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neoneyeneoneye/PlanExe/skills/planexe-mcp/SKILL.md

planexe-mcp

Skill402 starsChanged 3 months agoMITView on GitHub

OpenClaw skill for connecting to PlanExe via Model Context Protocol. Supports three deployment scenarios: cloud-hosted service, remote Docker, and local Docker.

  • Reads credentials

We split this skill into the rules it gives an agent

20 rules. About 0 are common, 7 are distinctive, and 13 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈7

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 13

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Add to your OpenClaw config or environment:

    line 28
  2. Very specific:

    Run PlanExe in Docker on a separate machine and connect remotely.

    line 46
  3. Very specific:

    Run PlanExe in Docker on the same machine as OpenClaw.

    line 67
  4. Distinctive:

    Create a new planning task.

    line 132
  5. Distinctive:

    Stop a running planning task.

    line 189
  6. Very specific:

    Call example_prompts to understand available planning scenarios

    line 310
  7. Very specific:

    Call plan_create with your prompt and parameters → receives task_id

    line 314
  8. Very specific:

    If failed, optionally call plan_retry to requeue with a stronger model

    line 316
  9. Very specific:

    Call plan_file_info with completed task_id to get download link

    line 317
  10. Very specific:

    If you lose a task_id, call plan_list with your user_api_key to recover it

    line 319
  11. Very specific:

    Verify PLANEXE_MCP_URL is correct

    line 333
  12. Distinctive:

    Check network connectivity between OpenClaw and the service

    line 335
  13. Very specific:

    Verify PLANEXE_API_KEY is valid

    line 338
  14. Distinctive:

    Check for typos or expired credentials

    line 339
  15. Distinctive:

    Check if the service is overloaded

    line 344
  16. Distinctive:

    Consider increasing the request timeout in your OpenClaw config

    line 345
  17. Very specific:

    Verify Docker is installed: docker --version

    line 348
  18. Very specific:

    Check container logs: docker logs <container-id>

    line 349
  19. Very specific:

    Ensure port 8001 is not in use: lsof -i :8001 (macOS/Linux)

    line 350
  20. Very specific:

    Check the PlanExe documentation

    line 355

≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

PlanExe MCP Skill

Access PlanExe's powerful planning capabilities directly from OpenClaw via the Model Context Protocol (MCP).

Overview

The planexe-mcp skill provides a unified interface to interact with PlanExe across three deployment scenarios:

  • Cloud: mcp.planexe.org (Stripe credits at home.planexe.org)
  • Remote Docker: Container on a separate machine
  • Local Docker: Container on the same machine as OpenClaw

Setup by Deployment Scenario

Scenario A: Cloud-Hosted Service

Connect to the hosted PlanExe MCP service.

Configuration:

Add to your OpenClaw config or environment:

PLANEXE_MCP_URL=https://mcp.planexe.org
PLANEXE_API_KEY=your_api_key_from_planexe_account

How to Get Your API Key:

  1. Visit home.planexe.org
  2. Purchase credits via Stripe
  3. Generate an API key in your account dashboard
  4. Copy the key to your OpenClaw configuration

Scenario B: Remote Docker

Run PlanExe in Docker on a separate machine and connect remotely.

On the Remote Machine:

docker run -p 8001:8001 planexe/planexe:latest

Configuration in OpenClaw:

PLANEXE_MCP_URL=http://<remote-ip>:8001
PLANEXE_API_KEY=your_api_key

Replace <remote-ip> with your remote machine's IP address or hostname.


Scenario C: Local Docker

Run PlanExe in Docker on the same machine as OpenClaw.

Setup:

docker run -p 8001:8001 planexe/planexe:latest

Configuration in OpenClaw:

PLANEXE_MCP_URL=http://127.0.0.1:8001
PLANEXE_API_KEY=your_api_key

Invoking PlanExe Tools

The PlanExe MCP exposes nine core tools via the /mcp endpoint:

Tool 1: example_plans

Preview curated example plans with download links for reports and zip bundles.

No parameters required:

{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "example_plans",
    "arguments": {}
  }
}

Returns: List of example plans with title, report_url, and zip_url.


Tool 2: example_prompts

Get example prompts to understand what PlanExe can do.

No parameters required:

{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "example_prompts",
    "arguments": {}
  }
}

Returns: List of example prompts for planning tasks.


Tool 3: plan_create

Create a new planning task. This is the main entry point for generating plans.

