score_v2.1+2026-10-31+2349fd99615c. https://machinerelations.ai/index/domains/murf.ai. CC BY 4.0.

APA

Parrott, J. (2026). Murf.ai (murf.ai) in the Machine Relations Index (Version mri_score_v2.1+2026-10-31+2349fd99615c) [Data set]. Machine Relations Research. https://machinerelations.ai/index/domains/murf.ai https://doi.org/10.5281/zenodo.23652423

BibTeX

```bibtex
@misc{parrott2026mrimurfai,
  author = {Parrott, Jaxon},
  title = {Murf.ai (murf.ai) in the Machine Relations Index},
  year = {2026},
  version = {mri\_score\_v2.1+2026-10-31+2349fd99615c},
  publisher = {Machine Relations Research},
  url = {https://machinerelations.ai/index/domains/murf.ai},
  doi = {10.5281/zenodo.23652423},
  license = {CC-BY-4.0},
  note = {Machine Relations Index (MRI), Machine Relations Research — machinerelations.ai}
}
```

DOI: https://doi.org/10.5281/zenodo.23652423

Citation file: https://machinerelations.ai/CITATION.cff

## Badge

Badge image: https://machinerelations.ai/index/domains/murf.ai/badge.svg

[![Murf.ai in the Machine Relations Index: 0.00% cited in monitored answer runs, 1 of 34,483 runs · Collecting. Machine Relations Research.](https://machinerelations.ai/index/domains/murf.ai/badge.svg)](https://machinerelations.ai/index/domains/murf.ai)

The badge is live: it shows the current release, so it changes when the release changes, and it returns 404 if this domain leaves the released population. The link goes to this profile, and the alt text says what the badge shows.

## Use the data

The public JSON is https://machinerelations.ai/data/machine-relations-index.json. The release manifest is https://machinerelations.ai/data/mri-release-manifest.json. The domain CSV is https://huggingface.co/datasets/machine-relations/machine-relations-index/resolve/main/domains.csv. The Zenodo concept DOI is https://doi.org/10.5281/zenodo.23652423.

```bash
curl -fsSL "https://machinerelations.ai/data/machine-relations-index.json" -o machine-relations-index.json
curl -fsSL "https://machinerelations.ai/data/mri-release-manifest.json" -o mri-release-manifest.json
curl -fsSL "https://huggingface.co/datasets/machine-relations/machine-relations-index/resolve/main/domains.csv" -o domains.csv
curl -fsSL -L "https://doi.org/10.5281/zenodo.23652423" -o mri-zenodo.html
```

```python
import json
from urllib.request import urlopen

index_url = "https://machinerelations.ai/data/machine-relations-index.json"
with urlopen(index_url) as response:
    index = json.load(response)
print(index["generated"], index["total_domains"])
```

## Public Boundary

The public dataset reports citation rates, rankings, and evidence counts. It excludes internal query identifiers, raw cited URLs, and answer-engine provider payloads. MRI measures observed root-domain citations in monitored prompts; it does not measure all AI answers, recommendation quality, website traffic, or commercial performance. A citation does not prove source support, and MRI confidence is not an Answer-Source Fidelity grade.

## Related Sources

- [Machine Relations Index](https://machinerelations.ai/index)
- [Public JSON artifact](https://machinerelations.ai/data/machine-relations-index.json)
- [Release manifest](https://machinerelations.ai/data/mri-release-manifest.json)