"Exposing an MCP server via a public tunnel with mcp-proxy" matching MCP servers:

Enables routing context and execution across AI tools like Claude, Cursor, Windsurf, and ChatGPT with a shared memory, task board, and context bus, plus local file conversion.

Enables AI harnesses to maintain a persistent memory layer backed by a local SQLite file, providing MCP tools to add, search, deprecate, and synchronize facts without deleting history.

MCP server for memory storage, encryption, search, and group sharing, used by Claude Code via the cordelia-agent-sdk.

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.

A task-aware transparent proxy that wraps stdio MCP servers (such as git, filesystem, and terminal) and compresses large tool outputs field-by-field using declarative YAML profiles, passing narrow intent queries through untouched. Discarded data is stored in SQLite and can be losslessly retrieved via an injected tool, either in full, by line range, or by grep, while errors are always preserved and failures fall back to the raw result.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

A local proxy that enables ChatGPT to access an Obsidian vault through the Obsidian Local REST API by tunneling via ngrok and adding the API key header.

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.

Metis — an open-source (AGPL-3.0), local-first MCP server / research companion. It answers from the user's own indexed PDF library with page-level citations (and flags what it can't find rather than inventing), keeps all data on the user's machine, and routes requests to 34 specialist agents.

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

Enables AI agents to maintain persistent, searchable two-layer memory with 37 tools, hybrid search, knowledge graphs, and enterprise features like authentication and backups.

Memory bank with Server as SSH support for central knowledge base

Enables chat with multiple LLM providers (OpenAI and Anthropic) while maintaining persistent conversation memory. Provides extensible tool framework for various operations including echo functionality and conversation storage/retrieval.

Enables AI coding agents to retain and recall project context across sessions through local Markdown storage and hybrid keyword/semantic retrieval, including reusable knowledge cards. It runs offline as a daemon and integrates with MCP-compatible IDEs to continue long-running work without re-explaining decisions or architecture.

Project management and session memory for AI agents that provides 13 tools for tracking projects, tasks, and context during AI coding sessions.

Enables insurance claims review assistance by querying a knowledge graph of Korean standard insurance terms, restoring applicable policy versions by enrollment date, and returning coverage/exclusion determinations with cited provisions.

Connects Claude and ChatGPT to a marketplace of AI specialist packages, letting assistants discover and purchase on-chain licenses, activate them, then run each package's method step by step. It also exposes knowledge-base search, templates, persistent memory, tool execution, and deliverable submission with sandbox verification.

Bridges Grok CLI to an OpenViking context database over MCP, enabling memory and code tools like recall, search, and resource management.

Enables querying PDF documents using natural language with grounded answers and source citations via a local RAG pipeline.

Connects AI assistants to Obsidian vaults via the Local REST API to search notes, retrieve content, and perform semantic searches. It features self-healing multi-URL connectivity and supports both stdio and HTTP transports for flexible deployment.

MCP server for alive-analysis. Query, search, and retrieve structured analysis history written with the ALIVE loop (Ask→Look→Investigate→Voice→Evolve), plus dashboard JSON export.

Proxies MCP protocol to JSON-RPC for 1C:Enterprise IT management system, enabling AI agents to manage tasks, projects, knowledge base, and files.

MCP server for integrating LightRAG with AI tools. Provides a unified interface for interacting with LightRAG API through the MCP protocol.

This MCP server enables AI agents to manage artifacts across sessions by providing tools for searching, retrieving, and registering entries in a persistent ledger, ensuring consistency and traceability of agent outputs.

Facilitates knowledge graph representation with semantic search using Qdrant, supporting OpenAI embeddings for semantic similarity and robust HTTPS integration with file-based graph persistence.

A secure multi-tenant MCP proxy that exposes 81 tools for full CRUD, search, chat, podcast, and command management on the OpenNotebook API, enabling natural language interaction with notebooks, notes, sources, and more.

Enables a simulated Alexa+ care companion to capture daily check-ins, recall longitudinal care-journal history, assess risk, create local family-inbox cards, schedule follow-ups, and produce weekly digests through MCP tools.

A local-first, privacy-preserving centralized memory hub for AI agents — MCP-compatible, zero cloud egress.

A local-first RAG system that indexes personal documents and enables querying them via an MCP tool, keeping data private with local embeddings.

Memtrace is a persistent memory layer for coding agents, built as a bi‑temporal structural knowledge graph over your codebase (AST‑driven symbols and relationships, plus temporal evolution and cross‑service API topology)