@@ -2,9 +2,19 @@
A Model Context Protocol (MCP) server that provides planning tools for LLMs to thoroughly plan their actions before getting started and pivot during execution when needed.
-## Features
+## What This Gives Your AI Assistant
-The server provides four core tools that constitute a comprehensive planning workflow:
+This MCP server enables your AI assistant to:
+
+- **Set clear goals** for complex tasks and keep them visible throughout the work
+- **Break down work** into manageable, trackable tasks with progress indicators
+- **Stay organized** with persistent task lists that survive across conversations
+- **Track progress** with visual status indicators (☐ pending, ⟳ in progress, ☑ completed, ☒ failed)
+- **Adapt plans** by adding tasks, updating status, and pivoting when needed
+
+## Core Capabilities
+
+The server provides four essential planning tools:
- **`update_goal`**: Set or update the overarching goal for your planning session
- **`add_tasks`**: Add one or more tasks to work on. Break tasks down into the smallest units of work possible and track progress.
@@ -76,22 +86,13 @@ For web-based integrations:
- `--generate-config`: Generate example configuration
- `--version, -v`: Show version
-## Tool Examples
-
-### Setting a Goal
+## How Your AI Assistant Uses This
-```json
-{
- "name": "update_goal",
- "arguments": {
- "goal": "Create a comprehensive MCP server for task planning and management"
- }
-}
-```
+### Setting Goals
-Response: `Goal "Create a comprehensive MCP server for task planning and management" saved! You probably want to add one or more tasks now.`
+Your AI assistant can establish clear objectives that stay visible throughout the planning session, helping maintain focus on the overall purpose.
-### Adding Tasks
+### Planning Tasks
When you first add tasks to an empty planning session, the tool provides guidance and shows your complete plan:
@@ -105,16 +106,10 @@ When adding tasks to an existing planning session, the tool keeps things brief:
- Shows your updated task list (same format as `get_tasks`)
- No repetitive instructions - just your updated plan
-### Getting Task Status
+### Tracking Progress
-```json
-{
- "name": "get_tasks",
- "arguments": {}
-}
-```
+Your AI assistant gets a clear view of all tasks with visual status indicators:
-Response:
```
**Goal:** Create a comprehensive MCP server for task planning and management
@@ -126,29 +121,9 @@ Legend: ☐ pending ⟳ in progress ☑ completed
☐ Build MCP server integration [i9j0k1l2]
```
-### Updating Task Status
-
-```json
-{
- "name": "update_task_status",
- "arguments": {
- "task_id": "a1b2c3d4",
- "status": "completed"
- }
-}
-```
-
-Response:
-```
-**Goal:** Create a comprehensive MCP server for task planning and management
+### Updating Status
-Legend: ☐ pending ⟳ in progress ☑ completed
-☑ Set up project structure [a1b2c3d4]
- Create Go module, directories, and basic files
-⟳ Implement core planning logic [e5f6g7h8]
- Create Goal and Task data structures with deterministic IDs
-☐ Build MCP server integration [i9j0k1l2]
-```
+As work progresses, your AI assistant can update task statuses and immediately see the updated plan with all changes reflected.
## Task Status Indicators