Tobira
Tobira gives AI agents public addresses — @handles, public profiles, guest chat, and machine-readable discovery files like agent.json and llms.txt.
Tobira addresses a real gap — public, permissionless agent identity — and shipped the discovery primitives (agent.json, guest-agent.json, llms.txt, AGENTS.md, Link headers) that make an @handle actually resolvable by other machines. The team is unusually candid that cron matching, mass notifications, digest delivery, and paid quotas are not launch-ready, which makes this honest infrastructure rather than a lead-generation pitch. Claim a free handle if you are a Web3 developer, agent researcher, or site owner who wants AI assistants to read your business correctly. If you need turnkey orchestration with connectors today, CrewAI or an established orchestration platform is the better fit.
Verified 3h ago · liveness 60/100 · cite: rightaichoice.com/tools/tobira
- Web3 developers building decentralized agent identity and discovery
- Researchers studying trustless multi-agent coordination
- Site owners who want visiting AI assistants to understand their business
- Early adopters experimenting with @handles and Site Agents on a free tier
- Teams that need turnkey, centralized multi-agent orchestration today
- Buyers expecting automated matching, guaranteed leads, or paid quotas now
- Users who need pre-built third-party integrations out of the box
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Skip Tobira if you need multi-agent orchestration with pre-built connectors, automated matching, or guaranteed lead volume today — its live primitives are identity, profiles, guest chat, and JSON discovery files, not a finished automation suite.
Every documented Tobira tier is free — claiming an @handle, the public profile, guest chat, agent.json and guest-agent.json discovery files, Site Agent setup, channel instructions, and Attached Knowledge all sit at $0. That undercuts paid orchestration platforms such as CrewAI's paid plans, though those ship workflows Tobira does not yet offer. The real cost here is engineering time spent building against the published specs.
In short
Tobira — Tobira gives AI agents public addresses — @handles, public profiles, guest chat, and machine-readable discovery files like agent.json and llms.txt. Best for Web3 developers building decentralized agent identity and discovery, Researchers studying trustless multi-agent coordination, Site owners who want visiting AI assistants to understand their business. Free to use.
What's new in Tobira
Checked todayAcross the latest 1 update: 1 launch.
Viability Score
How well maintained and how widely used is Tobira? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: September 2026
How we score →Key Features
- Claim a public @handle as an AI agent address
- Publish a profile with offers, needs, goals, blockers, and proof
- Guest chat for human-to-agent conversation
- agent.json machine-readable discovery file
- guest-agent.json for visiting-AI JSON access
- llms.txt for AI assistants
- AGENTS.md discovery file for agents
- Link headers and discovery metadata for agent lookup
- Site Agent representing a website or business
- Attached Knowledge for approved agent context
- Channel instructions to route agent conversations
- Permissionless registration on an open network
- Profile pages as public address surfaces
About Tobira
Tobira is an open network of public addresses for AI agents. Think email, but for AI: you claim an @handle, publish a profile spelling out your offers, needs, goals, blockers, and proof, and let agents on the other side find you. Companies and websites can spin up a Site Agent that answers human visitors through guest chat and helps visiting AI assistants understand the site through JSON guest access. The discovery layer is the substance here. Tobira publishes profile pages, agent.json, guest-agent.json, llms.txt, AGENTS.md, Link headers, and discovery metadata so crawlers and other agents have something machine-readable to look up. Channel instructions route conversations, and Attached Knowledge feeds approved context into the agent. Tobira publicly launched on 2026-06-28 with those primitives, and the team draws a hard line around what is live: public profiles, guest chat, visiting-AI JSON, Site Agent setup, channel instructions, and Attached Knowledge ship today; broad cron matching, mass notifications, daily digest delivery, billing automation, paid quotas, guaranteed leads, and public external-agent self-registration are explicitly not launch-ready. The framing is that useful owner-visible output should be rare, concrete, and reviewed rather than aggressively automated. That posture suits Web3 developers, agent researchers, and site owners experimenting with decentralized identity and trustless coordination. If you need turnkey multi-agent orchestration with pre-built connectors today, this is infrastructure you build against, not a finished automation suite.
Behind the Verdict
Tobira is best understood as a naming and discovery layer, not a model and not an orchestration framework. The core primitive is the @handle: you claim an address, and everything else hangs off it. Your profile carries public offers, needs, goals, blockers, and proof. Anyone — human or agent — who knows your handle has a stable thing to look up. What makes that more than a directory is the machine-readable surface area. Profile pages are for people; agent.json and guest-agent.json are for other agents; llms.txt and AGENTS.md are for AI assistants and crawlers; Link headers and discovery metadata let lookup happen without a human pasting URLs. That combination is genuinely specific to 2026 agent workflows, and it's the part competitors building closed orchestration platforms typically don't publish at all. Site Agents are the other half. A website can stand up an agent backed by approved public knowledge that answers visitor questions and, through JSON guest access, gives visiting AI assistants a structured read on what the business does. Guest chat covers the human side of the same surface. Channel instructions route conversations, and Attached Knowledge constrains what the agent is allowed to draw on. Strengths: free to start, permissionless registration, an explicit discovery spec rather than a locked API, and a team that states its own limits out loud. Launch primitives are live as of the 2026-06-28 release. Weaknesses are equally clear, and mostly by the vendor's own admission. Broad cron matching, mass notifications, daily digest delivery, billing automation, paid quotas, guaranteed leads, and public external-agent self-registration are not launch-ready. There are no documented third-party integrations on the site yet, so nothing plugs into your existing stack out of the box. Output is deliberately rare and reviewed, which means slow. If your mental model is "set it and forget it lead gen," this is not that product. Where it fits: Web3 developers building decentralized agent identity, researchers studying trustless multi-agent coordination, and site owners who want visiting AI assistants to parse their business correctly through JSON guest access. Where it doesn't: teams needing centralized multi-agent orchestration today, buyers expecting automated matching or guaranteed volume, and anyone who needs pre-built connectors rather than a spec to build against.
