AI Boost vs Beacon

AI Boost and Beacon 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.

AI Boost

MCP server for capturing and injecting developer expertise as searchable, reusable context for LLM agents.

Beacon

Beacon is an open-source endpoint telemetry layer that runs locally alongside AI agents, capturing prompts, tool calls, file modifications, and approval workflows before any of that activity disappears into the void. It normalizes that telemetry and forwards it to SIEM platforms like Wazuh, Elastic, or Splunk, so security teams can apply the same detection logic they already run against the rest of the fleet. The architecture is self-hosted by design — no data leaves the endpoint unless you route it there yourself. The project is early-stage; the plugin ecosystem covers the major local agent harnesses but gaps exist for less common runtimes. Teams with agents not yet on the supported list write custom collector plugins — which means more surface area to maintain.

Attribute	AI Boost	Beacon
Pricing	Paid	Free
Free trial	No	No
Open source	No	Yes
Has API	Yes	No
Self-hosted option	No	Yes
Platforms	Web (MCP server), integrates with Cursor, Claude Code, and generic MCP clients	Linux, macOS, Windows
Pros	Solves real gap: agents get curated, structured expertise instead of noisy memory replays Private by default with strong commitments: never indexed, sold, or used for training Seamless integration: one MCP config, works across all agent clients and projects Semantic + keyword indexing ensures correct boosters surface at the right moments	Runs entirely on the local endpoint with no external data forwarding required, so organizations in regulated industries can capture AI agent telemetry without breaching data residency requirements. Normalizes agent activity into structured telemetry compatible with Wazuh, Elastic, and Splunk, so security teams can write detection rules against AI agent behavior using the same tooling they already maintain for the rest of the infrastructure. Captures the full activity chain — prompts, tool calls, file edits, approval workflows — which means audit trails hold up when a compliance team asks exactly what an agent touched and when, rather than reconstructing context after the fact. MIT-licensed and free with no paid tier, so there is no licensing negotiation before a regulated-industry proof of concept, and the full source is auditable by the security team before deployment. Structured for MDM-managed deployments, so enterprise IT teams can push Beacon alongside agent runtimes through existing device management pipelines rather than requiring manual per-machine setup.
Cons	Pricing model and tiers not clearly communicated on the vendor site Requires agents to support MCP protocol (limits compatibility to newer tools) Booster quality and relevance depend on human curation; poor capture = poor suggestions	Plugin coverage is scoped to the major local agent harnesses the project explicitly supports; agents running on runtimes outside that list produce no telemetry until a custom collector plugin is written and maintained — which delays security coverage for any team adopting a newer or less common agent framework. There is no hosted dashboard or managed backend, which means the security team owns the full stack: endpoint deployment, SIEM routing, schema mapping, and alert logic. Teams without an operational SIEM who want a turnkey monitoring UI will abandon Beacon for a hosted observability product before the first sprint ends. The project carries a small contributor base at the time of publication; teams depending on active maintenance for fast-moving agent runtimes accept the risk that plugin support lags runtime updates, requiring internal engineering to bridge the gap or switch to a vendor with a dedicated support contract.

Bottom line

AI Boost is paid while Beacon is free; Beacon is open source; only AI Boost exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between AI Boost and Beacon?

AI Boost is Paid, while Beacon is Free and open source. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is AI Boost better than Beacon?

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.