Promptary vs Proxon

Promptary and Proxon are both inference engines & infra tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

Promptary

The core workflow is a prompt registry: you define structured prompts with schemas, agents pull them over the network at execution time, and you update once rather than redeploy everywhere. Output validation and repair is built into the loop, so malformed agent responses get a correction pass before they propagate. The MCP server integration means Claude, Cursor, and other MCP-compatible clients can connect to your prompt store directly. Where this breaks is the absence of a self-hosted option — every prompt contract and schema lives on Gildara's infrastructure, which is a hard stop for teams with data residency requirements. Those teams typically move toward self-managed registries or bake schema validation into their own API layer.

Proxon

Proxon surfaces AI activity across teams into a single operating record: which tools and agents exist, who owns them, what they cost, and whether they're producing results. The attribution layer connects token spend to specific teams and workflows rather than burying it in an undifferentiated API bill. Adoption tracking lets leadership identify high-performing workflows and push them to teams still running ad hoc. The ceiling appears when you need deep integrations with proprietary internal tooling — the vendor page describes discovery and governance but does not detail connector coverage, so teams with niche or self-built stacks will need to validate fit before committing.

Attribute	Promptary	Proxon
Pricing	Paid	Paid
Price	$0/mo	—
Free trial	No	No
Open source	No	No
Has API	Yes	Yes
Self-hosted option	No	No
Platforms	REST API, MCP Server, Telegram, Chrome Extension	Web
Pros	Runtime prompt fetching over API means updating a prompt once in the registry propagates to every agent on the next execution cycle, so you avoid the versioning drift that comes from managing prompts inside individual codebases. Structured prompt schemas give agents and your validation layer a shared contract, which means malformed outputs can be caught and repaired in-loop rather than silently corrupting the next step in your pipeline. MCP server support lets Claude, Cursor, and other MCP-compatible clients draw from the same prompt registry as your custom agents, so you stop maintaining separate prompt sources for IDE tooling versus deployed agents. A single subscription covering unlimited agents means cost scales with your team's usage tier, not with the number of agents you spin up — which removes the pricing incentive to share prompts sloppily across agents that should have distinct contracts.	Single inventory of all AI tools, agents, and workflows across the organization, so leadership stops discovering production AI systems by accident during an incident or audit. Spend attribution down to the team, workflow, and model level, which means the monthly API bill becomes an actionable breakdown instead of a number nobody can explain. Built-in optimization signals that flag redundant model work and suggest caching or routing changes, so engineering doesn't need a separate cost analysis pass to find waste. Adoption trend tracking by team, which means high-performing workflows can be identified and pushed to underperforming teams rather than staying siloed with whoever built them first. API access for exporting governance and cost data, so Proxon can feed into existing dashboards or alerting pipelines rather than requiring a separate login for every stakeholder.
Cons	No self-hosted option and no open-source codebase means every prompt contract, schema, and agent instruction lives on Gildara's infrastructure. Teams with data residency requirements, SOC 2 audit trails, or policies against third-party prompt storage hit this wall before they finish evaluation — at which point they build a self-managed registry or adopt a tool that ships a self-hosted tier. The scraped page content returned no substantive documentation or community evidence, which means there is precious little public signal on how the output repair loop behaves under edge cases, what happens when the MCP server is unreachable mid-agent-run, or what rate limits apply to runtime prompt fetches at scale. Teams that need to validate reliability before production commitment will find no community forum posts or open issue trackers to pressure-test claims against. The validator context confirms no self-host or repo exists, so teams that hit reliability or compliance limits have no path to fork or migrate their prompt contracts out of the platform — vendor lock-in on the registry layer is structural, not incidental.	The vendor page does not enumerate which AI platforms, model providers, or agent frameworks Proxon connects to natively. Teams running self-built or niche tooling will find gaps in the discovery layer — activity that runs outside supported connectors stays invisible, which defeats the core premise of a complete inventory. No self-hosted deployment option is described. Organizations in regulated sectors where activity metadata cannot leave their own infrastructure hit a hard architectural wall here, and at that point the evaluation moves to purpose-built on-premises governance tools regardless of what Proxon offers. Policy enforcement and approval flows are listed as capabilities but the vendor page does not show the depth of the rules engine. Teams that need granular, conditional access controls — for example, blocking specific models for specific data classifications — will need to pressure-test whether Proxon's governance layer goes deep enough or whether they need a dedicated AI access control product alongside it.

Bottom line

Promptary and Proxon are closely matched on pricing model, openness, and API availability — pick by feature set and platform support in the table above.

Frequently asked questions

What is the difference between Promptary and Proxon?

Promptary is Paid, while Proxon is Paid. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Promptary better than Proxon?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.