The AI Makerspace MCP Server provides three tools via the Model Context Protocol (MCP):
Web Search (web_search): Search the web on any topic using the Tavily API by providing a query string.
Roll Dice (roll_dice): Roll dice using standard notation (e.g., 2d20k1 for 2 twenty-sided dice, keep highest 1), with an optional parameter for number of rolls.
Get Crypto Price (get_crypto_price): Retrieve current price and market data for a cryptocurrency (e.g., bitcoin, ethereum, dogecoin) from the CoinGecko API, with an optional comparison currency (default: usd).
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., "@AI Makerspace MCP Server search the web for the latest news on AI agents"
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.
This project is a demonstration of the MCP (Model Context Protocol) server, which utilizes the Tavily API for web search capabilities. The server is designed to run in a standard input/output (stdio) transport mode.
Related MCP server: mcp-toolkit
The MCP server is set up to handle web search queries using the Tavily API. It is built with the following key components:
TavilyClient: A client for interacting with the Tavily API to perform web searches.
Python 3.13 or higher
A valid Tavily API key
You'll need to install this on the Windows side of your OS.
This will require getting two CLI tool for Powershell, which you can do as follows:
winget install astral-sh.uv
winget install --id Git.Git -e --source winget
After you have those CLI tools, please open Cursor into Windows.
Then, you can clone the repository using the following command in your Cursor terminal:
git clone https://AI-Maker-Space/AIE8-MCP-Session.gitAfter that, you can follow from Step 2. below!
Clone the repository:
git clone <repository-url>
cd <repository-directory>Configure environment variables:
Create a .env file in the project root and add your API keys:
TAVILY_API_KEY=your_api_key_here
COINGECKO_API_KEY=your_coingecko_api_key_here # Optional - free tier works without key but has rate limitsNote: CoinGecko API can work without an API key, but using one provides higher rate limits (10-50 calls/minute with free tier).
🏗️ Add a new tool to your MCP Server 🏗️
Create a new tool in the server.py file, that's it!
To start the MCP server, you will need to add the following to your MCP Profile in Cursor:
NOTE: To get to your MCP config. you can use the Command Pallete (CMD/CTRL+SHIFT+P) and select "View: Open MCP Settings" and replace the contents with the JSON blob below.
{
"mcpServers": {
"mcp-server": {
"command" : "uv",
"args" : ["--directory", "/PATH/TO/REPOSITORY", "run", "server.py"]
}
}
}The server will start and listen for commands via standard input/output.
The server provides several tools:
web_search: Search the web for information about a given query using Tavily API
roll_dice: Roll dice with standard notation (e.g., "2d20k1" for 2 twenty-sided dice, keep highest 1)
get_crypto_price: Get current cryptocurrency price and market data from CoinGecko API (e.g., "bitcoin", "ethereum")
There are a few activities for this assignment!
Choose an API that you enjoy using - and build an MCP server for it!
Build a simple LangGraph application that interacts with your MCP Server.
You can find details here!
Get the current price and market data for a cryptocurrency.
Args: coin_id: The cryptocurrency ID (e.g., 'bitcoin', 'ethereum', 'dogecoin') vs_currency: The currency to compare against (default: 'usd')
Returns: Formatted string with current price and market data
| Name | Required | Description | Default |
|---|---|---|---|
| coin_id | Yes | ||
| vs_currency | No | usd |
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 tool returns a 'Formatted string with current price and market data,' which gives some output context, but lacks details on error handling, rate limits, authentication needs, or data freshness. For a tool with no annotations, this is a significant gap in transparency.
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 well-structured and appropriately sized, with a clear purpose statement followed by Args and Returns sections. Every sentence adds value, and it's front-loaded with the core functionality. Minor room for improvement in brevity, but it's efficient overall.
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 moderate complexity (2 parameters, no output schema, no annotations), the description is somewhat complete but has gaps. It covers purpose and parameters well but lacks behavioral details like error cases or rate limits. Without annotations or output schema, it should do more to guide the agent, making it adequate but not fully comprehensive.
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%, so the description must compensate. It effectively explains both parameters: 'coin_id' as 'The cryptocurrency ID (e.g., 'bitcoin', 'ethereum', 'dogecoin')' and 'vs_currency' as 'The currency to compare against (default: 'usd')'. This adds clear meaning beyond the bare schema, covering semantics and examples, though it could note parameter constraints like valid currency codes.
