"Neo4j memory configuration and management" matching MCP servers:

An MCP server that enables LLMs to perform semantic and fulltext searches within Neo4j while executing complex, search-augmented Cypher queries for GraphRAG applications. It provides tools for database schema discovery and supports multi-provider embeddings to facilitate advanced graph traversals.

MCP server for Neo4j that provides abstract graph operations for LLMs, enabling safe and consistent interaction with Neo4j databases through tools like search, insert, update, delete, and schema introspection.

A Model Context Protocol server that enables running Cypher queries and retrieving schema from Neo4j databases, supporting AI-driven graph exploration and text-to-Cypher workflows.

A single local MCP gateway for Neo4j that exposes both proxied generic Neo4j tools (schema, Cypher, GDS) and custom YAML-defined use-case tools behind one stdio endpoint.

A local, read-only MCP server (plus CLI) over your own stock/ETF transaction log. A deterministic core computes drawdown-first risk with bootstrap confidence intervals and validates targets with walk-forward verdicts. The assistant narrates, but the number fence makes it structurally impossible for the model to produce a figure.

Exposes employee leave-management operations (add employees, check balance, apply/cancel leave, view history) as MCP tools for AI clients like Claude Desktop to call directly.

Enables AI assistants to use Neo4j knowledge graphs and Qdrant vector databases for hybrid reasoning, combining structured facts with semantic search for advanced knowledge management, research analysis, and standardized coding workflows.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

Connects AI assistants to your n8n instance to manage workflows, executions, credentials, and user settings through 31 specialized tools. It enables users to perform n8n operations like workflow creation, activation, and execution history retrieval via natural language.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Manage Job using MCP: Manage Job, Candidates, Resumes, Salaries all within this one MCP tools It can solve problems like: You have 50 resumes to screen. Your AI assistant can reason about candidates, but it can't: Read PDFs/DOCX — The AI can't open binary files Extract structured data — Copy-pasting loses formatting, metrics, and context Compare at scale — No consistent scoring across candida

Provides persistent memory for Claude with hierarchical categorization, cross-corpus recall, session journals, and customizable persona, enabling memory continuity across sessions.

Enables managing employee leave through natural language, including applying, approving, rejecting, and canceling leave, checking balances, and listing requests, using an in-memory data model.

Enables managing employee leave records through natural language, including adding employees, listing employees, adding/deleting leave entries, and viewing leave history.

Enables managing employee leave requests (apply, view, list leaves) through Claude desktop using natural language.

Enables natural language leave management, allowing users to check leave balances, apply for leave, and retrieve leave history via MCP tools.

Hosted memory for AI agents that learns from outcomes, with shared rooms. One key across Claude, Cursor & ChatGPT.

MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.

Embedded, local-first agent memory: facts extracted into a per-namespace SQLite file (vec0 + FTS5) with hybrid retrieval and point-in-time (time-travel) queries. ADD-only history over stdio — no server process, no cloud dependency.

MCP server providing persistent memory for AI applications, enabling Claude to store and recall memories with hybrid search and knowledge graph.