"Using Cline as a Knowledge Graph for Coding" matching MCP servers:

An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.

A knowledge graph MCP server providing persistent, structured memory for AI assistants with multi-agent isolation, tiered search, and index navigation.

Provides a per-person MCP interface to a knowledge graph of legal matters, enforcing OPA-based access barriers and logging every request in a hash-chained audit trail.

MCP server for querying versioned C2PA specification knowledge graphs, enabling AI agents to browse entity definitions, validation rules, and version diffs via natural language.

Enables creating, managing, analyzing, and visualizing knowledge graphs with support for multiple graph types (topology, timelines, changelogs, requirements, knowledge bases, ontologies) including node/edge management and resource association.

An implementation of persistent memory for Claude using a local knowledge graph, allowing the AI to remember information about users across conversations with customizable storage location.

An MCP server for tracking student learning via a knowledge graph, with spaced repetition scheduling and intelligent queries to identify gaps, misconceptions, and optimal next steps.

RAG Knowledge Graph - MCP server providing AI-powered tools and automation by MEOK AI Labs

An embedded knowledge graph in one SQLite file, exposing a MCP server for agents to read and write entities and relationships with full audit trail and time travel.

A persistent memory server that implements a local knowledge graph using the Kuzu embedded database to store entities, relationships, and observations. It enables AI models to maintain structured long-term context through searchable nodes and comprehensive tag-based organization.

Builds and manages a cardiology-focused knowledge graph in Neo4j by extracting medical entities and relationships from documents using LLMs. It enables users to ingest PDFs, refine extracted data, and perform natural language queries to gain clinical insights.

Provides LLM clients with a persistent, scalable knowledge graph memory system that supports semantic retrieval, contextual recall, and temporal awareness.

A lean, local knowledge graph that joins a repo's code to its aSPARK delivery artifacts, enabling agents to trace user stories to code and assess impact of changes, served over MCP.

Enables building and querying vector-based knowledge graphs with node and edge management and semantic search.

An MCP server that gives your agent a persistent project brain: vision, architecture decisions, conventions, roadmaps, and automatic session handoff.

Connects to an embedded Kuzu graph database and provides read-only MCP tools for AI clients to query a knowledge graph.

A TypeScript MCP server for managing persistent knowledge graphs with entities, directional relations, and time-based observations. It enables users to create, search, and track structured information with built-in concurrency control and JSON file storage.

A comprehensive Model Context Protocol server that integrates Vibe Coding methodology with Knowledge Graph technology for AI-assisted software development using Kuzu embedded database.

Enables natural language querying of a football knowledge graph via Neo4j, generating Cypher queries and answers using LLMs, and also provides tools to build the graph from text.

A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats.

A Model Context Protocol server that provides persistent project context management for AI-assisted development, specifically designed for the Cline VSCode Extension.

This MCP server provides persistent memory integration for chat applications by utilizing a local knowledge graph to remember user information across interactions.

Provides a scalable knowledge graph implementation for Model Context Protocol using Elasticsearch, enabling AI models to store and query information with advanced search capabilities, memory-like behavior, and multi-zone architecture.

Enables intelligent exploration of Unreal Engine documentation through a Neo4j-based knowledge graph. Supports concept relationship searches, learning path discovery, and dependency tracking between engine features using bilingual Chinese-English queries.

Self-hosted personal knowledge graph for Claude that persists across sessions, devices, and tools. Built on Neo4j with local semantic embeddings; OAuth 2.1 lets Claude Code, Claude Desktop, and claude.ai web all hit the same graph.

Exposes a Neo4j knowledge-graph index over personal markdown notes to LLM agents via MCP, enabling semantic search, tag navigation, and relationship discovery.

Exposes a dependency graph of strategic sourcing artifacts and analyses as an MCP server, enabling navigation of phases, analyses, deliverables, and graph traversal for impact analysis and build order.

Provides a SQLite-backed MCP server that records agent memory as history, enabling explicit consolidation, source checks, revisions, narrative versions, and accountable forgetting.

Local knowledge engine for codebases with hybrid search, knowledge graph, and interaction tracking, enabling Claude Code to search and interact with project knowledge locally.

Lets an AI assistant search, read, and write notes and sources in your self-hosted Open Notebook, with approval-gated writes and no data sent anywhere else. It bundles tools, prompts, and skills for meeting notes, decision records, weekly reviews, and source-cited research.

Enables Claude Code and other MCP clients to query a local, explainable knowledge graph of a codebase: answering questions, explaining symbols, tracing paths between them, and computing blast-radius impact, with every edge backed by file:line evidence. Read-only and fully offline — no network calls, telemetry, or runtime dependencies.

A local knowledge graph MCP server that provides AI agents with permanent, structured memory about codebases, enabling semantic search, blast radius analysis, and convention enforcement.

A persistent memory implementation using a local knowledge graph that lets Claude remember information about users across conversations.

MCP server for coding-os, a cognitive operating system that gives AI agents memory, structure, and discipline. It exposes tools for project management, task tracking, knowledge graphs, and cognition traces to Claude Code and Codex.

Enables cryptographic chunk hashing, reverse claim-to-source attribution, clearance boundary validation, and provenance audit trails for enterprise knowledge graphs to combat hallucinations.

Exposes a federated, typed knowledge graph to AI clients, letting agents traverse nodes and relationships while scope-based access rights are checked on every hop and provenance is tracked for each fact. This keeps shared knowledge consistent across teams while keeping private and team-scoped content out of reach of unauthorized consumers.

Provides AI coding agents with a local knowledge-graph memory, enabling cross-project retrieval via PageRank diffusion and tools to retrieve, write, extract, update, and view recent knowledge over MCP.

Enables agents to ground claims in enterprise knowledge by hashing source chunks, tracing claims back to their origins, validating clearance boundaries, and maintaining audit trails to support anti-hallucination workflows.

Maps Salesforce metadata into a Neo4j graph database, enabling AI agents to reason about schema and generate accurate SOQL queries.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.