What can you do with this server?

The Powerdrill MCP Server allows authenticated users to interact with Powerdrill datasets and perform data analysis tasks: * Authenticate using Powerdrill User ID and Project API Key * List datasets available in your account * Get dataset overview with detailed information * Create and run jobs to analyze data using natural language questions * Create sessions to group related jobs for organized analysis * List sessions to view active or recent analyses * List data sources within specific datasets * Create new datasets from scratch * Create data sources by uploading local files to datasets

Which integrations are available for this server?

Supports configuration of API credentials through .env files, making it easier to securely store and access Powerdrill authentication details. Enables installation and distribution of the MCP server through the npm registry, supporting both global installation and direct execution with npx. Mentions Powerdrill Flow Streamlit app as an alternative way to manipulate data in Powerdrill for users who have the appropriate credentials. Provides TypeScript implementation that needs to be built before running, enhancing type safety and development experience for the MCP server.

How do I use Powerdrill MCP Server?

1. Click on "Install 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., "@Powerdrill MCP Server analyze my sales dataset and show top performing products" 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.

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Powerdrill MCP Server

Official

by powerdrillai

Overview Schema Related Servers Score Discussions

TypeScript

Hybrid

Powerdrill MCP Server

A Model Context Protocol (MCP) server that provides tools to interact with Powerdrill datasets, authenticated with Powerdrill User ID and Project API Key.

Please go to https://chat.powerdrill.ai/ for AI data analysis individually or use with your Team.

If you have the Powerdrill User ID and Project API Key of your Team, you can manipulate the data via Powerdrill open sourced web clients:

Node.js edtion: https://flow.powerdrill.ai/, or play with the open source web client https://github.com/powerdrillai/powerdrill-flow.
Python edtion: https://powerdrill-flow.streamlit.app/, or play with the open source web client https://github.com/powerdrillai/powerdrill-flow-streamlit.

Features

Authenticate with Powerdrill using User ID and Project API Key
List available datasets in your Powerdrill account
Get detailed information about specific datasets
Create and run jobs on datasets with natural language questions
Integration with Claude Desktop and other MCP-compatible clients

Related MCP server: HF Dataset MCP

Installation

Installing via Smithery

To install powerdrill-mcp for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @powerdrillai/powerdrill-mcp --client claude

From npm

# Install globally
npm install -g @powerdrillai/powerdrill-mcp

# Or run directly with npx
npx @powerdrillai/powerdrill-mcp

From Source

Clone this repository and install dependencies:

git clone https://github.com/yourusername/powerdrill-mcp.git
cd powerdrill-mcp
npm install

CLI Usage

If installed globally:

# Start the MCP server
powerdrill-mcp

If using npx:

# Run the latest version
npx -y @powerdrillai/powerdrill-mcp@latest

You'll need to configure environment variables with your Powerdrill credentials before running:

# Set environment variables
export POWERDRILL_USER_ID="your_user_id"
export POWERDRILL_PROJECT_API_KEY="your_project_api_key"

Or create a .env file with these values.

Prerequisites

To use this MCP server, you'll need a Powerdrill account with valid API credentials (User ID and API Key). Here's how to obtain them:

Sign up for a Powerdrill Team account if you haven't already
Navigate to your account settings
Look for the API section where you'll find your:
- User ID: A unique identifier for your account
- API Key: Your authentication token for API access

First, watch this video tutorial on how to create your Powerdrill Team:

Create Powerdrill Team Tutorial

Then, follow this video tutorial for setting up your API credentials:

Powerdrill API Setup Tutorial

Quick Setup

The easiest way to set up the server is using the provided setup script:

# Make the script executable
chmod +x setup.sh

# Run the setup script
./setup.sh

This will:

Install dependencies
Build the TypeScript code
Create a .env file if it doesn't exist
Generate configuration files for Claude Desktop and Cursor with the npx-based configuration (recommended)

Then edit your .env file with your actual credentials:

POWERDRILL_USER_ID=your_actual_user_id
POWERDRILL_PROJECT_API_KEY=your_actual_project_api_key

Also update the credentials in the generated configuration files before using them.

