Best open-source AEO tools (2026)
The most complete open-source answer engine optimization tool is Elmo: MIT-licensed, free to self-host, and auditable down to how each metric is computed. Smaller projects like OneGlanse, GEO/AEO Tracker, and Gego exist alongside it. This is a thin, early space, and the honest picture is one mature platform, a handful of small projects, and the option to script your own checks.
Key takeaways
- Elmo is the most complete open-source answer engine optimization tool, MIT-licensed and free to self-host across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews.
- That is not just our claim. On public GitHub data as of 11 August 2026, Elmo leads this field on stars, contributors, releases, and length of continuous history. Nine people have contributed besides the lead developer; across every other project below combined, that number is four.
- The rest of the field is small. OneGlanse, GEO/AEO Tracker, and Gego are real but early, mostly single-developer projects.
- GetCito is a fork of Elmo since July 2026, so it is a lagging fork of another tool on this list.
- Canonry is capable but source-available under the FSL, not fully open source until it converts to Apache 2.0.
- Open source buys you three things a hosted tool cannot: auditable metrics, data you keep on your own infrastructure, and no vendor lock-in.
- "Free to self-host" is not free to run. You supply the LLM API keys and the infrastructure.
Why open source matters for answer engine optimization
Most AI visibility tools are closed and hosted. You send them your prompts, and you trust the score they hand back. Open source changes both halves of that deal. You can read how a metric is built, and you can run the whole thing on your own infrastructure, so your prompts and history never leave your environment.
For a number that might land in a board report or shape a content budget, being able to audit it matters. So does owning your data outright, with no vendor holding your visibility history and nothing to migrate off if you decide to leave. The trade is upkeep. You run the infrastructure, and you keep it current as engines change.
The best open-source AEO tools at a glance
| Tool | License | Self-host | What it tracks | Best for |
|---|---|---|---|---|
| Elmo | MIT, fully open source | Yes, free | Mentions and citations across ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews | A complete platform you own and audit |
| OneGlanse | MIT, fully open source | Yes | ChatGPT, Gemini, Perplexity, Claude, Google AI Overview | Capturing answers from AI web UIs, not just APIs |
| GEO/AEO Tracker | MIT, fully open source | Yes, local-first | ChatGPT, Perplexity, Gemini, Copilot, Google AI Overview, Grok | A single-user local dashboard with your own keys |
| Canonry | Source-available (FSL, Apache 2.0 later) | Yes | Gemini, ChatGPT, Claude, Perplexity, local LLMs; server-log AI traffic | Agent-first workflows and log-level attribution |
| GetCito | MIT | Yes | Elmo's engine set as of July 2026 | Nothing — it is a fork of Elmo, run Elmo instead |
| Gego | GPL-3.0, fully open source | Yes, via Docker | Citations, brand mentions, and keywords across OpenAI, Anthropic, Google, Perplexity, Ollama | Scheduled tracking driven from a CLI or REST API |
By the numbers
Feature grids are easy to write and hard to verify. Public repository activity is neither. These are the numbers as of 11 August 2026, and the column that matters most is contributors beyond the lead developer: a project with one committer is one person's spare time away from being abandoned.
| Project | Stars | Commits | Contributors | Beyond the lead dev | Releases | First commit | Commits, last 90d |
|---|---|---|---|---|---|---|---|
| Elmo | 233 | 862 | 10 | 9 | 19 | Jul 2025 | 206 |
| GEO/AEO Tracker | 229 | 28 | 1 | 0 | 8 | Feb 2026 | 19 |
| GetCito | 161 | 35 | 2 | 1 | 1 | Nov 2025 | 24 |
| OneGlanse | 146 | 496 | 1 | 0 | 0 | Apr 2026 | 0 |
| Canonry | 109 | 832 | 3 | 2 | 7 | Mar 2026 | 500 |
| Gego | 84 | 118 | 2 | 1 | 12 | Oct 2025 | 64 |
OneGlanse's 496 commits landed almost entirely in one burst, between 15 April and 10 May 2026. It has not had a commit since, and it has never cut a release. High commit counts and sustained maintenance are different things.
Then there is GetCito, where the numbers tell the story better than any argument. Its repository contains 35 commits, 27 of them from humans, across its entire lifetime, for a codebase of well over 100,000 lines. That is because 131,716 of those lines arrived in a single import of Elmo's code in July 2026. Stars measure attention, not work.
The open-source options, tool by tool
The honest picture is that this is a thin, early space. Elmo is the most complete open-source option, released under the MIT license with broad engine coverage. The other open-source projects we track are below. They are smaller and earlier, but they are real and worth knowing about.