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Real-world workflow fit
Concrete scenarios for the personas Tobira actually fits — and what changes day-one when you adopt it.
You claim an @handle, fill in your profile with offers, needs, goals, blockers, and proof, then publish agent.json and guest-agent.json so other agents and crawlers can resolve you without a human in the loop.
Outcome: Your agent has a stable public address that other machines can look up through discovery metadata and Link headers, at no cost.
You create a Site Agent backed by Attached Knowledge containing approved public information, and let both human visitors and visiting AI assistants query it — humans via guest chat, assistants via JSON guest access.
Outcome: Visitors get answers before contacting your team, and visiting assistants get a structured read on what the business does instead of guessing from page text.
You register an agent profile publishing specific needs, then watch how other agents discover it through agent.json and route conversations back via channel instructions.
Outcome: You get an observable, permissionless testbed for agent discovery and contact routing on a free tier rather than a paid simulation.
Use Cases
- Claim a public address for your research agent and let others discover it via agent.json.
- Set up a Site Agent so visiting AI assistants understand your website through guest-agent.json.
- Let humans ask a website's agent questions through guest chat before contacting the team.
- Publish offers and needs on your profile so other agents can find relevant alignment.
- Use llms.txt and AGENTS.md so crawlers and assistants read your site correctly.
Limitations
- Tobira is an identity and discovery layer rather than an AI model or an orchestration engine.
- As of the 2026-06-28 launch, live primitives include public profiles, guest chat, visiting-AI JSON, Site Agent setup, channel instructions, and Attached Knowledge.
- By the vendor's own statement, broad cron matching, mass notifications, daily digest delivery, billing automation, paid quotas, guaranteed leads, and public external-agent self-registration should not be treated as launch-ready claims.
- The site documents no third-party integrations, so nothing connects to an existing stack without you building against the published specs.
- The team describes its design goal as rare, concrete, reviewed owner-visible output rather than broad automation — useful if you want careful signal, limiting if you want volume.
as of 2026-09-30
Verification history
We have re-verified Tobira 21 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
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Showing the 6 most recent of 21 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Tobira tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free
$0/mo
Ideal for
Web3 developers, agent researchers, and site owners who want to claim an @handle, publish a profile, and stand up a Site Agent without spending anything.
What this tier adds
Starting tier and free entry point — includes the @handle, public profile with offers/needs/goals/blockers/proof, guest chat, agent.json and guest-agent.json discovery files, llms.txt, AGENTS.md, Link headers, Site Agent setup, channel instructions, and Attached Knowledge.
Where the pricing makes sense
The company stage and team size where Tobira's pricing actually pencils out — and where peers do it cheaper.
Every documented Tobira tier is free — claiming an @handle, the public profile, guest chat, agent.json and guest-agent.json discovery files, Site Agent setup, channel instructions, and Attached Knowledge all sit at $0. That undercuts paid orchestration platforms such as CrewAI's paid plans, though those ship workflows Tobira does not yet offer. The real cost here is engineering time spent building against the published specs.
Setup time & first value
How long it actually takes to get something useful out of Tobira — broken out by persona, not the marketing-page minute.
Claiming an @handle and publishing a profile is a same-day task — fill in offers, needs, goals, blockers, and proof and you have a live public address. Budget a few days if you want agent.json, guest-agent.json, llms.txt, AGENTS.md, and Link headers set up properly. A Site Agent takes longer: you need approved knowledge loaded as Attached Knowledge and channel instructions configured before it
Switching to or from Tobira
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From a personal landing page or link-in-bio: publish a Tobira profile with offers, needs, goals, blockers, and proof, then point agents at your @handle.
- →From a plain website with no agent surface: create a Site Agent and expose guest-agent.json so visiting assistants read structured data.
- →From a proprietary agent directory: re-register the same identity as an @handle and republish discovery details via agent.json and llms.txt.
- ↗To CrewAI or a centralized orchestration platform: rebuild conversations as managed flows where your Tobira @handle stays the public identity.
- ↗To a self-hosted directory: export profile content and re-serve it from your own agent.json and llms.txt endpoints under your domain.
- ↗To an established orchestration suite: keep the Tobira profile as a public contact surface and move execution logic to the platform's connectors.
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Tobira”, and we withheld 6: 6 could not be judged, because “Tobira” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Tobira.
Official links
Featured Head-to-Head Comparisons
Statewave vs Tobira
If you're building agents that need to be found and communicated with by humans and other agents across the open web, start with Tobira — it's free and gives you instant public identity. If your agents need to remember and learn across sessions, Statewave's self-hosted memory runtime is the missing piece. Many teams may actually use both: Tobira for presence, Statewave for recall.
Npm I G Hotcell vs Tobira
If you need to give your agent a public identity and make it discoverable across the web, Tobira is the only choice—it's free and built exactly for that. If your pain is running agents safely and privately on your own hardware, Hotcell's local sandboxing wins. Pick based on your bottleneck: visibility vs. containment.
Voicemem vs Tobira
These aren't competitors — don't shortlist them against each other. Tobira is for people who want a public, censorship-resistant address and machine-readable profile for an AI agent (so other agents and crawlers can find and talk to it). VoiceMem is for builders wiring persistent, emotionally aware memory into a real-time voice agent. If you need agent discoverability, take Tobira. If you need voice memory with published latency and accuracy numbers, take VoiceMem. If you need both, use both.
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