"PlayStation Portable" matching MCP servers:

Enables AI agents to search, fetch, and apply portable engineering standards over MCP, keyless and offline.

Enables AI agents to share a portable, user-level memory layer through MCP, allowing them to store, search, update, link, and consolidate facts with optional full-text and vector retrieval.

Enables read-only access to a local-first catalog of portable agent skills, exposing tools to discover ranked matches, inspect stored artifacts, traverse declared relationships, and view configuration.

Enables users to create and control portable, user-owned memory archives, including saving memories, reflections, values, and stories, exporting them as open JSON, publishing or discovering public archives, and loading consented material as a clearly-labelled memory-based AI persona.

Portable, provider-agnostic memory for AI agents using Azure Data Explorer (Kusto) with temporal and semantic scoring.

MCP server that provides a portable personal knowledge layer for AI tools, enabling cross-LLM continuity and personalized context across clients like Claude, ChatGPT, and Cursor.

A local MCP server that gives AI copilots a shared, portable long-term memory backed by an embedded knowledge graph, with semantic search and export/import capabilities.

Centralized repository for modular, portable skills and memory, enabling AI agents and IDEs to access personalized tools and memory via stdio or SSE transport.

A portable self-hosted memory layer for AI tools, storing context, memories, and handoffs for access from any MCP-compatible client.

Local-first, MCP-first cross-agent cognitive asset layer that enables agents to store, retrieve, govern, and migrate memory, roles, and verified skills as portable assets via MCP tools and SQLite.

An MCP server aimed to be portable, local, easy and convenient to support semantic/graph based retrieval of txtai "all in one" embeddings database. Any txtai embeddings db in tar.gz form can be loaded

FEGIS is a Model Context Protocol server that gives LLMs structured, persistent and portable memory through customizable cognitive tools defined in schema.

Enables AI agents to maintain persistent personal memory and portable skills across MCP-compliant clients, with hybrid semantic recall and deterministic SQL analytics.

Provides AI-powered code intelligence for any codebase using local LLMs and vector search, enabling semantic code search, pattern analysis, and context-optimized code generation with 90% token savings.