A
licenseA
qualityB
maintenanceA local (stdio) MCP server for PixelVault — agent-first image hosting, enabling upload of local files by path without base64.
6
6 npm
MIT
detection-mcp
by hoshiori-dev
Related Servers
Alternatives to detection-mcp
No user-submitted related servers found.
Related Servers
- FlicenseNot gradedqualityCmaintenanceMCP server that provides a local Web production console and HTTP control plane for AI video creation, exposing tools for project/revision management, media analysis, editing, review, and delivery while keeping formal rendering behind explicit approval gates.-
SensorMCP Serverofficial
AlicenseNot gradedqualityDmaintenanceAn MCP server that enables automated dataset creation and custom object detection model training through natural language interactions. It integrates foundation models like GroundedSAM for auto-labeling and supports training specialized YOLOv8 models using local or Unsplash images.4MIT- AlicenseNot gradedqualityDmaintenanceA filesystem-backed MCP server with REST API for AI tool integration and project workflow tracking. Zero database required.221 npmMIT
- AlicenseNot gradedqualityBmaintenanceMCP server for multimodal understanding and object grounding (bounding boxes) across images, videos, and documents, with support for multiple AI providers (Zhipu GLM-V, OpenAI GPT-4o, Anthropic Claude, or any OpenAI-compatible endpoint).1MIT
- FlicenseBqualityDmaintenanceOpenAI-compatible MCP server for running image analysis tools against your own vision model endpoint.78 npm-
TDQS
B3.4/5.0
Scored across 23 tools
Disambiguation5/5
Each tool targets a distinct resource (dataset, category, image, bbox, rotated bbox, export) with clear action verbs. Even the two annotation types are unambiguously separated by bbox vs rotated_bbox in their names.
Naming Consistency5/5
All tools follow a consistent verb_noun snake_case pattern, with clear verbs like create, delete, list, edit, add, get, restore, set, preview, export. Minor pluralization inconsistencies (e.g., add_bbox_annotations vs edit_bbox_annotation) do not undermine overall predictability.
Tool Count3/5
At 23 tools, the server sits in the heavy range (16-25). However, the number is justified by the broad domain covering datasets, categories, images, two annotation types, and export, so it feels borderline rather than excessive.
Completeness4/5
The surface covers full CRUD lifecycles for datasets, categories, and both annotation types, plus image status management and export. A notable gap is the lack of a dataset update operation, but core workflows are well-supported.
Maintenance
ActivityMaintained
ResponsivenessSyncing