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 tool's purpose: 'Get the current price and market data for a cryptocurrency.' It specifies the verb ('Get') and resource ('current price and market data for a cryptocurrency'), making it easy to understand. However, it doesn't differentiate from sibling tools like 'roll_dice' or 'web_search', which is unnecessary here since they serve completely different domains, so a 4 is appropriate.
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 provides no guidance on when to use this tool versus alternatives. It doesn't mention any context-specific scenarios, prerequisites, or exclusions. While the sibling tools are unrelated, there's no explicit or implied usage advice, leaving the agent without operational context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Roll the dice with the given notation
| Name | Required | Description | Default |
|---|---|---|---|
| notation | Yes | ||
| num_rolls | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavioral traits. It only says 'Roll the dice,' which is a direct restatement of the tool name and adds no depth about random generation, validation, error handling, or return format. This is effectively a tautology with no added transparency.
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 with no waste, which is positive. However, it is under-specified: it front-loads little useful information and does not structure any context for the parameters. It cannot be considered 'appropriately sized' because it omits essential detail.
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 tool with two parameters, no output schema, and no annotations, the description is severely inadequate. It does not explain dice notation, the meaning of num_rolls, or any behaviors/limitations. Even the sibling context (web_search) offers no help in situating this tool, making the description insufficient for reliable tool invocation.
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%, so the description must compensate. 'Given notation' loosely aligns with the 'notation' parameter but fails to define its format or semantics. The 'num_rolls' parameter is entirely absent from the description, leaving its purpose unexplained. Overall, minimal added meaning beyond the schema titles.
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 states a clear verb ('Roll') and resource ('dice'), indicating the tool's primary action. However, it does not specify what 'notation' means (e.g., standard dice notation like '2d6'), which leaves some ambiguity. It is distinct from the sibling web_search, but not explicitly differentiated.
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 provided on when to use this tool vs alternatives. The sibling list includes web_search, but the description gives no context for when dice rolling is appropriate or any exclusions. Users are left to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search the web for information about the given query
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
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 only says 'search the web' without explaining what the tool returns, any limitations (e.g., freshness, pagination), or side effects. This lack of detail leaves the agent uncertain about the tool's behavior beyond the obvious.
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, ten words long, and front-loaded with the core action. There is no wasted text or redundancy. It is appropriately concise for a simple tool, and every word earns its place.
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?
The tool is low-complexity with one parameter and no output schema. The description fails to explain the return value, result format, or any constraints/edge cases. Since there is no output schema, the description should cover what the agent can expect after invocation, but it does not. This makes the description incomplete for an agent to use correctly.
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 has one parameter 'query' with a string type, and the description mentions 'the given query,' which is redundant. Since schema description coverage is 0%, the description should add meaning about the query format, examples, or constraints, but it does not. The parameter is self-explanatory, but the description adds no extra value.
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 tool's function: 'Search the web for information about the given query.' It uses a specific verb ('search') and resource ('web'), and the query is self-evident. While it doesn't explicitly distinguish from siblings, the only sibling is 'roll_dice,' which is clearly unrelated, so no differentiation is needed.
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 implies usage: use this tool when you need web information. However, it provides no explicit guidance on when to prefer this tool over alternatives, when not to use it, or any prerequisites. There is no mention of exclusions or comparison with the sibling tool, so it remains at an implied level.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v0.1.0get_crypto_priceroll_diceweb_searchScored across 3 tools
Each tool has a clearly distinct purpose: get_crypto_price retrieves cryptocurrency market data, roll_dice performs a random dice roll, and web_search conducts web queries. There is no overlap in functionality, making tool selection straightforward for an agent.
The naming is mixed: get_crypto_price and web_search follow a verb_noun pattern, but roll_dice uses a verb-only format. While all names are readable, the inconsistency in structure (two with nouns, one without) reduces predictability across the set.
With only 3 tools, the server feels thin for its implied scope as an 'AI Makerspace' server, which suggests a broader utility or creative toolkit. The tools cover unrelated domains (crypto, dice, web search), making the set appear incomplete or poorly scoped rather than focused.
The server lacks a coherent domain, making completeness hard to assess, but there are significant gaps: for crypto, there's no historical data or portfolio tools; for dice, no customization options; for web search, no filtering or advanced parameters. The tools are isolated without supporting operations, leading to potential agent dead ends.
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