todo list mcp server
š Personal To-Do List MCP Server
A minimalistic and functional Model Context Protocol (MCP) server that provides AI assistants with a robust local To-Do list manager. This server demonstrates how an AI can manage local state and interact with persistent data (CRUD operations) without requiring external APIs or complex databases.
š Live Demo & Media
Live Registry Listing: Glama MCP Server
Related MCP server: Todo MCP Server
šø Screenshots

⨠Key Features
š¤ Native AI Integration: Works seamlessly with Claude Desktop, Cursor, and Antigravity.
š ļø Complete CRUD Operations: Add, list, complete, and delete tasks.
š Real-time Summaries: Provides read-only resources summarizing pending vs. completed tasks.
š Private Local Storage: Stores data strictly on your local machine using JSON.
āļø Zero Configuration: Works entirely out of the box with modern Python packaging.
š ļø Tech Stack Table
Category | Technology | Purpose |
Protocol | Model Context Protocol (MCP) | AI-to-Tool communication standard |
Language | Python 3.10+ | Core logic and execution |
SDK |
| Official Anthropic SDK for Python |
Package Manager |
| Modern dependency management |
Database | Local JSON File | Persistent local state storage |
āļø How It Works
Tool Invocation: The AI client sends a JSON-RPC request to the MCP server (e.g.,
add_task).Execution: The Python server parses the local
todos.jsonfile.Modification: The server updates the JSON file with the new task and saves it.
Response: The server returns a success confirmation back to the AI client.
šļø Project Architecture
graph LR
A[AI Assistant] <-->|JSON-RPC via stdio| B[Todo MCP Server]
B -->|Read/Write| C[(todos.json)]
B --> D[Tools: add, list, delete, complete]
B --> E[Resources: todo://summary]š Project Structure
āāā docs/ # Learning outcomes and documentation
ā āāā inspector.png
ā āāā resend-experience.md
āāā src/
ā āāā todo_mcp/ # Core MCP server package
ā āāā __init__.py
ā āāā __main__.py # Execution entrypoint
ā āāā server.py # Tools and resources logic
āāā .gitignore
āāā pyproject.toml # Modern Python package configuration
āāā README.mdš» Local Setup & Installation
Prerequisites
Python 3.10 or higher
Node.js (for
npxif using the Inspector)
Installation
Clone the repository and install it locally using pip:
git clone https://github.com/Arslan-Codes097/todo-list-mcp-server.git
cd todo-list-mcp-server
pip install .Running Locally (Inspector)
To test the tools in the interactive MCP Inspector UI:
npx @modelcontextprotocol/inspector python -m todo_mcpConnecting to an AI Client (Zero-Install)
The easiest way to use this server is via uvx. It will automatically download and run the server without you needing to clone the repository manually.
Add the following to your client's config.json:
{
"mcpServers": {
"todo-mcp": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/Arslan-Codes097/todo-list-mcp-server.git",
"python",
"-m",
"todo_mcp"
]
}
}
}š¤ Author & Credits
Arslan
GitHub: @Arslan-Codes097
Built as a hands-on exploration of the Model Context Protocol.
Available Tools
4 toolsadd_taskB
Add a new task to the todo list.
| Name | Required | Description | Default |
|---|---|---|---|
| task | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It states 'Add a new task' but does not disclose permissions, idempotency, duplicate handling, or effects on existing tasks; the output schema exists but is not described in the text. This is a mutation tool with minimal behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no filler, and the key verb/resource are front-loaded. It is appropriately brief for a simple tool, though it could include more context without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the trivial complexity and presence of an output schema, the description covers the basic purpose. However, with no annotations and no usage guidance, it leaves gaps around behavior and choice among sibling tools; it is minimally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no meaning beyond the schema's 'task' string titled 'Task'. It does not explain expected format, length, or whether the task string includes status/priority; the single parameter's semantics are only obvious from its name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Add') and resource ('task'), clearly indicating the operation on the todo list. This differentiates it from siblings (complete_task, delete_task, list_tasks) by naming the create action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to use this tool over alternatives; siblings are listed but no exclusions or context are mentioned. The description only states the action, leaving the agent to infer usage from the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
complete_taskA
Mark a task as completed using its ID (index).
