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abckiran

MCP Server Deepdive

by abckiran
OverviewSchemaRelated ServersScoreDiscussions
Python

MCP Server Deepdive Deployment

A Model Context Protocol (MCP) server implementation for deepdive deployment scenarios.

Installation

Using uvx (Recommended)

Install and run directly from GitHub:

uvx --from git+https://github.com/abckiran/mcpServerexample.git mcp-server

Local Development

  1. Clone the repository:

git clone https://github.com/abckiran/mcpServerexample.git
cd mcpServerexample

  1. Install dependencies:

uv sync

  1. Run the server:

uv run mcp-server

Related MCP server: Arithmetic MCP Server

MCP Configuration

Add this configuration to your MCP client (e.g., Cursor's mcp.json):

{
  "mcpServers": {
    "airbnb": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/abckiran/mcpServerexample.git",
        "mcp-server"
      ]
    }
  }
}

Features

  • Mathematical Operations: Basic arithmetic functions

  • Extensible Architecture: Easy to add new tools and functions

  • GitHub Integration: Direct deployment from repository

Usage Examples

The server provides various tools including:

  • Mathematical calculations

  • Custom functions for specific use cases

Project Structure

├── main.py                 # Main entry point
├── pyproject.toml         # Project configuration
├── src/
│   └── mcpserver/
│       ├── __init__.py
│       ├── __main__.py
│       └── deployment.py
└── README.md

Requirements

  • Python 3.12+

  • uv package manager

License

This project is open source and available under the MIT License.

Available Tools

1 tool
addC

Add two numbers

ParametersJSON Schema
NameRequiredDescriptionDefault
aYes
bYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

C2.8/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. 'Add two numbers' implies a simple computation but doesn't disclose behavioral traits like error handling, performance limits, or output format. It's minimal and lacks necessary context for a mutation operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with a single sentence that directly states the tool's function. It's front-loaded and wastes no words, making it efficient for quick understanding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (simple addition), 2 parameters, and the presence of an output schema (which handles return values), the description is minimally adequate. However, it lacks details on error cases or behavioral context, making it incomplete for robust use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description 'Add two numbers' adds no meaning beyond what the input schema provides. It doesn't explain what 'a' and 'b' represent, their constraints, or usage examples, failing to compensate for the low coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Add two numbers' clearly states the verb ('Add') and resource ('two numbers'), making the purpose immediately understandable. However, with no sibling tools to distinguish from, it lacks explicit differentiation, preventing a perfect score of 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives, prerequisites, or contextual constraints. With no sibling tools mentioned, there's no explicit comparison, but it also lacks any usage context or exclusions.

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. Dates show when Glama detected each change.

  1. 1 tool update
    • First observedadd
Install Server
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TDQS

B3/5.0
Disambiguation5/5

With only one tool, there is no possibility of confusion or overlap between tools; the purpose is singular and clear.

Naming Consistency5/5

A single tool inherently has no inconsistency in naming patterns; the tool name 'add' is straightforward and follows a simple verb convention.

Tool Count2/5

One tool is too few for a server named 'Deepdive', which suggests a broader scope; this minimal set feels thin and underdeveloped for the implied purpose.

Completeness2/5

The tool 'add' covers a basic arithmetic operation, but for a server with a name implying depth or comprehensive functionality, there are significant gaps in coverage, such as other mathematical operations or more complex features.

Maintenance

ActivityInactive
ResponsivenessSyncing

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Connectors

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