Parameters:

{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "plan_create",
    "arguments": {
      "prompt": "Create a project launch plan for Q2 2026",
      "model_profile": "premium",
      "start_date": "2026-04-01T20:55:00+02:00",
      "user_api_key": "your_optional_api_key"
    }
  }
}

Parameter Guide:

  • prompt (required): Your planning request in natural language. Write as flowing prose (not structured markdown), typically 300-800 words.
  • model_profile (optional): One of "baseline", "premium", "frontier", or "custom". Defaults to "baseline".
  • start_date (optional): Plan start date in ISO 8601 format with timezone offset (e.g. "2026-04-01T20:55:00+02:00"). When omitted, the plan starts now.
  • user_api_key (optional): Your PlanExe API key (if not set in environment)

Returns: task_id for polling status and retrieving results.


Tool 4: plan_status

Poll the status of a running planning task.

Parameters:

{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "plan_status",
    "arguments": {
      "task_id": "task_abc123def456"
    }
  }
}

Usage: Planning tasks typically take 10-20 minutes (baseline profile). Poll every 5+ minutes to check progress.

Returns: Current status (pending, processing, completed, failed), and progress percentage.


Tool 5: plan_stop

Stop a running planning task.

Parameters:

{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "plan_stop",
    "arguments": {
      "task_id": "task_abc123def456"
    }
  }
}

Returns: Confirmation that the task has been stopped.


Tool 6: model_profiles

Return available model profiles and their guidance before calling plan_create.

No required parameters:

{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "model_profiles",
    "arguments": {}
  }
}

Returns: Available model profiles (baseline, premium, frontier, custom) with descriptions and currently loaded models.


Tool 7: plan_file_info

Retrieve download information for completed plan artifacts.

Parameters:

{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "plan_file_info",
    "arguments": {
      "task_id": "task_abc123def456",
      "artifact": "report"
    }
  }
}

Artifact Options:

  • "report": Interactive HTML report (~700KB, self-contained — open in a browser)
  • "zip": Pipeline output bundle (md, json, csv intermediary files)

Returns: download_url for accessing the artifact.


Tool 8: plan_list

List recent tasks for an authenticated user. Useful for recovering a lost task_id.

Parameters:

{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "plan_list",
    "arguments": {
      "user_api_key": "pex_your_key_here",
      "limit": 10
    }
  }
}

Returns: List of recent tasks with task_id, state, progress_percentage, created_at, and prompt_excerpt.


Tool 9: plan_retry

Retry a failed task with an optional upgraded model profile.

Parameters:

{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "plan_retry",
    "arguments": {
      "task_id": "task_abc123def456",
      "model_profile": "premium"
    }
  }
}

Returns: Confirmation that the task was requeued to pending state.


Typical Workflow

  1. Optionally call example_plans to preview what PlanExe output looks like
  2. Call example_prompts to understand available planning scenarios
  3. Optionally call model_profiles to choose an appropriate model_profile
  4. Formulate your planning prompt
  5. Get user approval for the request
  6. Call plan_create with your prompt and parameters → receives task_id
  7. Poll plan_status every 5+ minutes until status is completed or failed
  8. If failed, optionally call plan_retry to requeue with a stronger model
  9. Call plan_file_info with completed task_id to get download link
  10. Download and use the generated plan
  11. If you lose a task_id, call plan_list with your user_api_key to recover it

Refer to the PlanExe API documentation for extended examples and advanced use cases.

Configuration Reference

VariableExampleDescription
PLANEXE_MCP_URLhttps://mcp.planexe.orgMCP endpoint URL
PLANEXE_API_KEYpk_live_abc123...API authentication key

Troubleshooting

Connection Refused

  • Verify PLANEXE_MCP_URL is correct
  • For Docker: Ensure the container is running (docker ps)
  • Check network connectivity between OpenClaw and the service

Authentication Failed

  • Verify PLANEXE_API_KEY is valid
  • Check for typos or expired credentials
  • For cloud: Log in to home.planexe.org to verify account status

Timeout Errors

  • For Docker deployments, allow time for container initialization
  • Check if the service is overloaded
  • Consider increasing the request timeout in your OpenClaw config

Docker Issues (Local/Remote)

  • Verify Docker is installed: docker --version
  • Check container logs: docker logs <container-id>
  • Ensure port 8001 is not in use: lsof -i :8001 (macOS/Linux)

Support

For issues or questions:

License

This skill is part of PlanExe and is available under the same license as the PlanExe project.

Download now (ZIP)

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