Retrieve recent chat messages from a board card's AI chat to gain context before responding.
MIT
307,785 tools. Last updated 2026-07-28 05:04
"Understanding Context Memory in Chat Systems" matching MCP tools:
- Search Beaker systems by CPU, architecture, memory, pool, and owner. Combine filters with AND logic to find matching systems.MIT
- Send a message in a chat session, optionally with context, to get an AI response.MIT
- Store facts, decisions, and project context as durable markdown memories with metadata to retain information across chat sessions.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
- Add new observations to an existing entity in a knowledge graph memory. Append facts like 'Lives in Seattle' to a person or project, with optional context and location settings.MIT
Matching MCP Servers
- Flicense-quality-maintenanceEnables 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.Last updated
- Flicense-qualityCmaintenanceA local semantic memory and code-indexer that uses AST parsing for structural understanding and persists architectural decisions to help AI assistants bypass context window limits.Last updated
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- List all accessible context spaces, including owned and shared, with each space's memory count.MIT
- Recover context from past chat sessions by reading recent history entries, including decisions, notes, and phase markers. Filter results by session, entry type, or count.MIT
- Reconstruct memory state at a past timestamp to run semantic search queries. Understand how agent context evolved over time.MIT
- Retrieve available agents for recruitment into chat rooms, optionally excluding those already in a specific chat.MIT
- List memory subjects with per-subject episode and memory counts to find subject IDs for use with other tools. Supports pagination via limit and offset.Apache 2.0
- Retrieve the latest chat messages from your project's chat room to review conversation context and what has been discussed.MIT
- Store observations as persistent memories with optional tags, importance levels, context, and auto-expiration to manage AI agent memory.MIT
- Answer conversational questions using prior chat history and context to shape retrieval and synthesis.MIT
- Retrieve the complete conversation context for an agent, including all its messages and @mentions, to resume execution from a given chat room.MIT
- Store important user preferences, project details, and business context for persistent recall across AI agent sessions.ISC
- Deploy files directly to Cloud Run by providing their contents in a chat context. Specify filenames and content for quick deployment without local file storage.Apache 2.0
- Return compact operating memory for AI agents to reload after session restart or context compaction, keeping Axint's rules accessible without rereading full documentation.Apache 2.0
- 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