"A graph database management system: Neo4j" matching MCP servers:

Enables authenticated, permission-bound read-only queries across registered repositories for inventory, ranking, impact analysis, tracing, and result interpretation.

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 querying a Neo4j knowledge graph built from Git repositories and relational database schemas via MCP, with tools for schema inspection, Cypher queries, and searching code and database entities.

Enables Claude to turn a public or private code repository into an interactive, in-chat graph of its folders, files, classes, functions and API endpoints, including the calls, imports, tests and HTTP requests linking them, which users can pan, search, filter and click through. Provides tools for exploring a node's callers, callees and tests, searching nodes by name, path or docstring, and optionally writing the graph into Neo4j.

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.

Transforms code repositories and development documentation into a queryable Neo4j knowledge graph, enabling AI assistants to perform intelligent code analysis, dependency mapping, impact assessment, and automated documentation generation across 15+ programming languages.

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.

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

Indexes a mono-repo into a knowledge graph and provides MCP tools to query code structure—packages, components, routes, HTTP calls—without file reads or grep round-trips.

Read-only MCP tools for coding agents to audit deployment targets, detect fabricated code, review backlog, database schema, analytics, ML models, architecture docs, and decision lenses.

Enables AI agents to format SQL, explain queries in plain English, analyze schemas, build queries from natural language, and generate migrations, all without requiring a database connection.

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.

Offline PostgreSQL diagnostics: reviews SQL, risky migrations, candidate indexes and EXPLAIN JSON plans without database credentials or executing statements.

A local MCP server for AI coding agents that builds a queryable knowledge graph of files and symbols, enforces edit scope before file writes, and records append-only reasoning logs to explain changes.

Enables exploring a C++17 coroutine and device-domain call graph through MCP tools, providing symbol search, caller/callee queries, and neighborhood exploration of coroutine-aware codebases.

Enables coding agents to query a deterministic AST knowledge graph of a codebase over MCP—finding symbols, callers/callees, dependencies, impact, and relevant tests via compact path:line JSON—so they can navigate code without grepping, embeddings, or an LLM.

A comprehensive MCP server that provides a graph database for tracking software codebase components, their relationships, and associated tasks/goals.

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.

Enables AI agents to create, validate, and export UML system models using structured MSON format. Supports generating PlantUML and Mermaid diagrams with direct export to System Designer macOS application.

A local MCP server that indexes codebases into Neo4j and provides tools for code analysis, dependency visualization, and impact assessment.

Enables AI coding assistants to query a persistent local code graph for targeted context, blast-radius analysis, and incremental updates, so they read only relevant files during reviews and large-repo workflows.

Enables querying a TypeScript codebase's graph for call flows, type relationships, and symbol locations without reading file bodies.

A function-level call-graph indexer for GDScript/Godot projects, exposed as an MCP server so AI coding assistants can answer questions like 'what calls this function?' or 'what would break if I change this signal?' without re-reading the whole codebase.

Enables Claude Code to query a TypeScript dependency graph and retrieve the minimal set of files needed for code review, implementation, or debugging.

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.

A TypeScript code graph tool with MCP integration that enables AI agents to perform semantic search and graph traversal (call graphs, paths between symbols) across a codebase.

Turns a codebase into a queryable graph with semantic search, call graphs, and control/data flow analysis, served to AI coding agents via the Model Context Protocol.

Builds rich code graphs from TypeScript/NestJS codebases using AST analysis and Neo4j, enabling semantic search, natural language querying, and intelligent graph traversal to provide deep contextual understanding of code relationships and dependencies.

Serves approved lessons learned from past corrections to coding agents, delivering task context and file-scoped lessons before work starts and checking finished work against them before the agent declares done. It also exposes module facts, dependency impact, and past misses tied to specific files.

Provides structured instructions to Cursor for generating comprehensive system summaries of Node.js/TypeScript codebases.