Manual Installation

If you prefer to set up manually:

# Install dependencies
npm install

# Build the TypeScript code
npm run build

# Copy the environment example file
cp .env.example .env

# Edit the .env file with your credentials

Usage

Running the server

npm start

Integrating with Claude Desktop

Open Claude Desktop
Go to Settings > Server Settings
Add a new server with one of the following configurations:

Option 1: Using npx (Recommended)

{
  "powerdrill": {
    "command": "npx",
    "args": [
      "-y",
      "@powerdrillai/powerdrill-mcp@latest"
    ],
    "env": {
      "POWERDRILL_USER_ID": "your_actual_user_id",
      "POWERDRILL_PROJECT_API_KEY": "your_actual_project_api_key"
    }
  }
}

Option 2: Using node with local installation

{
  "powerdrill": {
    "command": "node",
    "args": ["/path/to/powerdrill-mcp/dist/index.js"],
    "env": {
      "POWERDRILL_USER_ID": "your_actual_user_id",
      "POWERDRILL_PROJECT_API_KEY": "your_actual_project_api_key"
    }
  }
}

Save the configuration
Restart Claude Desktop

Integrating with Cursor

Open Cursor
Go to Settings > MCP Tools
Add a new MCP tool with one of the following configurations:

Option 1: Using npx (Recommended)

{
  "powerdrill": {
    "command": "npx",
    "args": [
      "-y",
      "@powerdrillai/powerdrill-mcp@latest"
    ],
    "env": {
      "POWERDRILL_USER_ID": "your_actual_user_id",
      "POWERDRILL_PROJECT_API_KEY": "your_actual_project_api_key"
    }
  }
}

Option 2: Using node with local installation

{
  "powerdrill": {
    "command": "node",
    "args": ["/path/to/powerdrill-mcp/dist/index.js"],
    "env": {
      "POWERDRILL_USER_ID": "your_actual_user_id",
      "POWERDRILL_PROJECT_API_KEY": "your_actual_project_api_key"
    }
  }
}

Save the configuration
Restart Cursor if needed

Using the tools

Once connected, you can use the Powerdrill tools in your conversations with Claude Desktop, Cursor, Cline, Windsurf, etc.:

List datasets: What datasets are available in my Powerdrill account? or Show me all my datasets
Create dataset: Create a new dataset called "Sales Analytics" or Make a new dataset named "Customer Data" with description "Customer information for 2024 analysis"
Create data source from local file: Upload the file /Users/your_name/Downloads/sales_data.csv to dataset {dataset_id} or Add my local file /path/to/customer_data.xlsx to my {dataset_id} dataset
Get dataset overview: Tell me more about this dataset: {dataset_id} or Describe the structure of dataset {dataset_id}
Create a job: Analyze dataset {dataset_id} with this question: "How has the trend changed over time?" or Run a query on {dataset_id} asking "What are the top 10 customers by revenue?"
Create a session: Create a new session named "Sales Analysis 2024" for my data analysis or Start a session called "Customer Segmentation" for analyzing market data
List data sources: What data sources are available in dataset {dataset_id}? or Show me all files in the {dataset_id} dataset
List sessions: Show me all my current analysis sessions or List my recent data analysis sessions

Available Tools

mcp_powerdrill_list_datasets

Lists available datasets from your Powerdrill account.

Parameters:

limit (optional): Maximum number of datasets to return

Example response:

{
  "datasets": [
    {
      "id": "dataset-dasfadsgadsgas",
      "name": "mydata",
      "description": "my dataset"
    }
  ]
}

mcp_powerdrill_get_dataset_overview

Gets detailed overview information about a specific dataset.

Parameters:

datasetId (required): The ID of the dataset to get overview information for

Example response:

{
  "id": "dset-cm5axptyyxxx298",
  "name": "sales_indicators_2024",
  "description": "A dataset comprising 373 travel bookings with 15 attributes...",
  "summary": "This dataset contains 373 travel bookings with 15 attributes...",
  "exploration_questions": [
    "How does the booking price trend over time based on the BookingTimestamp?",
    "How does the average booking price change with respect to the TravelDate?"
  ],
  "keywords": [
    "Travel Bookings",
    "Booking Trends",
    "Travel Agencies"
  ]
}

mcp_powerdrill_create_job

Creates a job to analyze data with natural language questions.

