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KrishnaPapana

MCP Server Deepdive

MCP Server Deepdive Deployment

Installation Steps

1. Clone the Repository

git clone https://github.com/KrishnaPapana/mcpserverexample.git
cd mcpserverexample

2. Set Up Python Environment

  • Ensure you have Python 3.12 or higher installed.

  • (Recommended) Create and activate a virtual environment:

python -m venv .venv
.venv\Scripts\activate

3. Install Dependencies

pip install -U pip
pip install .

4. Run the MCP Server

mcp-server

This will start the MCP server using the entry point defined in pyproject.toml.


For more details, see the project documentation or source code.


Related MCP server: MCP Builder

MCP Client Configuration

You can add the following to your MCP client config file to automatically install and run the server:

{
    "mcpserver":{
        "server":{
            "command": "uv",
            "args":[
                "--from",
                "git+https://github.com/KrishnaPapana/mcpserverexample.git",
                "mcp-server"
            ]
        }
    }
}

Available Tools

1 tool
add_two_numbersC
Adds two numbers together.
Args:
a -- the first number
b -- the second number
Returns:
The sum of a and b 
ParametersJSON Schema
NameRequiredDescriptionDefault
aYes
bYes

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the return value ('The sum of a and b'), which adds some context, but fails to address important aspects like error handling, input validation, or performance characteristics. For a tool with zero annotation coverage, this is insufficient.

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

Conciseness4/5

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

The description is appropriately sized and well-structured with clear sections for purpose, arguments, and returns. It uses minimal sentences that each serve a distinct purpose, though the formatting could be slightly more polished.

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 arithmetic) and lack of annotations or output schema, the description is moderately complete. It covers the basic purpose and parameters but misses details like error cases or input constraints, which would be helpful for an AI agent to use it correctly.

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

Parameters3/5

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

The description explicitly defines parameters 'a' and 'b' as 'the first number' and 'the second number', adding meaning beyond the input schema (which has 0% description coverage and only specifies types as strings). However, it does not clarify that the parameters are strings in the schema or explain how numeric addition works with string inputs, leaving some ambiguity.

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 clearly states the tool's purpose with a specific verb ('Adds') and resource ('two numbers together'), making it immediately understandable. However, since there are no sibling tools, it cannot demonstrate differentiation from alternatives, which prevents 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 or in what context it should be applied. It simply states what the tool does without any usage instructions, prerequisites, 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_two_numbers

TDQS

B3/5.0
Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap with other tools. The tool 'add_two_numbers' has a single, clear purpose that cannot be confused with any other functionality.

Naming Consistency5/5

A single tool inherently exhibits perfect naming consistency, as there are no other tools to compare it against. The name 'add_two_numbers' follows a clear verb_noun pattern, which would be consistent if more tools existed.

Tool Count2/5

A single tool is generally too few for most server purposes, as it limits functionality and suggests an incomplete or trivial implementation. For a server named 'Deepdive', which implies comprehensive exploration, one tool is a significant mismatch in scope.

Completeness1/5

The server is severely incomplete, as it only provides a basic arithmetic operation with no coverage of any broader domain. There is no indication of what 'Deepdive' entails, but a single addition tool fails to support any meaningful workflows or use cases.

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

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