How do I use Tavily Web Search MCP Server?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Tavily Web Search MCP Server find recent developments in quantum computing" 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.

Tavily Web Search MCP Server

by UpendraNath

Overview Schema Source Related Servers Discussions Admin

Python

Remote

AI Makerspace: MCP Session Repo for Session 13

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: Tavily Web Search MCP Server

Project Overview

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.

Prerequisites

Python 3.13 or higher
A valid Tavily API key

⚠️NOTE FOR WINDOWS:⚠️

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.git

After that, you can follow from Step 2. below!

Installation

Clone the repository:

git clone <repository-url>
cd <repository-directory>

Configure environment variables: Copy the .env.sample to .env and add your Tavily API key:
```
TAVILY_API_KEY=your_api_key_here
```
🏗️ Add a new tool to your MCP Server 🏗️

Create a new tool in the server.py file, that's it!

Running the MCP Server

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.

Usage

The server provides a web_search tool that can be used to search the web for information about a given query. This is achieved by calling the web_search function with the desired query string.

Activities:

There are a few activities for this assignment!

🏗️ Activity #1:

Choose an API that you enjoy using - and build an MCP server for it!

🏗️ Activity #2:

Build a simple LangGraph application that interacts with your MCP Server.

You can find details here!

Available Tools

4 tools

load_bookmark_dataB

Load bookmarks and history data from files

ParametersJSON Schema

Name	Required	Description	Default
`data_folder`	No		data

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

B3.1/5.0

Behavior2/5

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 tool loads data but doesn't cover critical aspects like whether this is a read-only operation, potential side effects, error handling, or performance implications, which are essential for safe use.

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 a single, efficient sentence that directly states the tool's function without unnecessary words. It's front-loaded and appropriately sized for its purpose, earning a perfect score for conciseness.

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 has an output schema (which handles return values) and only one parameter, the description is minimally adequate. However, with no annotations and low schema coverage, it lacks details on behavior and parameter usage, making it incomplete for fully informed use.

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 mentions loading data 'from files', which loosely relates to the 'data_folder' parameter, but with 0% schema description coverage, it doesn't add meaningful details like supported file types or folder structure. Since there's only one parameter, the baseline is higher, but the description doesn't fully compensate for the lack of schema documentation.

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 action ('Load') and the resource ('bookmarks and history data from files'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'organize_and_categorize' or 'web_search', which prevents a perfect score.

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 is provided on when to use this tool versus alternatives. The description lacks context about prerequisites, such as file formats or locations, and doesn't mention any sibling tools for comparison, leaving usage unclear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

organize_and_categorizeB

Clean, deduplicate, and categorize bookmark data

ParametersJSON Schema

Name	Required	Description	Default
`data_folder`	No		data
`output_folder`	No		organized

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

B3.1/5.0

Behavior2/5

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 mentions actions (clean, deduplicate, categorize) but doesn't specify whether this is a read-only or destructive operation, what permissions are needed, or any rate limits. This is a significant gap for a tool that implies data transformation.

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 a single, efficient sentence that front-loads the core purpose without any wasted words. It's appropriately sized for the tool's complexity, making it easy to parse and understand quickly.

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 moderate complexity (data processing with 2 parameters) and the presence of an output schema (which handles return values), the description is somewhat complete but lacks behavioral context. It covers the purpose but misses usage guidelines and transparency details, making it adequate but with clear gaps.

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 adds no parameter semantics beyond what the input schema provides, as schema description coverage is 0% and the description doesn't mention parameters. However, with only 2 parameters and high schema coverage (titles and defaults are clear), the baseline is 3 since the schema handles the heavy lifting adequately.

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 specific verbs (clean, deduplicate, categorize) and resource (bookmark data), making it easy to understand what it does. However, it doesn't distinguish itself from sibling tools like 'load_bookmark_data' which might handle similar data, so it doesn't reach the highest score.

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 like 'load_bookmark_data' for loading data or other siblings. It lacks explicit context, prerequisites, or exclusions, leaving the agent to infer usage based on the purpose alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

roll_diceC

Roll the dice with the given notation

ParametersJSON Schema

Name	Required	Description	Default
`notation`	Yes
`num_rolls`	No

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

C2/5.0

Behavior1/5

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 fails to mention the format of accepted notation, whether the roll is random, any constraints, error behavior, or the return value. This is a significant transparency gap.

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?