Parameters:

question (required): The natural language question or prompt to analyze the data
dataset_id (required): The ID of the dataset to analyze
datasource_ids (optional): Array of specific data source IDs within the dataset to analyze
session_id (optional): Session ID to group related jobs
stream (optional, default: false): Whether to stream the results
output_language (optional, default: "AUTO"): The language for the output
job_mode (optional, default: "AUTO"): The job mode

Example response:

{
  "job_id": "job-cm3ikdeuj02zk01l1yeuirt77",
  "blocks": [
    {
      "type": "CODE",
      "content": "```python\nimport pandas as pd\n\ndef invoke(input_0: pd.DataFrame) -> pd.DataFrame:\n...",
      "stage": "Analyze"
    },
    {
      "type": "TABLE",
      "url": "https://static.powerdrill.ai/tmp_datasource_cache/code_result/...",
      "name": "trend_data.csv",
      "expires_at": "2024-11-21T09:56:34.290544Z"
    },
    {
      "type": "IMAGE",
      "url": "https://static.powerdrill.ai/tmp_datasource_cache/code_result/...",
      "name": "Trend of Deaths from Natural Disasters Over the Century",
      "expires_at": "2024-11-21T09:56:34.290544Z"
    },
    {
      "type": "MESSAGE",
      "content": "Analysis of Trends in the Number of Deaths from Natural Disasters...",
      "stage": "Respond"
    }
  ]
}

mcp_powerdrill_create_session

Creates a new session to group related jobs together.

Parameters:

name (required): The session name, which can be up to 128 characters in length
output_language (optional, default: "AUTO"): The language in which the output is generated. Options include: "AUTO", "EN", "ES", "AR", "PT", "ID", "JA", "RU", "HI", "FR", "DE", "VI", "TR", "PL", "IT", "KO", "ZH-CN", "ZH-TW"
job_mode (optional, default: "AUTO"): Job mode for the session. Options include: "AUTO", "DATA_ANALYTICS"
max_contextual_job_history (optional, default: 10): The maximum number of recent jobs retained as context for the next job (0-10)
agent_id (optional, default: "DATA_ANALYSIS_AGENT"): The ID of the agent

Example response:

{
  "session_id": "session-abcdefghijklmnopqrstuvwxyz"
}

mcp_powerdrill_list_data_sources

Lists data sources in a specific dataset.

Parameters:

datasetId (required): The ID of the dataset to list data sources from
pageNumber (optional, default: 1): The page number to start listing
pageSize (optional, default: 10): The number of items on a single page
status (optional): Filter data sources by status: synching, invalid, synched (comma-separated for multiple)

Example response:

{
  "count": 3,
  "total": 5,
  "page": 1,
  "page_size": 10,
  "data_sources": [
    {
      "id": "dsource-a1b2c3d4e5f6g7h8i9j0",
      "name": "sales_data.csv",
      "type": "CSV",
      "status": "synched",
      "size": 1048576,
      "dataset_id": "dset-cm5axptyyxxx298"
    },
    {
      "id": "dsource-b2c3d4e5f6g7h8i9j0k1",
      "name": "customer_info.xlsx",
      "type": "EXCEL",
      "status": "synched",
      "size": 2097152,
      "dataset_id": "dset-cm5axptyyxxx298"
    },
    {
      "id": "dsource-c3d4e5f6g7h8i9j0k1l2",
      "name": "market_research.pdf",
      "type": "PDF",
      "status": "synched",
      "size": 3145728,
      "dataset_id": "dset-cm5axptyyxxx298"
    }
  ]
}

mcp_powerdrill_list_sessions

Lists sessions from your Powerdrill account.

