"Temporal" matching MCP servers:

Enables AI assistants to manage Temporal workflows, schedules, and workflow executions through a standardized interface.

Calendar MCP server with atomic booking, conflict prevention, deterministic RRULE expansion, and TOON token compression for AI agents.

Provides human-like memory dynamics for AI assistants where memories naturally fade over time unless reinforced through use, mimicking the Ebbinghaus forgetting curve. Enables automatic saving, searching, and management of contextual information with temporal decay algorithms.

Persistent 4-tier AI memory (episodic, semantic, project, procedural) with temporal scoring, contradiction detection, entity tracking, and real-time desktop visualization orb.

Memento is a local-first, open-source MCP middleware that gives AI agents persistent memory, proactive goal enforcement, and autonomous intelligence using a SQLite temporal graph with Reciprocal Rank Fusion retrieval.

OpenKai is an open-source MCP server that gives AI agents persistent memory across conversations, supporting core, long-term, short-term, episodic, and working memory types with goals, emotional intelligence, and temporal queries.

Persistent memory system for AI agents that records episodic memories with care-weighting and emotional valence, and provides full-text search with temporal chaining and automatic consolidation.

Local-first memory kernel for coding agents that provides a shared, auditable, graph-backed long-term memory layer with features like write preview, temporal recall, and provenance explanations.

Exposes MCP tools that start, query, signal and approve durable Temporal workflows which diagnose and remediate broken Kubernetes pods, so a crashed or restarted server simply re-attaches to the same deterministic heal instead of losing state or applying a fix twice.

A local-first persistent memory server that uses Voronoi partitioning and temporal intelligence to provide LLMs with long-term context across different sessions and clients. It features automatic drift detection to prevent hallucinations by identifying and penalizing outdated information as project requirements evolve.

Enables sleeping agents to monitor multiple event sources and wake only when durable composite or temporal conditions are met, supporting derived events and targeted wakeups without keeping an agent loop alive.

Long-term memory for AI agents over MCP — episodic + semantic memory, a temporal knowledge graph, and a dialectic user model, exposed as 32 tools (recall, remember, context, graph, dreaming, peers). Zero dependencies, runs fully offline; leads the LoCoMo benchmark at ~35x fewer LLM calls.

Persistent AI memory MCP server with 4-channel retrieval (semantic, BM25, entity graph, temporal). 74.8% on LoCoMo benchmark with zero cloud dependency. Works with Claude, Cursor, VS Code Copilot, and 17+ AI tools. EU AI Act compliant. MIT license.

Provides real-time temporal drift to SOUL.md agent identities, enabling agents to check their current behavioral state through tools like get_daily_drift.

This server enables Temporal Workflows and other MCP clients to call tools implemented as Temporal Nexus operations, and to proxy upstream MCP servers so every upstream call runs in a standalone Temporal activity.

AI Constraint Engine that enforces CLAUDE.md, .cursorrules, and AGENTS.md rules as laws. 51 MCP tools for semantic conflict detection, patch review, drift scoring, pre-commit hooks, and Guardian Mode. Catches euphemisms, temporal evasion, and hidden violations that keyword matching misses.

MCP server enabling AI agents to enforce corrected rules as durable pre-output checks, manage processed memory, and query a temporal knowledge graph.

Enables AI agents to have persistent, self-managing memory with bi-temporal supersession, timely forgetting, and recall under a limited context window, using MCP protocol.

Enables AI agents to store, query, and trace a time-aware memory graph of nodes and edges in a single SQLite file, supporting weighted recall, temporal queries, and provenance-aware writes over MCP.

Provides AI agents with persistent, searchable memory using a knowledge graph stored in SQLite. Features semantic search, temporal awareness, and workflow-aware prompts for development projects.