F
licenseNot graded
qualityD
maintenanceAn MCP Server that enables interaction with Ticketmaster's Discovery API for accessing event, venue, and artist information through natural language commands.
-
eventin-mcp-server
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., "@eventin-mcp-serverBook the main hall for July 15th from 2pm to 5pm"
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.
Eventin MCP Server - Quick Start Guide
Setup Steps:
Install Python 3.13 (if not already installed).
(Recommended) Create and activate a virtual environment: python -m venv .venv ..venv\Scripts\activate
Install uv (if not already installed): pip install uv
Install dependencies: uv pip install -r requirements.txt OR uv pip install -e .
Start eventin locally, and check if it's running in the browser properly
Replace My base_url your yours
Run the Eventin MCP server: uv --directory . run eventin_mcp_server.py
This will start the MCP server for Eventin bookings.
Logs:
Server logs are written to booking_server.log in this directory.
======================================
Related MCP server: OnSched Consumer API MCP Server
Steps to communicate with our MCP server using claude desktop:
Download and install claude desktop
Open claude desktop, click "Upgrade to connect your tools to Claude"
Click "Manage Connectors" in right corner
Click "Developer" menu in the left side, and you find "Edit Config" button, click it
After that, you will find "claude_desktop_config.json", here just put following code
{
"mcpServers": {
"eventin": {
"command": "uv",
"args": [
"--directory",
"D:\\machine_learning\\mcp-server-demo", //your directory may be different
"run",
"eventin_mcp_server.py"
]
}
}
}Now you will see that, your mcp tools are connected with the claude
Sample output
Available Tools
2 toolsget_bookingsB
Get event bookings with filters
Args: page: Page number (default 1) per_page: Items per page (default 10) status: Filter by payment status (e.g., 'completed', 'failed') event_id: Filter by specific event ID
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | ||
| status | No | ||
| event_id | No | ||
| per_page | No |
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, the description must fully disclose behavioral traits. It implies a read-only operation via 'Get' but does not explicitly state whether it is safe, what response format to expect, or any side effects. Pagination behavior and error handling are also omitted.
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 concise and front-loaded with the main purpose, followed by a clean parameter list. No unnecessary words or repetition, though the formatting could be slightly more polished with markdown.
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?
The description covers the core functionality and filters, and an output schema exists to explain return values. However, it lacks usage guidance relative to get_booking_stats and does not mention pagination behavior or any limitations, leaving the context incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description manually lists each parameter with a default or semantic meaning, such as 'status: Filter by payment status' and 'event_id: Filter by specific event ID', which compensates for the 0% schema description coverage. The schema only provides types and defaults, so the description adds useful context.
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 retrieves event bookings with filtering, which identifies the primary function and resource. However, it does not explicitly differentiate from the sibling tool get_booking_stats, though the resource names are distinct enough.
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 the sibling get_booking_stats. There is no mention of alternatives, prerequisites, or typical scenarios, leaving the agent without direction for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_booking_statsB
Get summary statistics of bookings
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
B3.2/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for behavioral disclosure. It only mentions 'get', which implies a read operation, but does not describe permissions, side effects, limitations, or response characteristics. The output schema helps with return format, but behavioral transparency is sparse.
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 concise sentence: 'Get summary statistics of bookings'. It is front-loaded with the verb and resource, with no filler or redundant information. Every word earns its place.
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?
The tool is simple (zero parameters) and has an output schema, so the description doesn't need to explain return values. However, it lacks usage context, limitations, or any behavioral notes, making it minimally viable but not comprehensive. Given the simplicity, it is acceptable but could be improved with guidance on using it alongside get_bookings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline score is 4 per the guidelines. The description adds no parameter semantics because there are no parameters to describe, and the schema coverage is trivially complete.
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 verb 'Get' and the resource 'summary statistics of bookings'. It differentiates from the sibling tool get_bookings by indicating aggregated data rather than raw bookings, though it doesn't explicitly compare. It is specific enough to convey the tool's basic function.
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 the sibling get_bookings. The description lacks any context about scenarios, prerequisites, or exclusions, leaving the agent without comparative direction.
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.
2 tool updates
v0.1.0- First observed
get_booking_stats - First observed
get_bookings
TDQS
B3.4/5.0
Scored across 2 tools
Disambiguation5/5
The two tools are clearly distinct: get_bookings returns individual booking records with filters, while get_booking_stats provides summary statistics. There is no functional overlap, making selection unambiguous.
Naming Consistency5/5
Both tool names follow a consistent pattern: 'get_' followed by a noun, using snake_case (get_bookings, get_booking_stats). This is predictable and uniform.
Tool Count3/5
With only two tools, the server feels thin and below the typical well-scoped range of 3-15 tools. While both tools are relevant to bookings, the count is borderline and may be insufficient for broader event management needs.
Completeness2/5
The server only provides read and aggregate operations (list bookings, get stats). Missing are any create, update, cancel, or delete functionalities, which are essential for a complete booking management workflow. This represents significant gaps.
Maintenance
ActivityInactive
ResponsivenessNo issues
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Eventify MCP server — manage events, attendees, sessions, speakers, sponsors, and analytics.
MCP server for Meitre restaurant reservations.
MCP server unifying ERPs, CRMs, APIs and knowledge base for Claude, ChatGPT and Gemini.
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