Parameters:

pageNumber (optional): The page number to start listing (default: 1)
pageSize (optional): The number of items on a single page (default: 10)
search (optional): Search for sessions by name

Example response:

{
  "count": 2,
  "total": 2,
  "sessions": [
    {
      "id": "session-123abc",
      "name": "Product Analysis",
      "job_count": 3,
      "created_at": "2024-03-15T10:30:00Z",
      "updated_at": "2024-03-15T11:45:00Z"
    },
    {
      "id": "session-456def",
      "name": "Financial Forecasting",
      "job_count": 5,
      "created_at": "2024-03-10T14:20:00Z",
      "updated_at": "2024-03-12T09:15:00Z"
    }
  ]
}

mcp_powerdrill_create_dataset

Creates a new dataset in your Powerdrill account.

Parameters:

name (required): The dataset name, which can be up to 128 characters in length
description (optional): The dataset description, which can be up to 128 characters in length

Example response:

{
  "id": "dataset-adsdfasafdsfasdgasd",
  "message": "Dataset created successfully"
}

mcp_powerdrill_create_data_source_from_local_file

Creates a new data source by uploading a local file to a specified dataset.

Parameters:

dataset_id (required): The ID of the dataset to create the data source in
file_path (required): The local path to the file to upload
file_name (optional): Custom name for the file, defaults to the original filename
chunk_size (optional, default: 5MB): Size of each chunk in bytes for multipart upload

Example response:

{
  "dataset_id": "dset-cm5axptyyxxx298",
  "data_source": {
    "id": "dsource-a1b2c3d4e5f6g7h8i9j0",
    "name": "sales_data_2024.csv",
    "type": "FILE",
    "status": "synched",
    "size": 2097152
  },
  "file": {
    "name": "sales_data_2024.csv",
    "size": 2097152,
    "object_key": "uploads/user_123/sales_data_2024.csv"
  }
}

Troubleshooting

If you encounter issues:

Make sure your environment variables are set correctly in .env
Check that the server starts successfully with npm start
Verify your Claude Desktop configuration points to the correct file paths
Check the console output for any error messages

License

MIT

Available Tools

9 tools

mcp_powerdrill_create_datasetD

ParametersJSON Schema

Name	Required	Description	Default
`name`	Yes	The dataset name, which can be up to 128 characters in length
`description`	No	The dataset description, which can be up to 128 characters in length

TDQS

D1/5.0

Behavior1/5

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

Tool has no description.

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

Conciseness1/5

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

Tool has no description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has no description.

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?

Tool has no description.

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

Purpose1/5

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

Tool has no description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Tool has no description.

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

mcp_powerdrill_create_data_source_from_local_fileD

ParametersJSON Schema

Name	Required	Description
`dataset_id`	Yes	The ID of the dataset to create the data source in
`file_path`	Yes	The local path to the file to upload
`file_name`	No	Optional custom name for the file, defaults to the original filename
`chunk_size`	No	Size of each chunk in bytes, default is 5MB

TDQS

D1/5.0

Behavior1/5

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

Tool has no description.

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

Conciseness1/5

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

Tool has no description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has no description.

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?

Tool has no description.

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

Purpose1/5

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

Tool has no description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Tool has no description.

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

mcp_powerdrill_create_jobD

ParametersJSON Schema

Name	Required	Description	Default
`question`	Yes	The natural language question or prompt to analyze the data
`dataset_id`	Yes	The ID of the dataset to analyze
`datasource_ids`	No	Optional array of specific data source IDs within the dataset to analyze
`session_id`	Yes	Session ID to group related jobs
`stream`	No	Whether to stream the results (default: false)
`output_language`	No	The language for the output (default: AUTO)	AUTO
`job_mode`	No	The job mode (default: AUTO)	AUTO

TDQS

D1/5.0

Behavior1/5

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

Tool has no description.

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

Conciseness1/5

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

Tool has no description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has no description.

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?

Tool has no description.

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

Purpose1/5

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

Tool has no description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Tool has no description.

