F
licenseNot graded
qualityD
maintenanceA basic educational MCP server that provides simple tools for mathematical calculations, text manipulation, and time retrieval. Designed for learning MCP implementation patterns and development purposes.
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Demo MCP Server
by SannketNikam
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Demo MCP Serverroll 3 dice for my board game"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Basic Setup
Install uv
Create a project folder named fastmcp-demo-server
Open the folder in VS Code
Open terminal
Execute the command: uv init
uv add fastmcp
Fastmcp version
Create a basic server
Test the server -uv run fastmcp dev main.py (MCP Inspector CMD)
Run the server -uv run fastmcp run main.py
Add the server to claude desktop - uv run fastmcp install claude-desktop main.py (For local server)
Use the same steps from above to create a Remote MCP Server and follow the below steps and for Local MCP Server just follow till the upper step.
Test the server using MCP Inspector | This opens in browser just like FastAPI's page
Create a GitHub repo
git init
git add
git commit -m "Initial commit: Simple MCP Server"
git remote add origin https://github.com/YourUsername/simple-mcp-server.git
git push -u origin main
Create an account on FastMCP Cloud
Deploy on FastMCP Cloud
import random
from fastmcp import FastMCP
# Create a FastMCP server instance
mcp = FastMCP(name="Demo Server")
@mcp.tool
def roll_dice(n_dice: int=1) -> list[int]:
"""Roll n_dice 6 sided dice and return the results."""
return [random.randint(1,6) for _ in range(n_dice)]
@mcp.toll
def add_numbers(a: float, b: float) -> float:
"""Add two numbers together."""
return a + b
if __name___ == "__main__":
mcp.run()Available Tools
3 toolsadd_expenseC
Add a new expense entry to the database.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| date | Yes | ||
| amount | Yes | ||
| category | Yes | ||
| subcategory | No | ||
| note | No |
TDQS
C2.7/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description only states the action but lacks details on idempotency, side effects, or data validation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, concise but lacks structure or front-loading of key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With five parameters, no output schema, and no annotations, the description is incomplete; it does not explain return values or handle edge cases.
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 coverage is 0%. The description adds no meaning to any of the five parameters, not even the required date, amount, or category.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 ('expense entry'), clearly distinguishing it from siblings like delete_expense and list_expenses.
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?
No guidance on when to use this tool versus alternatives. Siblings exist but no differentiation is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_expensesC
List expense entries within an inclusive date range.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| start_date | Yes | ||
| end_date | Yes |
TDQS
C2.9/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility for behavioral disclosure. It only states basic read-only behavior without mentioning pagination, limits, ordering, or potential side effects, leaving significant gaps.
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 a single concise sentence that front-loads key information. It is appropriately brief, though it could benefit from additional context without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity with 2 required parameters and no output schema, the description should cover return format or data structure. It fails to mention what the response contains, leaving the agent uncertain about the output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, so the description must compensate. It clarifies the date range is inclusive but does not specify date format, timezone handling, or parameter constraints beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and the resource 'expense entries', and specifies the scope as 'within an inclusive date range'. This explicitly differentiates it from sibling tools like add_expense, delete_expense, update_expense, and summarize.
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, no exclusion criteria, and no prerequisites. It merely states the function without context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
summarizeB
Summarize expenses by category within an inclusive date range.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| start_date | Yes | ||
| end_date | Yes | ||
| category | No |
TDQS
B3.2/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It mentions 'inclusive date range' but does not state that the tool is read-only, lacks details on return format, and omits any side effects or permissions.
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?
One sentence with no wasted words. It is front-loaded with the key action but could benefit from additional param details without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and 0% schema coverage, the description is insufficient. It fails to provide parameter details, return value expectations, or usage context beyond the basic purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%. The description mentions 'category' as a grouping field but does not clarify its optionality or the expected format for date parameters. It adds minimal value beyond the schema structure.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool summarizes expenses by category within a date range. The verb 'summarize' and resource 'expenses' are specific, and the grouping by 'category' distinguishes it from sibling tools that perform CRUD operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance. The usage is implied by the tool name and siblings, but no alternatives or exclusions are mentioned.
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.
3 tool updates
- First observed
add_expense - First observed
list_expenses - First observed
summarize
TDQS
B3.3/5.0
Scored across 3 tools
Disambiguation5/5
Each tool has a clearly distinct purpose: add_expense creates new entries, list_expenses retrieves entries with filtering, and summarize provides aggregated analysis. There is no overlap in functionality, making tool selection straightforward for an agent.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern (add_expense, list_expenses, summarize), with 'summarize' being a verb-only form that still fits the action-oriented naming style. The naming is predictable and readable throughout.
Tool Count5/5
With 3 tools, this server is well-scoped for expense management, covering core operations: creation, retrieval, and summarization. Each tool earns its place without feeling thin or excessive for the domain.
Completeness3/5
The tools cover basic expense tracking (create, list, summarize), but there are notable gaps in lifecycle coverage, such as updating or deleting expenses. This could limit agents in handling modifications or corrections, though core workflows are supported.
Maintenance
ActivityInactive
ResponsivenessNo issues
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