MCP.Market

Orca MCP Server

by jascal·io.github.jascal/orca-mcp-server·v0.1.30·14 stars

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

B72/100grade B
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Safety scan
B72/100

full report

Adoption
Growing

14 stars44 downloads/wk

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Orca MCP Server tools

No tool declarations could be read from the package source. They show once the server is installed.

Public scan report

scanner v0.1.9 · 2026-09-27 · same rubric, same numbers if you re-run it

no findings
  • Code scan3 source files scanned25/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitystatic API keys via environment variables6/15
  • Maintenancelast push 116 days ago8/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10
Overall 72/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How Orca MCP Server compares

Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
72/100
higher than 38% of 48,255 servers
GitHub stars
14
more than 90% of 28,688 servers
Downloads a week
44
more than 36% of 12,191 servers with a package

Install Orca MCP Server in Claude Code, Cursor or VS Code

Runs npx -y @orcalang/orca-mcp-server on your machine. Read the scan report first; the gateway never runs local packages.

claude mcp add orca-mcp-server -- npx -y @orcalang/orca-mcp-server
Add to Cursor

What the publisher says

From the Orca MCP Server repository's README, as published. We do not edit it. Read it on GitHub

Orca

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.

What it looks like

# machine PaymentProcessor

## context

| Field       | Type    | Default |
|-------------|---------|---------|
| order_id    | string  |         |
| amount      | decimal |         |
| retry_count | int     | 0       |

## events

- submit_payment
- payment_authorized
- payment_declined
- retry_requested
- settlement_confirmed

## state idle [initial]
> Waiting for a payment submission

## state authorizing
> Waiting for payment gateway response
- on_entry: send_authorization_request

## state declined
> Payment was declined

## state settled [final]
> Payment fully settled

## transitions

| Source      | Event                | Guard      | Target      | Action           |
|-------------|----------------------|------------|-------------|------------------|
| idle        | submit_payment       |            | authorizing |                  |
| authorizing | payment_authorized   |            | settled     |                  |
| authorizing | payment_declined     |            | declined    |                  |
| declined    | retry_requested      | can_retry  | authorizing | increment_retry  |
| declined    | retry_requested      | !can_retry | settled     | record_failure   |

## gu

The verifier checks this before anything runs: reachability, deadlocks, guard determinism, orphan declarations, and effect consistency.

Features

Language

  • States with [initial] / [final] markers, descriptions, onentry / onexit actions
  • Transitions as a flat table — the format LLMs generate most reliably
  • Guard expressions: comparisons, boolean logic, null checks
  • Hierarchical (nested) states
  • Parallel regions with all-final / any-final / custom sync strategies
  • Timeouts: timeout: 30s -> state_name
  • Ignored events: ignore: EVENT_NAME
  • Machine invocation: one machine calling another, with input mapping and completion events
  • Multi-machine files: multiple machines in one .orca.md separated by ---
  • ## effects section: named I/O schemas for external side effects
  • Decision tables: co-located conditional logic without guard explosion — verified for completeness, consistency, and cross-machine reachability

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

Orca MCP Server: common questions

Is Orca MCP Server safe?
Mostly: it is graded B (72/100). Read the Orca MCP Server safety report
How do I install Orca MCP Server?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does Orca MCP Server need an API key?
Yes. The registry entry asks for ANTHROPIC_API_KEY.
Is Orca MCP Server maintained?
The last commit was 154 days ago (2026-06-03). The latest release is v0.1.30.
How does Orca MCP Server compare with other MCP servers?
safety score 72/100 (higher than 38% of 48,255 servers); github stars 14 (more than 90% of 28,688 servers); downloads a week 44 (more than 36% of 12,191 servers with a package). Full comparison.