#knowledge-graph

Knowledge graph data structures

Turn any markdown vault or codebase into a cited, AI-queryable knowledge graph. Local-first CLI, web viewer, and MCP server.

Turn PDF, DOCX, tables, and figures into citation-ready reusable agent assets and Foam/LightRAG wikis — MCP SDK 2 server plus VS Code extension

Local-first, inspectable memory for coding agents: durable context across sessions and repositories, code-aware recall, bi-temporal history, MCP, and a self-hosted WebUI.

Go SDK for Dakera AI agent memory — self-hosted, 88.2% LoCoMo. Vectors, hybrid search, knowledge graphs, sessions.

Persistent memory MCP for AI agents — SQLite, knowledge graph, 13-tool Python MCP + 17-tool BrainBar surface with ToolAnnotations

Tablassert turns biomedical spreadsheets (Excel, CSV, TSV) into knowledge graphs ready for NCATS Translator. Declare how your columns map to subject–predicate–object statements in YAML; Tablassert resolves free text to standard CURIEs, attaches provenance and statistical annotations, and emits KGX-compliant nodes and edges.

Write once. Generate everything. A modular, open-source ecosystem for building durable, observable, multimodal AI systems. Text, voice, image, video, music — one unified interface, any provider, any model, local or cloud.

Autonomous Claude Code orchestration with persistent memory, self-coordinating agent orgs, and a codebase knowledge graph.

A cognition aware database engine for AI agent memory. Purpose built in Rust with WAL, HNSW, knowledge graphs, and speculative context pre assembly. Not a wrapper, a ground up storage engine that thinks.

AST knowledge graph MCP server for Claude Code — semantic search, call graph traversal, HTTP route tracing, impact analysis. Auto-indexes 10 languages via Tree-sitter.

Memory security for AI agents. Scan native memory writes, gate tools on bound hosts, inspect what was stored. Not a second brain.

A SQLite extension that adds graph database capabilities with Cypher query language support and built-in graph algorithms.

Agent coordination MCP server — shared blackboard, decision tracking, and context assembly

A fast, cross-platform build system and task orchestrator for polyglot monorepos. One statically linked Go binary, config as code, no second toolchain to install.

DE-centralized - MARKdown - for US: Persistent memory for AI agents, shared knowledge for teams, and a second brain for you. Built on the Mark Protocol.

Shared, persistent memory for AI assistants, built on the Zettelkasten method

A local context layer for AI tools: mirror your repositories, index them into a knowledge graph, and serve it over MCP so agents answer from real source instead of guessing.

Markdown filesystem for agents and teams.

Persistent memory & code intelligence server for AI coding agents. Deploy on VPS for shared memory across machines. Hybrid search (BM25 + pgvector), knowledge graph, impact analysis. 14 MCP tools. Works with Claude Code, OpenCode, Cursor, and any MCP client.

Vendor-neutral Go CLI for the Open Knowledge Format. Create, validate, lint, index, search, and graph OKF bundles. Built to be driven by AI agents.

RushDB is a graph + vector database and memory layer for AI agents. Push any JSON, get typed, searchable, relationship-aware records back — no schema, no migrations. Built on Neo4j.

QNTX = Experiential ꩜ Learning ⌬ System ≡ Attestation +

The governance layer for LLM-maintained Markdown wikis.

Persistent memory MCP server for AI agents — Rust, 19 tools, knowledge graph, Hebbian learning, episodic memory, contradiction detection, prospective triggers, Bayesian calibration, zero-config Docker setup.

PDBe MCP Servers integrate Protein Data Bank Europe resources with LLMs via Model Context Protocol. Provides seamless access to protein structure data through API tools and graph database schema assistance for intelligent Cypher query generation, bridging structural biology and AI research.

Mission working memory for LLMs: named session graph (GQL) — cue, bounded pin_map, gated mutate. Not chat SSOT, not RAG/GraphRAG, not a DB proxy.

A lightweight knowledge system for small‑and‑medium teams tailored to AI Agents. It compiles Feishu Docs, local Markdown, code structures and curated business data into structured, traceable knowledge, guiding Agents to retrieve high‑quality content via pattern‑driven reasoning and exploration.