Orca MCP Server

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

What does this entry provide?

Orca MCP Server is an MCP server entry in ChatHome Skills, sourced from Official MCP Registry and scored 67/100. As a Model Context Protocol server, it exposes tools that MCP-compatible LLM clients such as Claude, Cursor, and Copilot can call directly, extending an agent's reach beyond its built-in capabilities. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding Orca MCP Server to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.

Snapshot facts

Source: Official MCP Registry
Quality: 67/100
Install method: npm
Repo: jascal/orca-lang
Repo updated: Jun 3, 2026

Install command

npx -y @orcalang/orca-mcp-server@0.1.30

Install method: npm

Review the upstream source before running this command.

GitHub project

Quality

Repo stars

Repo updated

Jun 3, 2026

How is this score calculated?

Weighted across six dimensions, scored 0-100.
Provenance (25): listed in an official or curated registry.
Installability (25): a runnable install command beats a declared transport, which beats a source checkout.
Maintenance (20): recency of the last push; archived entries score zero here.
Adoption (20): repository stars on a log curve.

MCP manifest

{
  "_meta": {
    "io.modelcontextprotocol.registry/official": {
      "status": "active",
      "isLatest": true,
      "updatedAt": "2026-06-03T02:36:27.218364Z",
      "publishedAt": "2026-06-03T02:36:27.218364Z",
      "statusChangedAt": "2026-06-03T02:36:27.218364Z"
    }
  },
  "server": {
    "name": "io.github.jascal/orca-mcp-server",
    "title": "Orca MCP Server",
    "$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
    "version": "0.1.30",
    "packages": [
      {
        "version": "0.1.30",
        "transport": {
          "type": "stdio"
        },
        "identifier": "@orcalang/orca-mcp-server",
        "runtimeHint": "npx",
        "registryType": "npm",
        "environmentVariables": [
          {
            "name": "ANTHROPIC_API_KEY",
            "isSecret": true,
            "description": "Anthropic API key for LLM-powered tools (generate_machine, generate_multi_machine, refine_machine, generate_actions with use_llm). Not required for parse_machine, verify_machine, compile_machine, or server_status."
          },
          {
            "name": "ORCA_PROVIDER",
            "default": "anthropic",
            "description": "LLM provider to use: anthropic (default), openai, grok, or ollama."
          },
          {
            "name": "ORCA_MODEL",
            "description": "Model name to use for LLM tools. Defaults to claude-sonnet-4-6 for Anthropic."
          }
        ]
      }
    ],
    "repository": {
      "id": "1189955224",
      "url": "https://github.com/jascal/orca-lang",
      "source": "github",
      "subfolder": "packages/mcp-server"
    },
    "description": "Go from natural language to verified finite state machines — topology bugs caught before code runs."
  }
}

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