Retrieve recent chat messages from a board card's AI chat to gain context before responding.
MIT
613,999 tools. Updated 2026-09-26 19:00
"Understanding Context Memory in Chat Systems" matching MCP tools:
- List context windows for a project to inspect chat/session-level memory containers, their status, node counts, and update times.Apache 2.0
- Store conversation context in agent memory with automatic importance scoring and embedding, enabling multi-session tracking and memory decay.MIT
- Retrieve relevant memory context to enhance message understanding. Fetches conservative memories with configurable limits on count, characters, and tokens.MIT
- Send a message in a chat session, optionally with context, to get an AI response.MIT
- Retrieve comprehensive context from all memory systems using semantic search to enhance AI assistant capabilities in retaining short-term, long-term, and episodic memory.MIT
Matching MCP Servers
- FlicenseNot gradedqualityNot gradedmaintenanceEnables AI to automatically search, retrieve, and organize your Cursor chat history across sessions. Supports tagging, nicknames, project-scoped search, and full-text search to maintain context between conversations.-
- AlicenseAqualityCmaintenanceA minimal MCP server that exposes Gemini's web and multimodal understanding (video, audio, document, image) through five dedicated tools.51MIT
Matching MCP Connectors
Words-in-context vocabulary practice questions with distractor explanations.
BOLD Systems (Barcode of Life Data System, University of Guelph) — the global DNA barcode…
- Retrieve comprehensive project context including statistics, recent activity, and team information to enable AI understanding.MIT
- Preserve understanding across sessions by saving conversation context, chat summaries, or important knowledge.-
- Create and execute migration plans between different memory systems, validate compatibility, and transfer data from source to target schemas.MIT
- Store facts, decisions, and project context as durable markdown memories with metadata to retain information across chat sessions.MIT
- Reconstruct memory state at a past timestamp to run semantic search queries. Understand how agent context evolved over time.MIT
- Store observations as persistent memories with optional tags, importance levels, context, and auto-expiration to manage AI agent memory.MIT
- List all AI systems in your workspace with registration status and evidence coverage to identify unregistered systems and gaps before the EU AI Act deadline.MIT
- Retrieve recent chat messages from the current project to review discussions and understand conversation context, including sender and timestamps.MIT
- Store important user preferences, project details, and business context for persistent recall across AI agent sessions.ISC
- Chat with Code-Fundi AI to get code-aware answers, including conversation threading, repository knowledge, embeddings memory, and voice mode.MIT
- Send a message in a persistent workspace chat to ask about accumulated findings; replies use real multi-turn history, removing the need to re-explain context each time.MIT
- List the curated Code-Fundi chat model catalog, showing providers, required tier, and context length.MIT
- Retrieve a list of systems in a specified group, returning each system's ID and name.Apache 2.0
- Store memory observations with optional tags, importance ratings, context, and automatic expiration to manage and organize information effectively.MIT
- Clear the stored API key for a named company context to revoke access and remove credentials from server memory.Apache 2.0