Forall vs LocalCode

Forall and LocalCode are both cli coding agents 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.

Forall

Forall is an Apache-2.0 CLI agent from Astrio that generates spec-driven code alongside machine-checkable proofs, running entirely in your terminal or wiring into Cursor, Claude Code, or Codex via MCP. You describe what the code must do; the agent produces both the implementation and a formal proof you can verify independently. The verification step is not optional decoration — it runs against the spec, so a failing proof surfaces a real logical flaw before the code ships. The docs describe Rust, TypeScript, and Java as the supported targets, which covers a specific but meaningful slice of production codebases. Teams outside those languages hit a hard wall.

LocalCode

Type what you want, get a suggested command, approve it, and it runs — no API key, no network request, no telemetry. All inference runs on Apple Silicon through the Foundation Models framework, which means your file paths, hostnames, and search terms never travel anywhere. The workflow is strictly one-shot: one prompt, one command suggestion, one approval gate. There is no session memory, no chaining, and no multi-step automation. Teams that want anything beyond single-command suggestions will hit the ceiling of what this proof-of-concept was designed to do.

Attribute	Forall	LocalCode
Pricing	Paid	Free
Free trial	No	No
Open source	Yes	Yes
Has API	Yes	No
Self-hosted option	Yes	Yes
Platforms	CLI, terminal, MCP clients	Apple Silicon Mac, macOS 26+
Released	2026-07-17	—
Pros	Generates machine-checkable proofs alongside code, so correctness is verifiable by a tool rather than trusted on faith — eliminating the class of bugs that pass all tests but violate the spec. Apache-2.0 license with a self-hosted CLI path, which means the proof pipeline runs on your infrastructure without sending proprietary specs to a third-party service. MCP integration drops the agent directly into Cursor, Claude Code, or Codex via a config block, so teams avoid a context switch to a separate tool when they want verification mid-session. Spec-driven generation disciplines the coding workflow upfront, which means the spec ambiguities that normally surface in code review get resolved before the first line is written. Agentic execution runs specs-to-proof autonomously in the terminal, so verification does not require manual orchestration between separate tools for generation and checking.	All inference runs on-device via Apple Foundation Models, so file paths, hostnames, and search terms never leave the machine — which means no data-handling review before using it on sensitive internal systems. MIT-licensed with Go and Swift source fully available, so any developer can audit exactly what runs and modify the tool without negotiating a license or waiting on a vendor. A mandatory approval step before any command executes, so a misunderstood prompt cannot silently delete files or overwrite output — you review before it runs. No API key, account, or network connection required at runtime, so there is no quota to hit, no credential to rotate, and no outage dependency on a third-party service.
Cons	Language support is limited to Rust, TypeScript, and Java — a Python, Go, or C++ team gets zero proof generation, and the vendor page describes no roadmap for expansion, leaving those teams with no path forward except switching to a different verification approach entirely. Spec-driven development requires writing formal specifications before generating code; teams without prior exposure to this discipline spend non-trivial time learning to write specs that are precise enough for the proof system to use, at which point the productivity argument against traditional TDD weakens. Teams whose correctness requirements are satisfied by property-based testing tools — like QuickCheck for Haskell or Hypothesis for Python — have an established, language-native alternative that does not require adopting a new agent layer and may switch there rather than retrofit Forall into an incompatible stack.	The tool has no session memory and no command chaining: each prompt is independent. If you need to run 'find the large files, then compress them, then move them,' you issue three separate prompts and manually carry the output between steps — at which point you are doing the work the tool was supposed to save. The build requires macOS 26 and Xcode 26 alongside Apple Silicon. Teams with Intel Macs, Linux servers, or mixed-OS development environments cannot use it at all — this is the condition under which a team switches to a cloud-based CLI assistant like GitHub Copilot CLI or a self-hosted model with an OpenAI-compatible endpoint, which have no hardware gate. The vendor labels this a proof-of-concept explicitly. There are no open issues, no pull requests, and a commit history of 20 commits. Teams that need a maintained, production-grade tool with bug fixes and evolving model support are adopting technical debt the day they ship this to a shared workflow.

Bottom line

Forall is paid while LocalCode is free; only Forall exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Forall and LocalCode?

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

Is Forall better than LocalCode?

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.