GetCito
DA fork of Elmo — if you are considering GetCito, use Elmo instead
GEO/AEO Tracker
FOpen-source, self-hosted AI visibility dashboard
Gego
FGPL-3.0 self-hosted GEO tracker with CLI and dashboard
OpenSight
FMIT-licensed AI visibility tracker with a free hosted tier
Lettertrace
FMIT-licensed, bring-your-own-key AI visibility monitor
Genwolf
FDaily prompt tracking across ChatGPT, Gemini, and Perplexity
Elmo
Elmo is the most complete open-source AI visibility platform, and the reason this list has a clear top pick. It is released under the MIT license, free to self-host, and every metric is computed by code you can read. It tracks how AI answer engines mention and cite your brand across ChatGPT, Claude, Perplexity, Gemini, and Google's AI Overviews, among other engines, then turns that into a visibility score, citation analytics, brand-mention tracking, and competitor benchmarking. You can export everything through the API, and agencies can white-label it.
It fits teams that want to own their AEO data outright. The self-hosted core runs on Docker and PostgreSQL. You supply your own model API keys, which carry usage costs, and there is no license fee or per-seat charge. Be clear on what it is not: Elmo does not do sentiment analysis, prompt-volume estimates, content generation, shopping-result tracking, or geographic breakdowns. It measures visibility and citations well, and leaves the content work to you. Managed cloud hosting is available for teams that would rather not run the infrastructure.
OneGlanse
OneGlanse is an MIT-licensed, self-hosted tracker covering ChatGPT, Gemini, Perplexity, Claude, and Google AI Overview. Its distinguishing choice is how it collects answers. Instead of hitting the model APIs, it captures responses through authenticated accounts on the AI web interfaces, which is closer to what a real user sees. Data lands in a ClickHouse backend on your own infrastructure, and you bring your own API keys.
It suits developers who care that the answers being scored come from the actual chat products, not the API surface, and who are comfortable standing up ClickHouse. The idea is good and the approach is genuinely different from everything else here. Check the activity before you build on it, though. Its 496 commits landed in a single burst between 15 April and 10 May 2026, and the repository has not had a commit since. It has one contributor and no tagged releases.
GEO/AEO Tracker
GEO/AEO Tracker is an MIT-licensed, local-first dashboard for watching brand visibility across six platforms: ChatGPT, Perplexity, Gemini, Copilot, Google AI Overview, and Grok. It stores everything client-side in IndexedDB, with no external database to run, and you provide your own keys for data fetching and model inference.
The local-first design is the appeal. Nothing leaves your browser, setup is light, and the platform coverage is broad for a solo project. The flip side is scope. It is a single-user tool built around one person's dashboard, not a team platform, so treat it as a personal monitor rather than shared infrastructure.
Canonry
Canonry is the most ambitious of the independent projects. It is a self-hosted, agent-first AEO platform that tracks how Gemini, ChatGPT, Claude, Perplexity, and local models cite your site, ingests server logs to measure AI-driven traffic, and integrates with Google Search Console, GA4, Bing Webmaster, and Google Business Profile. A built-in agent named Aero exposes a 67-tool MCP adapter, and clients are configured declaratively in YAML.
One honest caveat on the "open source" label. Canonry ships under the FSL-1.1-ALv2, a source-available license that converts to Apache 2.0 after two years. You can read and self-host the code today, but it is not OSI open source in the strict sense until that conversion. If server-log attribution and agent workflows matter to you, it is worth a look, with that license nuance understood.
GetCito
If you are considering GetCito, use Elmo instead. GetCito is a fork of Elmo. On 10 July 2026, it replaced its codebase with Elmo's in one pull request of 847 files.
Everything GetCito offers today it inherited from Elmo. There is little reason to run a fork when the upstream project is free and moving faster — 17 commits to Elmo's 98 in the month after the fork. GetCito vs Elmo.
Gego
Gego is a GPL-3.0 GEO tracker you self-host from Docker Hub. It schedules prompts across generative engines on a cron, then captures citations, brand mentions, and extracted keywords, with competitor and alias tracking alongside them. It queries OpenAI, Anthropic, Google, and Perplexity, and it will also point at Ollama or a custom provider, so you can run the whole loop against local models. There is a dashboard, a CLI, and a REST API.
Two caveats. A full deployment expects PostgreSQL, MongoDB, and etcd, which is a heavier footprint than a single-container deploy. And GPL-3.0 is copyleft rather than permissive, so unlike the MIT projects here it constrains what you can build on top of it and redistribute.
Build it yourself: scripting AI visibility checks
If no existing tool fits, the underlying job is not complicated to script. Send your prompts to the model APIs, directly or through a router like OpenRouter, then parse each response for your brand name and any links back to your site. Store the results and repeat on a schedule, because a single run is a snapshot and answers shift over time.
The catch is everything around that loop. You have to cover enough engines, handle the ones without clean APIs, keep it running, and build some way to actually read the output. That upkeep is most of what you pay for when you buy a tool, or skip by self-hosting one that already does it.