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

mcp_powerdrill_create_sessionD

ParametersJSON Schema

Name	Required	Description	Default
`name`	Yes	The session name, which can be up to 128 characters in length
`output_language`	No	The language in which the output is generated	AUTO
`job_mode`	No	Job mode for the session	AUTO
`max_contextual_job_history`	No	The maximum number of recent jobs retained as context for the next job
`agent_id`	No	The ID of the agent	DATA_ANALYSIS_AGENT

TDQS

D1/5.0

Behavior1/5

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

Tool has no description.

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

Conciseness1/5

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

Tool has no description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has no description.

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?

Tool has no description.

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

Purpose1/5

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

Tool has no description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Tool has no description.

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

mcp_powerdrill_delete_datasetD

ParametersJSON Schema

Name	Required	Description	Default
`datasetId`	Yes	The ID of the dataset to delete

TDQS

D1/5.0

Behavior1/5

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

Tool has no description.

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

Conciseness1/5

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

Tool has no description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has no description.

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?

Tool has no description.

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

Purpose1/5

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

Tool has no description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Tool has no description.

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

mcp_powerdrill_get_dataset_overviewD

ParametersJSON Schema

Name	Required	Description	Default
`datasetId`	Yes	The ID of the dataset to get overview information for

TDQS

D1/5.0

Behavior1/5

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

Tool has no description.

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

Conciseness1/5

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

Tool has no description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has no description.

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?

Tool has no description.

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

Purpose1/5

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

Tool has no description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Tool has no description.

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

mcp_powerdrill_list_datasetsD

ParametersJSON Schema

Name	Required	Description
`limit`	No	Maximum number of datasets to return
`pageNumber`	No	The page number to start listing (default: 1)
`pageSize`	No	The number of items on a single page (default: 10)
`search`	No	Search for datasets by name

TDQS

D1/5.0

Behavior1/5

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

Tool has no description.

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

Conciseness1/5

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

Tool has no description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has no description.

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?

Tool has no description.

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

Purpose1/5

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

Tool has no description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Tool has no description.

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

mcp_powerdrill_list_data_sourcesD

ParametersJSON Schema

Name	Required	Description
`datasetId`	Yes	The ID of the dataset to list data sources from
`pageNumber`	No	The page number to start listing (default: 1)
`pageSize`	No	The number of items on a single page (default: 10)
`status`	No	Filter data sources by status: synching, invalid, synched (comma-separated for multiple)

TDQS

D1/5.0

Behavior1/5

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

Tool has no description.

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

Conciseness1/5

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

Tool has no description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has no description.

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?

Tool has no description.

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

Purpose1/5

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

Tool has no description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Tool has no description.

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

mcp_powerdrill_list_sessionsD

ParametersJSON Schema

Name	Required	Description
`pageNumber`	No	The page number to start listing (default: 1)
`pageSize`	No	The number of items on a single page (default: 10)
`search`	No	Search for sessions by name

TDQS

D1/5.0

Behavior1/5

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

Tool has no description.

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

Conciseness1/5

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

Tool has no description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has no description.

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?

Tool has no description.

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

Purpose1/5

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

Tool has no description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Tool has no description.

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

Install Server

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

C2.1/5.0

Disambiguation5/5

Each tool has a clearly distinct purpose with no overlap: create/delete/list operations target specific resources (datasets, data sources, jobs, sessions) and get_dataset_overview provides unique insight. The resource-action combinations are unambiguous, making tool selection straightforward for an agent.

Naming Consistency5/5

All tools follow a perfect verb_noun pattern with consistent snake_case: mcp_powerdrill_<verb>_<noun> or mcp_powerdrill_<verb>_<noun>_<modifier>. The naming is highly predictable, using verbs like create, delete, get, list consistently across resources.

Tool Count5/5

With 9 tools, the count is well-scoped for a data processing server. It covers core operations for datasets, data sources, jobs, and sessions without being overwhelming. Each tool appears to earn its place in managing these resources.

Completeness4/5

The toolset provides strong CRUD coverage for datasets (create, delete, list, get overview) and listing for data sources and sessions, with create operations for jobs and sessions. Minor gaps include no update operations for datasets or data sources, and no delete/get for jobs or sessions, but agents can likely work around these for basic workflows.

Maintenance

ActivityInactive

ResponsivenessNo issues

Resources

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