Linkforge

"The Missing SaaS Link"

LinkForge MCP serves as an AI-native interface, replacing raw complex CRUD operations with token-optimized semantic querying and insights. By providing pre-filtered, AI-ready intelligence instead of raw data dumps, LinkForge significantly reduces token load and latency for Large Language Models.

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🚀 Core Innovation

LinkForge MCP improves on existing projects by:

1. Semantic Tooling Instead of CRUD: Tools pre-filter at the server level, returning compressed, AI-ready summaries.
2. Token-Aware Response Compression: Each tool returns structured, minimal, AI-optimized output.
3. Context-Aware Query Layer: Translates semantic intents to platform filters.
4. Cross-Platform Schema Normalization: Normalizes SaaS data (e.g., Tasks, Events) into unified models.
5. Modular SaaS Adapters: Each SaaS integration is an independent adapter sharing the core semantic engine.

🏗️ Architectural Layers

1. The Core Server & Semantic Compression

• Location: src/core/server.ts & src/core/compression.ts
• What it does: Replaces raw data dumps with AI-optimized strings. The TokenCompressionLayer drops null objects, empty properties, and restructures objects into simple \n-delimited semantic summaries.

2. The Semantic Query Engine

• Location: src/core/query.ts & src/core/intent.ts
• What it does: Classifies AI queries (like isUrgent or upcoming) into a standardized SemanticQuery. The QueryTranslator maps this intent object to specific platform API search terms.

3. Modular SaaS Adapters

The system provides several mock SaaS adapters that prove the architecture works. Instead of exposing dozens of complex pagination and filter endpoints, we expose pure insights:

Todoist

• todoist_get_overdue_high_priority_tasks
• todoist_get_tasks_due_today
• Result: Converts missing fields, normalizes priority, calculates exact dates automatically.

Linear

• linear_get_blocked_high_priority_issues
• linear_get_unassigned_urgent_issues
• Result: Automatically groups tickets based on GraphQL state mappings (Todo, In Progress, Done, Blocked).

Spotify

• spotify_get_recently_skipped_tracks
• spotify_get_most_replayed_tracks_last_week
• spotify_get_focus_music_playlists
• Result: Generates AI-actionable summaries ("Frequently Skipped", "Heavy Rotation") rather than raw track metadata.

Strava

• strava_get_injury_risk_pattern
• strava_get_longest_effort_last_30_days
• strava_get_declining_pace_runs
• Result: Analyzes heart rate distributions over pace times to flag "High Exhaustion/Injury Risk Run".

4. Performance & Security

• Token Budgeting (Cache): src/core/cache.ts introduces time-to-live memorization to avoid hitting rate limits.
• AI Loop Defense: src/core/security.ts tracks invocation counts per AI tool over rolling windows, safely breaking the AI out of infinite loops via MCP errors.

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🛠️ Quick Start

Prerequisites

• Node.js (v18+)
• npm or pnpm

Installation

git clone https://github.com/pronzzz/linkforge-mcp.git
cd linkforge-mcp
npm install

Running the Server

To build the TypeScript source and run the server:

npm run build
npm start

For development with hot-reloading:

npm run dev

The system will initialize all semantic tools asynchronously and begin serving over stdio for standard MCP client integration.

📄 Documentation

• Project Guide
• Contributing Guidelines
• Code of Conduct

📜 License

This project is licensed under the MIT License.