"Information About Persistent Memory" matching MCP servers:

An MCP server that provides information about Utkarsh, including bio, skills, work experience, and portfolio projects, accessible via local stdio or remote HTTP with OAuth.

An MCP (Model Context Protocol) server that gives AI agents live, structured ad intelligence across Facebook, Google, and Instagram — data that no base model can produce from training alone. Powered by Apify actors. Works with any MCP-compatible client: Cursor, Claude, etc.

Persistent AI memory with SQLite hybrid search (FTS5 + semantic), built-in Qwen3 embedding, and rclone sync across machines.

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

Provides persistent memory for AI agents using hybrid search (vector embeddings + BM25) with neural reranking, enabling storage and retrieval of insights, debugging solutions, and patterns across coding sessions.

Gives AI coding agents persistent, evolving knowledge about a codebase, enabling them to store and retrieve observations about architecture, conventions, gotchas, and recent work context.

A different approach from typical persistent-memory MCPs. Instead of a local SQLite + embeddings store, the memory lives as plain files in a .ai-memory/ directory you commit to your repo (facts.jsonl, decisions/\*.md, gotchas.md). Git is the sync layer — what one Claude/Cursor/Cline learns about a repo, the next session (or a teammate's agent) picks up automatically. 5 MCP tools: get_rep

Persistent knowledge graph MCP server with SQLite backend, offering graph traversal, fuzzy search, and temporal queries for entities and relations. It serves as a drop-in replacement for the npm mcp-server-memory with enhanced capabilities.

Enables agents to manage persistent long-term memory through MCP tools for searching, adding, updating, giving feedback, and forgetting memories, with automated pipelines for redaction, distillation, and reconciliation.

A zero-dependency, file-based persistent memory system for AI agents with tiered memory, Ebbinghaus decay, and keyword retrieval.

Persistent memory and payment safety for AI agents on Lightning. Enables agents to remember purchases, track vendor reputations, enforce budgets, and share trust signals via Nostr.

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

Two-layer memory for AI agents. Episodes compress into identity. The only MCP memory server with an immune system. Patterns earn permanence through evidence, false knowledge gets caught and demoted, and stale information fades — so your agent's memory gets smarter over time, not just bigger. Zero dependencies. 5 tools. Works with any MCP client.

Provides AI agents with persistent, long-term memory via OKF-formatted markdown and SQLite indexing, enabling stateful storage, retrieval, and search across sessions.

MCP server for persistent, cross-session, local-first memory for AI agents, storing memories as Markdown files with SQLite indexing for hybrid search.

Provides persistent memory with semantic search for MCP-based AI agents, enabling them to store and recall information across sessions using vector embeddings.

Enables AI agents to record and rank learnings, facts, and methods through a collaborative voting framework. It provides tools for agents to surface the most useful information across sessions using persistent memory storage.

A persistent memory MCP server for Claude Code that automatically saves conversations and retrieves relevant history across sessions to provide context.

Local-first persistent memory layer for MCP agents with hybrid search, file ingestion, and GDPR compliance.

Local-first, governable long-term memory for AI agents. Provides SQLite-backed storage, cross-session recall, and traceable memory corrections through a standard MCP interface.