"A server implementing NFS (Network File System) with MCP (Model Context Protocol)" matching MCP servers:

An agentic file-system assistant that lets users read, write, list, and search local files through natural language, using a LangChain agent with an Ollama LLM backed by a FastMCP server.

A server exposing intelligent tools for enhancing RAG applications with entity extraction, query refinement, and relevance checking capabilities.

An event-driven MCP server that enables agents to share context streams, publish and subscribe to events, manage tasks, and follow protocols, keeping a fleet of agents mutually context-aware in real time.

A server built with mcp-framework that allows users to extend Claude's capabilities by adding custom tools that can be used through the Claude Desktop client.

A unified API server that enables interaction with multiple AI model providers like Anthropic and OpenAI through a consistent interface, supporting chat completions, tool calling, and context handling.

A stateful gateway server for AI applications that solves the memory limitations of Large Language Models by maintaining separate conversation contexts for each user.

A conversational application server that integrates LLM capabilities via Ollama with vector memory context, supporting multiple users, sessions, automatic history summarization, and a plugin system for executing real actions.

This server facilitates the invocation of AI models from providers like Anthropic, OpenAI, and Groq, enabling users to manage and configure large language model interactions seamlessly.

An MCP server providing access to Telos, a philosophical AI mentor that combines rationalist thinking with stoic philosophy to offer personalized guidance and smart contract accountability on Solana.

A server that implements the Model Context Protocol for Schwab API, allowing access to account information, positions, stock quotes, and order/transaction history designed for integration with Large Language Models.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Multi-agent swarm orchestrator for AI workflows. Exposes blackboard read/write, agent dispatch, permission gating (AuthGuardian), token budget enforcement (FederatedBudget), and audit log tools over MCP. Supports 14 AI framework adapters including LangChain, AutoGen, CrewAI, Codex, and A2A — mix any frameworks in one swarm with race-condition-safe shared state.(Traffic light for agents)

Local MCP server for Bind Protocol — credential parsing, verification, and hashing tools for AI agents.

Enables network discovery, port scanning, and infrastructure monitoring with device detection, service fingerprinting, and cluster health checks for autonomous AI systems.

A drop-in MCP server implementation for Next.js projects using Vercel MCP Adapter, allowing developers to integrate model context protocol functionality with custom tools, prompts, and resources.

An educational project that deliberately implements vulnerable MCP servers to demonstrate various security risks like prompt injection, tool poisoning, and code execution for training security researchers and AI safety professionals.

Local-first shared memory and coordination layer for AI coding agents, with repository evidence, reservations, handoffs, code graph context, and dashboard review backed by PostgreSQL/pgvector.

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

Trust, identity, and reputation infrastructure for AI agents. Register agents with W3C DID (Ed25519), check EigenTrust reputation scores, submit peer attestations, search agents by capability, and verify IPFS-anchored audit trails. 11 tools.

Reduces Claude's context window costs by automatically summarizing inactive files to their public interfaces using AST parsing, keeping only the full contents of the currently active file.