β‘ Welcome to Spector
The Zero-Overhead, Agent-Ready AI Memory Backbone.
Welcome to the Spector documentation β 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.
π₯ Why Spector?
| Metric |
Value |
| π€ MCP Tools |
6 agent-ready tools (semantic, hybrid, RAG, ingest, delete, status) |
| β‘ Vector Search Latency |
0.05 ms avg @ 10K docs (128-dim) |
| π Keyword Search Latency |
0.98 ms avg @ 100K docs |
| 𧬠Hybrid Search Latency |
0.17 ms avg @ 10K docs |
| π Vector Throughput |
18,800 queries/sec @ 10K |
| π§΅ Concurrent Hybrid |
14,000+ ops/sec @ 16 threads (384-dim) |
| ποΈ IVF-PQ + TurboQuant |
8β32Γ memory reduction |
| β
Test Suite |
331+ tests, all passing |
| π¦ Dependencies |
Zero (JDK only) |
πΊοΈ Quick Navigation
π Getting Started
π€ Agent Integration (MCP)
ποΈ Architecture & Concepts
π Reference
π‘ Highlights at a Glance
graph LR
A["π€ AI Agent"] --> B["π‘ MCP Server"]
B --> C["β‘ SpectorEngine"]
C --> D["π§ Hybrid Search"]
D --> E["π― RRF Fusion"]
E --> F["π€ LLM Re-ranking"]
F --> G["β¨ Results"]
H["π Document"] --> I["π§© Chunking"]
I --> J["𧬠Embedding"]
J --> C
π Project Stats
|
|
| Language |
Java 25 |
| License |
Apache 2.0 Β· 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 |
Built with β‘ by Spectrayan Β· GitHub Β· Apache 2.0 Β· BSL 1.1 (memory)