リモート MCP server

Provides memory infrastructure for stateful agents to store, reason over, and query conversations, events, and peer representations.

Provides shared graph-based memory for AI agents using a local Postgres database to store and recall facts without calling an LLM for writes.

Lets an AI agent store, recall, and calibrate persistent memories, search indexed documents, and report outcomes.

Provides persistent AI memory using hybrid search, temporal knowledge graphs, and automated entity extraction to enhance agent context.

Lets AI agents log conversation exchanges and recall persistent memory context through MCP tools.

Lets AI agents save, inspect, correct and forget memories across sessions, keeping a Source Receipt for each one.

Stores and retrieves long-term memories across AI clients, with feedback-driven re-ranking and shared rooms for multiple agents.

Provides long-term memory for AI agents using hybrid vector and full-text recall with support for rooms and time-travel.

Provides persistent, governed long-term memory and session continuity for AI agents across different tools and sessions.

Gives AI clients durable graph and vector memory so they can recall and store context across conversations.

Provides AI assistants with local-first graph memory using SQLite and semantic search to recall, connect, and learn from long-term context.

Gives AI clients one shared long-term memory to search, read the user profile, and add facts and documents.

Gives AI clients one shared long-term memory to add facts and documents, search past context, read the user profile, and ask questions.

Lets AI agents search your code, recall saved team decisions, and reuse project context across sessions and tools, with cited sources.

Provides long-term bitemporal memory for AI agents using a knowledge graph with provenance and cited answers.

Lets AI agents search and remember your self-hosted documents, tickets and code with hybrid search and persistent memory.

Provides persistent memory and behavioral drift detection to help AI agents maintain identity and context across sessions.

Provides an agent-agnostic memory backend that preserves continuity between humans and AI using streamable HTTP transport.

Provides AI agents with a persistent memory layer and virtual filesystem to read, search, and update project context.

Gives AI agents semantic, episodic, and procedural memory that persists across sessions and learns from failed workflows.