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Road Poneglyph

by xfloukiex-lab

Runs a local, model-driven pre-mortem that identifies unstated assumptions, technical risks, and execution gaps in plans.

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Install Road Poneglyph

Pick your client, then add it in one click or paste the config.

STDIOPython
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "xfloukiex-lab-road-poneglyph": {
      "command": "uvx",
      "args": [
        "road-poneglyph-mcp"
      ]
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

We couldn’t confirm it starts correctly

We ran the install command but it didn't respond within our test window — this can mean a slow first-time install rather than a real problem.

uvx road-poneglyph-mcp

No response to initialize.

This is an experimental automated check and can have false negatives — missing environment variables, a slow cold install, etc. It doesn’t necessarily mean something’s wrong. Last checked 1mo ago.

Overview

The xfloukiex-lab/road-poneglyph MCP server reviews plans for unstated assumptions, omitted technical risks, and execution blind spots. Its single tool returns a structured pre-mortem prompt organized into assumptions, technical and architectural risks, and operational gaps. The server does not call a language model or make network requests; it supplies an analysis prompt for the model already being used through the MCP client. Reach for the xfloukiex-lab/road-poneglyph MCP server when you want a local plan review without API credentials.

Use cases

  • Review a software delivery plan before implementation
  • Surface unstated assumptions in an architecture proposal
  • Identify technical risks omitted from a project plan
  • Check operational blind spots before shipping

Key features

  • Structured pre-mortem analysis
  • Unstated assumption detection
  • Technical and architectural risk review
  • Operational blind-spot detection
  • Local prompt generation without network calls
  • Configurable project type

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 1d ago

Recent health check succeeded.

17/18 checks healthy over the last 79d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 9d ago via OSV.dev · road-poneglyph-mcp (PyPI)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars2Stargazers on the source repository.
Last commit4mo agoMost recent push to the default branch.
Install checkInconclusiveDidn't respond in our test window — often a slow first install.
Directory activity5 viewsConfig copies, upvotes, and views on AllMCPs.

How Road Poneglyph works

What xfloukiex-lab/road-poneglyph MCP server does

The xfloukiex-lab/road-poneglyph MCP server examines a written plan for important details that are absent rather than simply responding to the plan's stated content. It is intended for structured pre-mortems: reviews that surface what could undermine execution before work begins.

The returned analysis is divided into three areas:

  • The Void Century: assumptions the plan relies on without establishing them.
  • Hidden Reef: technical and architectural risks that the plan leaves out.
  • The Treacherous Seas: operational and execution blind spots that could affect delivery.

This makes the server suitable for reviewing software plans and other project plans where missing assumptions or unexamined risks could create problems during implementation.

How it works

The xfloukiex-lab/road-poneglyph MCP server exposes one MCP tool: read_poneglyph. It accepts a required current_plan string and an optional project_type string, which defaults to Software.

Rather than invoking a language model itself, the server generates a carefully structured analysis prompt. The MCP-compatible client passes that prompt to the model the user is already interacting with. As a result, the server requires no API key, makes no network calls, and does not send the plan to an external service itself.

The tool reference is:

text
read_poneglyph(current_plan: str, project_type: str = "Software")

The client and model therefore remain responsible for executing the review prompt and presenting the resulting critique.

Setup and configuration

The package requires Python 3.10 or newer. Install it from PyPI with:

Terminal
pip install road-poneglyph-mcp

Installation provides the road-poneglyph command. A Claude Desktop configuration can register it as a local stdio MCP server:

config.json
{
  "mcpServers": {
    "road-poneglyph": { "command": "road-poneglyph" }
  }
}
Terminal
claude mcp add road-poneglyph -- road-poneglyph

Restart the MCP client after registration so the tool becomes available. The README specifically identifies Claude Desktop, Claude Code, and Cursor as compatible clients; this listing includes the supported client names available in its client taxonomy.

Tools and capabilities

The xfloukiex-lab/road-poneglyph MCP server provides one focused capability rather than a collection of project-management operations:

  • Submit a plan for a structured pre-mortem.
  • Set the project type or use the Software default.
  • Identify unstated assumptions.
  • Surface omitted technical and architectural risks.
  • Highlight operational and execution gaps.

It does not provide a model, a hosted analysis endpoint, or a separate credential system. The analysis depends on the model connected through the MCP client.

Read the full README View source on GitHub

Reviews

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Frequently Asked Questions about Road Poneglyph

Use Python 3.10 or newer and run `pip install road-poneglyph-mcp`. The package installs the `road-poneglyph` command.

Yes. The README provides a Claude Desktop configuration that runs the local `road-poneglyph` command.

No. It does not call a language model itself, requires no credentials, and makes no network calls.

It provides `read_poneglyph(current_plan: str, project_type: str = "Software")`, which returns a structured pre-mortem analysis prompt.

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