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DataForge Semantic MCP Server

DataForge Semantic MCP Server

by SGromych
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

df_create_project

Create a new DataForge project with an initial version automatically generated. Provide a name, optional color, and description to set up a project for managing semantic metadata.

Instructions

WRITES TO DATAFORGE. Create a project. An initial version is created with it.

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": {
      "name": "<name>"
    },
    "name": "df_create_project"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYes
colorNoHex colour, e.g. #2479BC
descriptionNo
idempotency_keyNoOptional UUID v4. Reusing a key within 24 hours replays the original response instead of applying the change twice. One is generated automatically when omitted.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

B3/5.0
Behavior3/5

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

Annotations already indicate a non-read-only, non-idempotent, non-destructive operation. The description adds useful context that it writes to DataForge and that an initial version is automatically created. It does not disclose permissions, reversibility, or other side effects, but it goes slightly beyond the annotations.

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 three short sentences with no filler and the write warning is front-loaded. It is sparse but not padded, and every sentence carries at least some information.

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?

For a mutation tool with no output schema and minimal annotation detail, the description covers the key side effect (initial version creation) but omits expected response, prerequisites, and reversibility. It is minimally viable for a straightforward create operation, but not complete.

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?

Schema description coverage is 50%: color and idempotency_key are documented, but name and description are not. The tool description adds no parameter-level meaning and does not compensate for the undocumented parameters or explain the idempotency_key behavior.

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 states the specific verb and resource: 'Create a project.' The added note that an initial version is created clarifies scope. It does not explicitly distinguish this from siblings like df_create_version or df_update_project, but the resource is clear 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?

There is no guidance on when to use this tool versus alternatives such as df_create_version or df_import_version_from_git. The description only restates the core action without context, triggers, or exclusions.

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

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