"Code Review Graph Visualization Tools and Resources" matching MCP servers:

A high-performance code knowledge graph server implementing MCP, indexing codebases into a structured AST knowledge graph with semantic search, call graph traversal, and HTTP route tracing.

MCP server for indexing source code from repositories into a Neo4j graph database and enabling Graph RAG-based search and traversal of functions via natural language queries.

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

Knowledge graph for token-efficient code reviews. Builds a structural map of your codebase with Tree-sitter, tracks changes incrementally, and gives AI agents precise context via MCP tools. Features fixed multi-word search, qualified call resolution, dual-mode embedding (ONNX local + LiteLLM cloud), and output pagination.

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 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.

A knowledge graph MCP server that indexes your codebase into a local SQLite graph and provides tools for project mapping, file summaries, and impact analysis, drastically reducing token usage in AI coding assistants.

A local knowledge graph of your codebase for Claude Code on macOS, exposing structural data via MCP tools for querying calls, imports, test coverage, and impact analysis.

Enables agents to route spoken requests to the right project on the right machine and to remember the outcome by reading and writing a FalkorDB graph, so learned aliases, clarification answers, and episodes carry over across sessions. Exposes five fixed, validated graph tools — route_request, whats_running, machine_blast_radius, project_history, and why_heard — each answering with its MATCH path, Cypher, and parameters, and reporting not-in-graph or ambiguous names distinctly instead of guessing.

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.

Structural graph map of any codebase. Scans entities, relationships, and feature flows across 13 languages so LLMs navigate by structure instead of reading everything.

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

A self-contained, in-memory graph database for AI Agents. Provides semantic code understanding through the Model Context Protocol (MCP).

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.

Enables an engineering assistant to persist and query local CAD review context—named features, notes, tags, and revision-bound decisions with their requirements and evidence—in SQLite by artifact, entity, text, or tag, marking records stale against a caller-supplied revision. It never opens the CAD file, so it works on a laptop with no CAD software or other server running.

Local-first memory for Claude Code and any MCP client: hybrid vector + keyword search and a bi-temporal knowledge graph in one SQLite file. Local embeddings, no API key, $0/token.

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 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 AI agents to navigate, search, and rank notes in an Obsidian vault using graph relationships, providing context-aware access to knowledge without exposing raw file contents.

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