io.github.jascal/orca-mcp-server

MCPcommunity
v0.1.30io.github.jascalUnknownUpdated 2mo agonpmGitHub

Go from natural language to verified finite state machines — topology bugs caught before code runs.

Orchestrated State Machine Language — a two-layer architecture for reliable LLM code generation. The core insight: LLMs generate flat transition tables reliably, but they struggle to guarantee topology correctness on their own. Orca separates program structure (state machine topology) from computation (action functions), then verifies the structure automatically before any code runs. Machines are…

Automatically indexed from public sources. Not yet verified by the developer on Forge.Claim this listing →
2mo agoLast update
Package
Authorio.github.jascal
LicenseUnknown
Version0.1.30
Sourcemcp-registry
Trust Status
B
60/100Good
Listed in Forge index+10/10
Publisher identity verified+0/20
Publisher: run `forge publish` from the package repo to claim ownership
Ed25519 publish signature+0/5
Included automatically when the publisher runs `forge publish`
Domain verification+0/5
Publisher: host /.well-known/forge.json on the package homepage with { "publisher": "<github-login>" }
npm Trusted Publishing (Sigstore)+0/5
Publish from GitHub Actions with --provenance so the attestation binds this package to this repo
npm maintainer match+0/5
Earned once your identity is verified above and that login is an npm maintainer of this package
CVE scan · clean+30/30
Static analysis · clean+20/20
Paste into Claude Code, Cursor, or any AI assistant to fix all gaps
StatusCommunity-indexed
PublisherUnverified
SignatureUnsigned
Domain
Provenance
Dependencies60 resolved+ · none vulnerable
Tool surface
Security scan✓ Cleanv0.1.30 · 2mo ago
EvalsNone
IndexedJun 13, 2026

Verification confirms publisher identity (repo ownership), not code safety. The security scan covers known CVEs and suspicious install scripts — it cannot prove the absence of malicious code.

About

Orchestrated State Machine Language — a two-layer architecture for reliable LLM code generation. The core insight: LLMs generate flat transition tables reliably, but they struggle to guarantee topology correctness on their own. Orca separates program structure (state machine topology) from computation (action functions), then verifies the structure automatically before any code runs. Machines are written in plain Markdown — a format LLMs can read and write natively. ctx.retrycount Context(ctx)…

Keywords
mcp