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⚡ Welcome to Spector

The Zero-Overhead, Agent-Ready AI Memory Backbone.

Welcome to the Spector documentation — your central hub for the high-performance, agent-native AI search engine. Whether you're connecting AI agents via MCP, building RAG pipelines, powering recommendation systems, or need sub-millisecond search with zero infrastructure, you're in the right place.

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🔥 Why Spector?

Metric	Value
🤖 MCP Tools	6 agent-ready tools (semantic, hybrid, RAG, ingest, delete, status)
⚡ Vector Search Latency	0.05 ms avg @ 10K docs (128-dim)
🔍 Keyword Search Latency	0.98 ms avg @ 100K docs
🧬 Hybrid Search Latency	0.17 ms avg @ 10K docs
🚀 Vector Throughput	18,800 queries/sec @ 10K
🧵 Concurrent Hybrid	14,000+ ops/sec @ 16 threads (384-dim)
🗜️ IVF-PQ + TurboQuant	8–32× memory reduction
✅ Test Suite	331+ tests, all passing
📦 Dependencies	Zero (JDK only)

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🗺️ Quick Navigation

🚀 Getting Started

Page	Description
Getting Started	Build, run, and search in 5 minutes
What is Spector	Product overview, use cases, and comparisons
JDK API Status	Vector API, Panama FFM, and preview feature compatibility
FAQ	Common questions answered

🤖 Agent Integration (MCP)

Page	Description
MCP Integration Architecture	How the MCP server works under the hood
MCP Server Guide	Setup for Claude Desktop, Cursor, and custom agents

🏗️ Architecture & Concepts

Page	Description
Architecture Overview	Module diagram, data flow, threading model
Core Concepts	HNSW, IVF-PQ, BM25, RRF, SIMD deep-dives
Ingestion Pipeline	Document → chunk → embed → index pipeline
RAG Pipeline	End-to-end retrieval-augmented generation
Distributed Mode	Clustering, sharding, and replication
GPU Acceleration	CUDA setup and kernel details

📖 Reference

Page	Description
REST API Reference	All endpoints with curl examples
Java SDK Guide	Programmatic usage (client + embedded)
Spring AI Integration	Spring AI VectorStore adapter
CLI Reference	spectorctl commands
Configuration Guide	All parameters with tuning advice

⚙️ Operations & Community

Page	Description
Performance Tuning	Benchmarks and optimization strategies
Contributing	Development setup and PR process

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💡 Highlights at a Glance

graph LR
    A["🤖 AI Agent"] --> B["📡 MCP Server"]
    B --> C["⚡ SpectorEngine"]
    C --> D["🧠 Hybrid Search"]
    D --> E["🎯 RRF Fusion"]
    E --> F["🤖 LLM Re-ranking"]
    F --> G["✨ Results"]
    
    H["📄 Document"] --> I["🧩 Chunking"]
    I --> J["🧬 Embedding"]
    J --> C

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Tip

New here? Start with Getting Started to build and run your first search in under 5 minutes. Want to connect an AI agent? See the MCP Server Guide.

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🌟 Project Stats

Language	Java 25
License	Apache 2.0 · BSL 1.1 (memory module)
Modules	18 Maven modules
Dependencies	Zero (JDK only)
SIMD	AVX2 / AVX-512 / NEON
GPU	CUDA via Panama FFM
MCP	Built-in, 6 agent-ready tools
Distributed	gRPC fan-out + consistent hashing

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Built with ⚡ by Spectrayan · GitHub · Apache 2.0 · BSL 1.1 (memory)