Open source vs enterprise AEO software: the real tradeoffs
The real choice is not open source versus paid. It is who does the work and who holds the data. Enterprise AEO software gives you a hosted dashboard your team can open tomorrow, managed engine coverage, and a vendor who keeps it running, in exchange for a subscription and a scoring model you cannot inspect. Self-hosting an open-source tool inverts that: no license fee, auditable metrics, and your data on your own machines, with the cost moving from a subscription line to engineering time.
| Open source, self-hosted | Managed, paid | |
|---|---|---|
| Cost | No license fee. You pay for infrastructure and AI provider API usage. | A subscription, often metered by prompt or seat. |
| Setup | You deploy and maintain it yourself. | Sign up and start tracking. |
| Transparency | Read the code and verify how every metric is built. | The scoring is usually a black box. |
| Data ownership | Prompts and history stay on your infrastructure. | Your data lives in the vendor's dashboard. |
| Coverage and upkeep | On you, or the project's maintainers. | The vendor handles engine coverage and updates. |
How to choose
Start with how you will use it, not a feature grid. If you want full control, auditable numbers, and no per-seat fees, a self-hosted open-source tool fits, and Elmo is the most complete one on offer, and the one the public GitHub numbers actually favor on stars, contributors, releases, and sustained history alike. If you want the same open code with the smallest footprint, GEO/AEO Tracker's local-first design is worth a look, bearing in mind it is one developer and 28 commits. If your priority is server-log attribution, Canonry goes furthest, with its license caveat and single-maintainer concentration in mind.
The one thing worth weighing above features is whether anyone will still be maintaining the project in a year. That is what the contributor column is for. A tool with one committer is one person's spare time away from being abandoned, and in a field where models get renamed and APIs shift every few months, an unmaintained tracker quietly stops being correct rather than visibly breaking.
Then weigh coverage, maintenance, and your own capacity to run infrastructure against what a managed subscription would cost. If the honest answer is that you have no time to self-host, that is useful to know early: see the best AEO tools for hosted options, or the free AI visibility tools guide for what a zero-budget setup can and cannot do. Whatever you pick, the job is the same: get a reliable, repeatable read on whether AI answers cite you, from a tool you trust because you can see how it works.
/ FAQ
Frequently Asked Questions
- What are the best open-source AEO tools?
- Elmo is the most complete open-source answer engine optimization tool: MIT-licensed, free to self-host, and covering ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews. Public GitHub data as of 11 August 2026 backs this up — Elmo leads the field on stars, contributors, and releases, and is the only project with a meaningful number of contributors beyond one person. Smaller projects fill out the rest of the space, including OneGlanse, GEO/AEO Tracker, and Gego, most of them single-developer efforts. Canonry is actively developed but source-available rather than fully open source. GetCito replaced its codebase with Elmo's in July 2026, so running it means running a lagging fork of Elmo.
- Which open-source AEO tool is the most actively maintained?
- By GitHub activity on 11 August 2026, Elmo has the strongest sustained record: 862 commits over 13 months, 206 in the last 90 days, 19 releases, and 10 contributors. Canonry logged more raw commits in that window (500), but 451 came from one developer and it is source-available rather than open source. OneGlanse has not had a commit since 10 May 2026, and GEO/AEO Tracker and GetCito have 28 and 35 total commits respectively.
- Is there an open-source AI visibility tracker?
- Yes. Elmo is an open-source AI visibility platform released under the MIT license, and you can self-host it for free. A few smaller open-source projects exist too, though the space is still early. For anything they don't cover, you can script your own checks against the AI model APIs.
- Is there an open-source alternative to Profound or enterprise AEO tools?
- Yes. Elmo is an open-source, self-hostable alternative to enterprise platforms like Profound. It tracks how AI answer engines mention and cite your brand, benchmarks competitors, and exports your data, all under the MIT license with every metric computed by code you can read. You run the infrastructure and supply your own model API keys instead of paying a subscription.
- Should I use GetCito or Elmo?
- Use Elmo. If you are considering GetCito, Elmo is what you actually want, because GetCito is a fork of it — on 10 July 2026 it replaced its codebase with Elmo's. Everything it offers came from Elmo, and it has shipped less since — 17 commits to Elmo's 98 in the month after the fork — so it is drifting further behind rather than building past it.
- Can I self-host an AEO tool?
- Yes. Several open-source answer engine optimization tools are built to self-host. Elmo runs on Docker and PostgreSQL on your own infrastructure, so your prompts and visibility history never leave your environment. OneGlanse, GEO/AEO Tracker, and Canonry are self-hostable too. You bring your own LLM API keys, which carry usage costs, but there is no license fee or per-seat charge.
- Can I build my own AI visibility tool?
- You can. The core loop is straightforward: send your prompts to the model APIs, directly or through a router like OpenRouter, parse each answer for brand mentions and citations, and log the results over time. The work is in maintaining it, covering enough engines, and running it at scale, which is what a finished tool handles for you.
- Why use an open-source AI visibility tool?
- Because you can audit it and own it. With open source, you read exactly how each visibility metric is collected and computed instead of trusting a black-box score that might land in a board report. You self-host it, so prompts and history stay on your own infrastructure, and there is nothing to migrate off if you switch. No vendor lock-in.
- Is Elmo really open source?
- Yes. Every line of Elmo is open source under the MIT license and available on GitHub. You can read exactly how each metric is collected and computed, self-host it on your own infrastructure for free, and export your data at any time.
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