Vector Search

97-domain knowledge graphs for AI agents — 4× F1 of RAG, 11× fewer tokens. MCP-native.

Persistent knowledge system with OWL-RL reasoning and 22 MCP tools. Local-first.

Productivity-boosting RAG engine for codebases with multi-provider AI support and semantic search.

One shared, durable memory for your AI coding agents — local-first, zero-dependency.

MCP web search + tiered web fetch for AI agents (Exa, Firecrawl), SSRF-guarded, cross-platform.

Serves coding agents one canonical doc per query instead of rereading the repo — ~60% fewer tokens.

Long-term and multimodal memory for AI agents - character-aware, mem0-compatible, fully-local option

Deterministic ebook-to-markdown pipeline with MCP tools to browse, search, and read your books.

Embedded, local-first agent memory: one SQLite file per namespace, no server, no cloud.

Persistent memory for AI agents - hybrid semantic + keyword recall with autonomous consolidation

Local multi-client RAG server over the Model Context Protocol.

Local research agent that verifies its own answers. Runs on Gemma 3 4B + Ollama, $0/query.

MCP memory server for AI coding assistants. Windows Service, ONNX embeddings, SQLite vector search.

Graph-backed session memory for LLMs: checkpoint, resume, file analysis, token-savings stats.

Embedded, local-first memory and retrieval for AI agents. One SQLite file, no server, no API key.

MCP server for the Qiskit Code Assistant intelligent code completion

One tool for AI agents to scrape, crawl, extract, map, and search the web. Self-hosted, no API keys.

Semantic knowledge engine for Obsidian with auto-classification and DAG hierarchy

Authority-weighted memory graph for AI agents with conflict detection and semantic search.

Local-first MCP sidecar for Markdown artifacts, review intents, and supervised knowledge growth.