The description is very short and front-loaded, but it is under-specified. Every sentence is technically earned but the content is insufficient. It is concise at the expense of usefulness.

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?

Despite being a simple tool, the description is incomplete for an agent to use it correctly. It does not explain the expected notation syntax or the number of rolls, and while an output schema exists, the description does not help connect inputs to outputs. The description needs more detail to be functionally complete.

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%, so the description must compensate for parameter meaning. It only vaguely references 'notation' and completely ignores the 'num_rolls' parameter. The description provides essentially no semantic information beyond the parameter names.

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

Purpose3/5

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

The description is essentially a restatement of the tool name ('roll dice') with a vague reference to 'given notation'. It communicates the basic action but adds no detail about what notation is or how it differs from other tools. It's minimally clear but not strongly differentiated.

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?

There is no guidance on when to use this tool versus alternatives, nor any context about suitable scenarios. The description simply states the action without implying any usage conditions or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

web_searchC

Search the web for information about the given query

ParametersJSON Schema

Name	Required	Description	Default
`query`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

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 the full burden of disclosing behavioral traits. It does not mention whether the tool is read-only, what kind of results it returns, any potential side effects, or limitations. The description simply restates the action without adding safety or behavioral context.

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 a single, short sentence that is appropriately sized and front-loaded. It contains no fluff or redundant words, making it easy for an agent to parse quickly.

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?

Although the tool is simple and has an output schema, the description lacks essential contextual information such as when to use it, what the query parameter entails, and any behavioral details. Given the absence of annotations and minimal parameter guidance, the description is insufficient for fully correct tool invocation in ambiguous situations.

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?

With 0% schema description coverage and only one parameter, the description should explain what constitutes a valid query, any formatting requirements, or how the query is used. It only says 'about the given query,' which adds no meaningful detail beyond the parameter name and type.

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 performs a web search for the given query, using the specific verb 'search' and resource 'the web'. It implicitly distinguishes itself from sibling tools like github_search_repositories by specifying the web as the scope, but it does not explicitly name or contrast with alternatives.

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 offers no guidance on when to use this tool versus other sibling tools. It does not mention any preconditions, alternatives, or specific contexts, leaving the agent to infer usage only from the tool's name and generic purpose.

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 updatesv1.0.0Jan 3, 2026
- Changedload_bookmark_data1 field changed
  - addedInput schema / title
```
Added value: +"load_bookmark_dataArguments"
```
- Changedorganize_and_categorize1 field changed
  - addedInput schema / title
```
Added value: +"organize_and_categorizeArguments"
```
- Changedroll_dice1 field changed
  - addedInput schema / title
```
Added value: +"roll_diceArguments"
```
- Changedweb_search1 field changed
  - addedInput schema / title
```
Added value: +"web_searchArguments"
```
4 tool updatesOct 28, 2025
- First observedload_bookmark_data
- First observedorganize_and_categorize
- First observedroll_dice
- First observedweb_search

Deploy Server

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

C2.7/5.0

Scored 2026-04-18 08:15 across 4 tools

Disambiguation2/5

The tools have unclear boundaries and overlapping purposes. 'load_bookmark_data' and 'organize_and_categorize' both deal with bookmark data, making it ambiguous which to use for basic operations. 'roll_dice' is completely unrelated to the web search/domain theme, creating confusion about the server's core purpose. An agent would struggle to differentiate when to use each tool appropriately.

Naming Consistency3/5

The naming conventions are mixed but still readable. 'load_bookmark_data' and 'web_search' follow a verb_noun pattern, while 'organize_and_categorize' uses a verb_and_verb style and 'roll_dice' is a simple verb_noun. There's no consistent pattern across all tools, but the names are descriptive enough to understand their functions individually.

Tool Count2/5

With only 4 tools, the count feels too thin for a 'Tavily Web Search MCP Server' as implied by the name. The inclusion of unrelated tools like 'roll_dice' and bookmark management functions suggests poor scoping. A focused web search server would typically have more search-related operations, making this set appear incomplete and mismatched to its stated purpose.

Completeness2/5

There are significant gaps in the tool surface for a web search domain. While 'web_search' exists, there's no support for advanced search features, result filtering, or search history management. The bookmark tools are incomplete without create/update/delete operations, and 'roll_dice' is entirely out of scope. This creates dead ends for agents trying to perform comprehensive web search tasks.

Maintenance

ActivityInactive

ResponsivenessNo issues

Resources

GitHub Repository

Need Help?

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