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13 changes: 13 additions & 0 deletions servers/local_intelligence_mcp/server.yaml
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name: local_intelligence_mcp
image: mcp/local_intelligence_mcp
type: server
meta:
category: ai
tags:
- ai
about:
title: Local_intelligence_mcp
description: "A Swift-based, cross-platform Model Context Protocol (MCP) server that extends Apple’s on-device Intelligence features to local AI agents in a secure and privacy-preserving way.\n\nLocal Intelligence MCP provides text processing, summarization, and contextual analysis tools designed to augment Apple Intelligence capabilities within your own applications "
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Copilot AI Oct 11, 2025

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The description text is truncated mid-sentence, ending with 'within your own applications ' without completing the thought or closing properly.

Suggested change
description: "A Swift-based, cross-platform Model Context Protocol (MCP) server that extends Apple’s on-device Intelligence features to local AI agents in a secure and privacy-preserving way.\n\nLocal Intelligence MCP provides text processing, summarization, and contextual analysis tools designed to augment Apple Intelligence capabilities within your own applications "
description: "A Swift-based, cross-platform Model Context Protocol (MCP) server that extends Apple’s on-device Intelligence features to local AI agents in a secure and privacy-preserving way.\n\nLocal Intelligence MCP provides text processing, summarization, and contextual analysis tools designed to augment Apple Intelligence capabilities within your own applications. This enables developers to leverage advanced AI features locally, ensuring privacy and security for end users."

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icon: https://avatars.githubusercontent.com/u/1335392?v=4
source:
project: https://github.com/bretbouchard/Local_Intelligence_MCP
202 changes: 202 additions & 0 deletions servers/local_intelligence_mcp/tools.json
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[
{
"name": "text_normalize",
"description": "Clean and standardize text input by removing extra whitespace, normalizing punctuation, and applying consistent formatting rules",
"arguments": [
{
"name": "text",
"type": "string",
"desc": "The text content to normalize and clean"
},
{
"name": "removeFillers",
"type": "boolean",
"desc": "Whether to remove filler words and unnecessary content"
},
{
"name": "standardizeFormat",
"type": "boolean",
"desc": "Whether to apply standard formatting rules"
}
]
},
{
"name": "text_chunking",
"description": "Split large text documents into manageable chunks while preserving context and meaning boundaries",
"arguments": [
{
"name": "text",
"type": "string",
"desc": "The text content to split into chunks"
},
{
"name": "maxChunkSize",
"type": "number",
"desc": "Maximum size of each chunk in characters"
},
{
"name": "overlap",
"type": "number",
"desc": "Number of characters to overlap between chunks"
}
]
},
{
"name": "summarization",
"description": "Generate comprehensive summaries of text content with configurable style and length parameters",
"arguments": [
{
"name": "text",
"type": "string",
"desc": "The text content to summarize"
},
{
"name": "style",
"type": "string",
"desc": "Summary style: executive, technical, brief, detailed"
},
{
"name": "maxLength",
"type": "number",
"desc": "Maximum length of the summary in words"
}
]
},
{
"name": "pii_redaction",
"description": "Detect and redact personally identifiable information while preserving technical and domain-specific terminology",
"arguments": [
{
"name": "text",
"type": "string",
"desc": "The text content to scan for PII"
},
{
"name": "policy",
"type": "string",
"desc": "Redaction policy: conservative, balanced, aggressive"
},
{
"name": "preserveAudioTerms",
"type": "boolean",
"desc": "Whether to preserve audio and technical terminology"
}
]
},
{
"name": "focused_summarization",
"description": "Create targeted summaries focusing on specific aspects or topics within the content",
"arguments": [
{
"name": "text",
"type": "string",
"desc": "The text content to analyze and summarize"
},
{
"name": "focus",
"type": "array",
"desc": "Array of focus areas: key_decisions, action_items, technical_details, etc."
},
{
"name": "analysisDepth",
"type": "string",
"desc": "Analysis depth: surface, standard, deep"
}
]
},
{
"name": "content_purpose_detector",
"description": "Analyze and identify the purpose, intent, and context of text content with comprehensive categorization",
"arguments": [
{
"name": "text",
"type": "string",
"desc": "The text content to analyze for purpose and intent"
},
{
"name": "context",
"type": "object",
"desc": "Additional context information including domain and analysis preferences"
}
]
},
{
"name": "tag_generation",
"description": "Extract relevant keywords, topics, and metadata tags from text content with confidence scoring",
"arguments": [
{
"name": "text",
"type": "string",
"desc": "The text content to analyze for tag generation"
},
{
"name": "maxTags",
"type": "number",
"desc": "Maximum number of tags to generate"
},
{
"name": "includeTechnical",
"type": "boolean",
"desc": "Whether to include technical terminology in tags"
}
]
},
{
"name": "schema_extraction",
"description": "Extract and create structured data schemas from unstructured text content",
"arguments": [
{
"name": "text",
"type": "string",
"desc": "The text content to extract structured data from"
},
{
"name": "schemaType",
"type": "string",
"desc": "Type of schema to extract: person, event, product, technical_spec"
},
{
"name": "outputFormat",
"type": "string",
"desc": "Output format: json, yaml, xml"
}
]
},
{
"name": "health_check",
"description": "Perform comprehensive health monitoring and system diagnostics with detailed status reporting",
"arguments": []
},
{
"name": "system_info",
"description": "Retrieve detailed system information including device capabilities, performance metrics, and configuration details",
"arguments": [
{
"name": "categories",
"type": "array",
"desc": "Information categories to retrieve: device, performance, network, capabilities"
},
{
"name": "includeSensitive",
"type": "boolean",
"desc": "Whether to include sensitive system information"
}
]
},
{
"name": "capabilities_list",
"description": "List all available tools, capabilities, and system features with detailed descriptions and usage information",
"arguments": [
{
"name": "category",
"type": "string",
"desc": "Filter by capability category: text_processing, analysis, system, extraction"
},
{
"name": "includeExamples",
"type": "boolean",
"desc": "Whether to include usage examples for each capability"
}
]
}
]