"Information on memory" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Engram is a persistent, long-term memory layer for AI agents and assistants. Claude, ChatGPT, Grok, Cursor and any MCP client share one memory, stored as plain markdown notes: your knowledge base, second brain and AI context in one place. No extraction step: the memory is the note itself, so you can read exactly what your AI remembers and fix it. Edit your memory in Obsidian (real-time sync), the web app, or on your phone. Hybrid keyword + semantic search (RAG over your notes) finds exact strings like error messages, config keys and IDs. Remote MCP server over Streamable HTTP with OAuth 2.1; notes encrypted at rest. Https://engram.page https://youtu.be/rwnPeZ-8Lqo?is=NI-N7BduydGAiZlF https://github.com/engram-app/Engram
Give your agents your team's real data — read the shared graph, propose actions your team approves.
Search and inspect signed scientific claims, methods, observations, artifacts, provenance, contradictions, retractions, and reproducible admission receipts from a shared memory for AI agents.
Patent-pending semantic memory for AI agents: quality-gated writes, conflict tracking. Free trial.
Hosted MCP memory: save sessions/decisions once, search from Claude, Cursor, ChatGPT. EU-hosted FTS.
Persistent memory and knowledge graphs for AI agents. Hybrid search, context checkpoints, and more.
The world's first named AI prompt quality score. Score, optimize, and compare LLM prompts before they hit any model. Free tier available. Built on PEEM, RAGAS, G-Eval, and MT-Bench frameworks. x402-native on Base.
Multilingual YouTube → Knowledge Pack engine. Paste a video URL and get a structured pack — summary, key ideas, glossary, quiz, transcript with timestamps — in Spanish, Portuguese, German, or English. Anonymous endpoint plus OAuth-gated tools for library search, RAG Q&A on a single pack, and Anki export.
Agent-first resource directory for AI agents: protocols, security, RAG, memory, evals, and more.
Historical market memory for AI agents using semantic vector search across years of financial market data. Discover similar market regimes, price patterns, and market context for quantitative research and algorithmic trading.
Shared semantic graph for AI reviews, classification and structured memory across AI assistants.
Read-only hosted MCP over CanonicAI's cited Answers corpus on canonicai.com.
Per-project memory for AI agents: decisions, attempts, tasks, ranked recall. Paid per call via x402.
Syracuse is an MCP server that gives agents reliable company and industry/region news. Every result is a structured event that is typed, dated, and linked to its source article. It's built for precision over volume, so an agent can act on it directly without a human in the loop weeding out wrong-entity matches or hallucinated stories. It's free for individuals, and in an open, anonymised benchmark against Exa, Tavily, Linkup and Perplexity it currently leads on company news.
Cross-vendor AI memory over MCP. One semantic store, readable and writeable from every MCP client.
A high-performance, edge-native Data Refinery Engine built on Cloudflare's serverless AI stack (Workers, Workers AI, D1, KV, Vectorize) designed to continuously ingest unstructured data, refine it into pristine machine-readable structured intelligence, compute semantic diffs, and serve it directly to AI agents via the Model Context Protocol (MCP) and REST APIs.
Collective memory for AI agents. One agent solves a bug — every agent gets the fix instantly.
Market data and web intelligence for AI agents, paid per call in USDC on Base via x402.
Agent-first resource directory for AI agents: protocols, security, RAG, memory, evals, and more.
LLM caching proxy (x402 USDC on Base) - exact + semantic cache. Free health.