| Name | Required | Description | Default |
|---|---|---|---|
| task_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It states the mutation ('Mark as completed') but does not disclose side effects, idempotency, error behavior on invalid IDs, or prerequisites. Minimal but not misleading, so a low-average score is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, tightly written sentence that immediately conveys purpose and key parameter usage. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with an output schema, the description covers the core action. It omits details like required existence of the task or error handling, but given the simplicity and clear sibling context, it is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description clarifies that 'task_id' is an ID and also an index, giving practical meaning beyond the integer type. Although schema coverage is 0%, the description compensates sufficiently for the single parameter, though it could add more on valid ranges or required existence.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Specific verb 'Mark' + resource 'task' + action 'completed' clearly states the tool's function. The parenthetical 'using its ID (index)' adds the key parameter context. It is easily distinguished from sibling tools like delete_task and add_task.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies that the tool requires an existing task ID, which establishes when to use it. However, it does not explicitly mention when not to use it or suggest alternatives, but the sibling names make the distinctions obvious.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delete_taskA
Delete a task from the list using its ID.
| Name | Required | Description | Default |
|---|---|---|---|
| task_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Delete') but does not disclose that this is a permanent, destructive operation or whether it requires any prerequisites or has irreversible consequences. The description is minimal and fails to add transparency beyond the action itself.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that immediately states the action and parameter use. There is no wasted wording, and it is front-loaded with the verb 'Delete'.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, obvious action), the description is reasonably complete. It explains what the tool does and how to specify the target. However, it omits any details about return values or potential error cases, though an output schema exists that might cover that. For a straightforward delete, it is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides only the parameter type (integer) with no description (0% coverage). The description compensates by stating 'using its ID', clarifying that task_id is the identifier of the task to be deleted. This adds meaningful context to the parameter, making it clear how to populate it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Delete a task') and the resource ('from the list'), using 'its ID' to specify the means. It is distinct from sibling tools like add_task, list_tasks, and complete_task, which perform different operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage is implied: you use this when you need to permanently remove a task. However, there is no explicit guidance on when to use it versus alternatives, and no mention of prerequisites or exclusions. It does not mislead, but it lacks explicit direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_tasksA
List all tasks in the todo list.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the behavioral transparency burden. It accurately implies a read-only listing of all tasks, but provides no additional behavioral context such as ordering, pagination, or performance implications. For a zero-parameter list tool this is acceptable, though not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that expresses exactly what the tool does with no wasted words. It is appropriately concise for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a very simple zero-parameter tool with an output schema available. The description fully covers its externally visible behavior: it lists all tasks. Given the tool's simplicity and the presence of an output schema, no further contextual detail is required.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters and schema description coverage is 100%. Since there are no parameters to explain, the description does not need to provide additional parameter semantics; the baseline of 4 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('list'), identifies the resource ('tasks'), and states the scope ('all tasks in the todo list'). It is clearly distinct from the mutating sibling tools complete_task, delete_task, and add_task.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes the use case clear: call this to view every task in the todo list. It does not explicitly mention when not to use it, but the distinction from mutating sibling tools is straightforward and unlikely to confuse an agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
4 tool updates
v0.1.0- First observed
add_task - First observed
complete_task - First observed
delete_task - First observed
list_tasks
TDQS
Scored across 4 tools
Each tool has a distinct purpose: add, list, complete, and delete tasks. There is no ambiguity or overlap between them.
All tools follow the consistent verb_noun pattern (add_task, list_tasks, complete_task, delete_task), making the naming predictable and clear.
With just 4 tools, the server is tightly scoped to the core operations of a todo list, and each tool is necessary and sufficient for basic task management.
The tools cover the full lifecycle of a todo item: create (add_task), read (list_tasks), update (complete_task), and delete (delete_task). No essential operations are missing for a simple todo list.
Maintenance
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An MCP server that used to create notes
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