--- title: "Agen.co in the Machine Relations Index" description: "Canonical domain: agen.co" canonical: "https://machinerelations.ai/index/domains/agen.co" --- # Agen.co in the Machine Relations Index Canonical URL: https://machinerelations.ai/index/domains/agen.co Canonical domain: agen.co Source role: Other observed source Release mri_score_v2.1+2026-11-03+92e5b18cc6e2; methodology mri_score_v2.1; generated 2026-11-03; window 2026-05-10 to 2026-11-03; artifact c812e2190baa. agen.co appeared as a cited source in 2 of 35,433 monitored answer runs (0.01%) from 2026-05-10 to 2026-11-03. ## How the Site Describes Itself > Agen.co is the AI agent governance platform. Secure, audit, and control how AI agents access enterprise tools and data across every MCP server and identity. agen.co describes itself this way in the description tag on its homepage, read on November 3, 2026. It is the source's own wording, quoted as found, not a finding of this Index. ## Overall Evidence - Citation rate: 0.01% - Cited runs: 2 of 35,433 - Days cited: 2 of 171 - Engine breadth: 1 observed engines (perplexity) - Confidence: Collecting - Standing: collecting · 0.01% across 2/35,433 observed runs ## Observed Segments | Category | Question shape | State | Cited runs | Observed runs | Run dates | Rate | Standing | |---|---|---|---:|---:|---:|---:|---| | [AI Security & Privacy](https://machinerelations.ai/index/categories/ai-security-privacy) | [Problem-first research](https://machinerelations.ai/index/categories/ai-security-privacy/problem_first) | published | 2 | 277 | 13 | 0.72% | #148 of 513 | ## Citation History agen.co was first cited in a monitored answer run on October 26, 2026, and most recently on November 2, 2026, with cited runs in 2 of the 2 months from then to this release. The release window opens 2026-05-10, so an earlier citation would not show here. A month's rate is the share of all monitored answer runs that month that cited this domain. The latest month is still collecting. | Month | Cited runs | Observed runs | Rate | |---|---:|---:|---:| | October 2026 | 1 | 16,496 | 0.01% | | November 2026 (to 2026-11-03) | 1 | 950 | 0.11% | ## By Answer Engine An engine's rate is its cited runs over every monitored run that engine answered in the window. Engines answer different numbers of runs, so compare rates, not counts. | Engine | Cited runs | Engine's observed runs | Rate | |---|---:|---:|---:| | [Perplexity](https://machinerelations.ai/index/engines/perplexity) | 2 | 8,461 | 0.02% | | [ChatGPT](https://machinerelations.ai/index/engines/chatgpt) | 0 | 8,343 | 0.00% | | [Claude](https://machinerelations.ai/index/engines/claude) | 0 | 8,381 | 0.00% | | [Gemini](https://machinerelations.ai/index/engines/gemini) | 0 | 6,893 | 0.00% | | [Google AI Mode](https://machinerelations.ai/index/engines/google_ai_mode) | 0 | 2,081 | 0.00% | | [Google AI Overviews](https://machinerelations.ai/index/engines/google_ai_overviews) | 0 | 1,274 | 0.00% | ## Peers Agen.co holds its best segment rank, #148 of 513, in AI Security & Privacy / Problem-first research, at 0.72%. 95 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-security-privacy/problem_first | Rank | Source | Source role | Segment citation rate | Against this source | |---|---|---|---:|---| | #101 of 513 | [Accordshield.com](https://machinerelations.ai/index/domains/accordshield.com) | Other observed source | 1.08% | +0.36 pts | | #102 of 513 | [Accountablehq.com](https://machinerelations.ai/index/domains/accountablehq.com) | Other observed source | 1.08% | +0.36 pts | | #103 of 513 | [BleepingComputer](https://machinerelations.ai/index/domains/bleepingcomputer.com) | Editorial publication | 1.08% | +0.36 pts | | #147 of 513 | [Advent-of-ai-security.com](https://machinerelations.ai/index/domains/advent-of-ai-security.com) | Other observed source | 0.72% | Same rate | | #149 of 513 | [Agileblue.com](https://machinerelations.ai/index/domains/agileblue.com) | Vendor-owned source | 0.72% | Same rate | | #247 of 513 | [Alignmentforum.org](https://machinerelations.ai/index/domains/alignmentforum.org) | Other observed source | 0.36% | -0.36 pts | | #248 of 513 | [Alpacadatalab.com](https://machinerelations.ai/index/domains/alpacadatalab.com) | Other observed source | 0.36% | -0.36 pts | | #249 of 513 | [Amazonaws.com](https://machinerelations.ai/index/domains/amazonaws.com) | Other observed source | 0.36% | -0.36 pts | ## Citation Machine Relations Index (MRI), Machine Relations Research — machinerelations.ai. Agen.co (agen.co), 0.01% citation rate, 2 of 35,433 monitored answer runs, 2026-05-10 to 2026-11-03. Release mri_score_v2.1+2026-11-03+92e5b18cc6e2. https://machinerelations.ai/index/domains/agen.co. CC BY 4.0. APA Parrott, J. (2026). Agen.co (agen.co) in the Machine Relations Index (Version mri_score_v2.1+2026-11-03+92e5b18cc6e2) [Data set]. Machine Relations Research. https://machinerelations.ai/index/domains/agen.co https://doi.org/10.5281/zenodo.23652423 BibTeX ```bibtex @misc{parrott2026mriagenco, author = {Parrott, Jaxon}, title = {Agen.co (agen.co) in the Machine Relations Index}, year = {2026}, version = {mri\_score\_v2.1+2026-11-03+92e5b18cc6e2}, publisher = {Machine Relations Research}, url = {https://machinerelations.ai/index/domains/agen.co}, 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/agen.co/badge.svg [![Agen.co in the Machine Relations Index: 0.01% cited in monitored answer runs, 2 of 35,433 runs · Collecting. Machine Relations Research.](https://machinerelations.ai/index/domains/agen.co/badge.svg)](https://machinerelations.ai/index/domains/agen.co) 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)