Skip to main content

OmniPlan MCP

An MCP (Model Context Protocol) server and CLI for reading and writing OmniPlan (.oplx) and Microsoft Project (.mpp) schedule files.

macOS only — AppleScript bridge required for .mpp and all write operations.

Installation

pip install omniplan-mcp

Or install from source in editable mode:

cd /Users/cygnus/work/github/omniplan-mcp
pip install -e .

Usage

CLI mode (human-friendly)

Read and display a schedule:

# Read a complete schedule
omniplan-mcp read schedule.oplx

# Show a high-level summary
omniplan-mcp summary schedule.oplx

# Search for tasks by name
omniplan-mcp search schedule.oplx "design"

# List all tasks (table or tree view)
omniplan-mcp tasks schedule.oplx
omniplan-mcp tasks schedule.oplx --tree

# List resources or dependencies
omniplan-mcp resources schedule.oplx
omniplan-mcp dependencies schedule.oplx

Modify a schedule (requires the document to be open in OmniPlan):

# Find a task's ID by name
omniplan-mcp lookup "Task Name"

# Mark a task as complete
omniplan-mcp set-done 258
omniplan-mcp set-done 258 --subtree

# Add/remove dependencies
omniplan-mcp add-dep 260 258
omniplan-mcp rm-dep 260 258

# Set duration (seconds, days, hours, or minutes)
omniplan-mcp set-duration 258 3d
omniplan-mcp set-duration 258 28800

# Add a new child task
omniplan-mcp add-task 258 "Subtask" 2d

# Rename, delete, clear constraints
omniplan-mcp rename 258 "New Name"
omniplan-mcp delete 258
omniplan-mcp clear-constraint 258

# Save the document
omniplan-mcp save

# JSON output (read commands)
omniplan-mcp read schedule.oplx --json
omniplan-mcp summary schedule.oplx --json

Get help:

omniplan-mcp --help
omniplan-mcp read --help

MCP server mode (for AI tools)

Start the MCP server in stdio mode:

omniplan-mcp serve

Configure your MCP host (e.g., Claude Code) to use it:

{
  "mcpServers": {
    "omniplan": {
      "command": "omniplan-mcp",
      "args": ["serve"]
    }
  }
}

Architecture

src/omniplan_mcp/
├── __init__.py      # Version (__version__ = "0.5.0")
├── __main__.py      # CLI entry point: delegates to cli.py
├── cli.py           # CLI subcommands (click)
├── server.py        # MCP server: tool definitions + output formatters
└── parser.py        # Two parsing paths + write operations (AppleScript bridge)
tests/
└── test_parser.py   # Unit tests with in-memory .oplx ZIPs

Dual-mode design

The package provides two interfaces from the same codebase:

  1. CLI mode (omniplan-mcp read ..., omniplan-mcp set-done ...) — human-friendly terminal output
  2. MCP server mode (omniplan-mcp serve) — JSON-RPC over stdio for AI tools

Both share the same parser (parser.py) and AppleScript bridge.

Key design decisions

  1. Dual parser architecture: .mpp files open OmniPlan and read via AppleScript's in-memory object model. .oplx files parse XML directly (no OmniPlan needed). Both return identical 6-tuples: (projects, resources, tasks, violations, assignments, dependencies).

  2. Two ID systems: XML (.oplx) uses string IDs like "t258". AppleScript uses sequential integers starting at 1. All write operations strip the t prefix automatically.

  3. Write operations work on the open OmniPlan document: Tools like add_dependency, set_task_duration, clear_constraint_date generate AppleScript that targets document 1 of application "OmniPlan". The document must be open.

  4. Read tools work from file (.oplx or .mpp): read, summary, search, tasks, resources, dependencies parse the file on disk.

  5. list_dependencies reads from the baseline scenario, not the editing scenario.

Omni Automation JavaScript vs JXA

evaluate_omniplan_script uses Omni Automation JavaScript (not JXA/AppleScript JS). See the full explanation in the MCP server documentation.

Percent-complete computation

.oplx files store completion as effort-done / effort ratio. Group tasks compute completion bottom-up from children. Task status is computed: 100% → "finished", else compare end date to today.

Development

# Install in editable mode
pip install -e .

# Run tests
python -m pytest tests/ -v

# Build distribution
python -m build

Testing

Tests use a hand-crafted .oplx ZIP in memory (no real files). Add new test functions in tests/test_parser.py with inline XML constants. Tests cover: parsing, resource filtering, tree building, string parent IDs, percent-complete from effort, outline_depth, task_status, and Actual.xml preference.

Metadata

Release files for omniplan-mcp 0.5.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for omniplan-mcp 0.5.0
File Size Uploaded Provenance
omniplan_mcp-0.5.0.tar.gz 42.6 kB With provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for omniplan-mcp 0.5.0
File Interpreter ABI Platform
omniplan_mcp-0.5.0-py3-none-any.whl Python 3 none any Details

Total release size: 78.7 kB

Release files / omniplan_mcp-0.5.0.tar.gz

Download URL omniplan_mcp-0.5.0.tar.gz
Size 42.6 kB
Tags Source
SHA-256 checksum
How to use checksums
8f391835ca5fb2060027e38e10696aab3b160141728d2792aa9c7ddb137289fd
BLAKE2b-256 checksum
How to use checksums
47e1a0a21efe09bac6885f50c6751735b9bc23751c69ef6b9cc3002eada0d5a3
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.12

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Jun 15, 2026.

Transparency log

Release files / omniplan_mcp-0.5.0-py3-none-any.whl

Download URL omniplan_mcp-0.5.0-py3-none-any.whl
Size 36.1 kB
Tags Python 3
SHA-256 checksum
How to use checksums
bcfee17c71353102422a32aac185e5f57562334b021467b5d492f1c136298633
BLAKE2b-256 checksum
How to use checksums
c244a977bbfb26361dc676bf9235a1598da424b6cc0c14b2f34b4fea85afbe5b
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.12

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Jun 15, 2026.

Transparency log

Security for omniplan-mcp 0.5.0

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

Full provenance

All 2 files in this release have been uploaded with provenance metadata.

Select from 2 files

Attestation for omniplan_mcp-0.5.0.tar.gz

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Jun 15, 2026.

Transparency log

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page