VISEON Ask
VISEON's Schema.org knowledge graph: products, services, people, FAQs and terms, from viseon.io
Should I use this
Quality & Safety
Based on automated analysis of tool definitions and protocol compliance.
Context Cost
This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.
Install
One-Click Install
Add this to your `claude_desktop_config.json` file:
{
"mcpServers": {
"semantic-intelligence": {
"url": "https://viseon.io/mcp"
}
}
}Remote endpoints
https://viseon.io/mcpstreamable-httpWhat it can do
Tool inventory
Tools (5)
🟢get_entity(url)
Get complete schema.org entity data by URL
Input Schema
{
"type": "object",
"properties": {
"url": {
"type": "string",
"description": "Full URL of the entity"
}
},
"required": [
"url"
]
}Output Schema
{
"type": "object",
"additionalProperties": true
}🟢query_relationships(subject, predicate)
Find entities connected to a subject
Input Schema
{
"type": "object",
"properties": {
"subject": {
"type": "string"
},
"predicate": {
"type": "string"
}
},
"required": [
"subject"
]
}Output Schema
{
"type": "object",
"properties": {
"items": {
"type": "array",
"items": {
"type": "object"
}
},
"count": {
"type": "integer"
}
},
"required": [
"items",
"count"
]
}🟢find_by_type(type)
Find all entities of a specific schema.org type
Input Schema
{
"type": "object",
"properties": {
"type": {
"type": "string"
}
},
"required": [
"type"
]
}Output Schema
{
"type": "object",
"properties": {
"items": {
"type": "array",
"items": {
"type": "string"
}
},
"count": {
"type": "integer"
}
},
"required": [
"items",
"count"
]
}🟢search_content(query)
Full-text search across graph
Input Schema
{
"type": "object",
"properties": {
"query": {
"type": "string"
}
},
"required": [
"query"
]
}Output Schema
{
"type": "object",
"properties": {
"items": {
"type": "array",
"items": {
"type": "string"
}
},
"count": {
"type": "integer"
}
},
"required": [
"items",
"count"
]
}🟢fuzzy_find_and_traverse(query, type, limit, weights)
Find and rank schema.org entities from natural language. Returns bounded entity context with relationship IDs; use get_entity for full detail.
Input Schema
{
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Search terms (e.g., \"AI optimisation services\", \"schema markup articles\")"
},
"type": {
"type": "string",
"description": "Optional: filter by entity type (Organization, Service, Article, Person, WebPage, Question)"
},
"limit": {
"type": "integer",
"minimum": 1,
"maximum": 10,
"default": 5,
"description": "Optional: maximum ranked entities to return (default 5, maximum 10)"
},
"weights": {
"type": "object",
"description": "Optional: Custom weight multipliers for ranking",
"properties": {
"predicates": {
"type": "object",
"description": "Predicate weight multipliers (e.g., {\"name\": 3.0, \"about\": 1.5})"
},
"entityTypes": {
"type": "object",
"description": "Entity type multipliers (e.g., {\"Service\": 2.0, \"Article\": 1.0, \"Question\": 2.0})"
}
}
}
},
"required": [
"query"
]
}Output Schema
{
"type": "object",
"properties": {
"items": {
"type": "array",
"items": {
"type": "object"
}
},
"count": {
"type": "integer"
}
},
"required": [
"items",
"count"
]
}Community
Evidence