OpenRefine MCP Server

by FiquemSabendo

Overview Schema Source Related Servers Discussions Admin

Python

Local

create_project

Import a dataset from a URL to create a new OpenRefine project.

Instructions

Create a new OpenRefine project from a dataset URL.

Args: dataset_url: URL of the dataset to import name: Optional name for the project

Returns: Project information containing project ID and name

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "dataset_url": "<dataset_url>"
    },
    "name": "create_project"
  }
}

Input Schema

Name	Required	Description	Default
`dataset_url`	Yes
`name`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jun 17, 2026

TDQS

A3.8/5.0

Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It only states basic creation without mentioning potential side effects, authentication, or error handling. It lacks details on what happens if the URL is invalid or timeouts.

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 with a clear docstring format, front-loading the purpose. The Args and Returns sections are structured and useful, though the return description could be more formal.

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 simple tool with 2 parameters and an output schema, the description covers purpose and parameters adequately. However, it lacks information on error scenarios, prerequisites, or time expectations, making it slightly 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 includes an Args section that explains dataset_url and name, adding meaning beyond the bare-bones schema (which has 0% coverage). It provides clear purpose for each parameter despite lacking format constraints.

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 it creates a new OpenRefine project from a dataset URL, using specific verb-resource combination. It distinguishes itself from sibling tools like delete_project, export_csv, and apply_operations.

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

Usage Guidelines4/5

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

The description implies when to use this tool (to create a project), but does not explicitly state when not to use it or mention alternatives. It is clear enough given the sibling tool names.

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

Deploy Server