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668,750 tools. Updated 2026-10-17 07:23

"Context Memory Systems and Technologies" matching MCP tools:

  • Find lab systems by hardware attributes and ownership. Filter by CPU, memory, architecture, hostname, owner, or pool to identify matching machines.
    MIT
  • Search company context across Yonote index and source systems to retrieve relevant internal information for a query.
    Apache 2.0
  • 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
  • Update project context including current projects, technologies used, goals, challenges, team size, and methodology for AI memory storage.
    -
  • Create and execute migration plans between different memory systems, validate compatibility, and transfer data from source to target schemas.
    MIT
  • List tacit memory metadata to know covered situations and context fields for retrieve_guidance, without returning guidance text.
    Apache 2.0

Matching MCP Servers

  • A
    license
    Not graded
    quality
    D
    maintenance
    Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.
    1
    GPL 3.0
  • F
    license
    A
    quality
    C
    maintenance
    A 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.
    3
    -

Matching MCP Connectors

  • Encrypted long-term memory shared across your AI assistants (Claude, ChatGPT, Perplexity).

  • BOLD Systems (Barcode of Life Data System, University of Guelph) — the global DNA barcode…

  • List all accessible context spaces, including owned and shared, with each space's memory count.
    MIT
  • Load persistent memory first in every conversation to retrieve hot topics, active context, and protocols. Pass project to prioritize relevant neurons; skipping loses context.
    MIT
  • Fetch memory-enriched context and coherence guidance for the incoming user message before replying, receiving an allowed indicator and turn token to record the answer.
    MIT
  • List all accessible context spaces with their memory counts, including those you own and those shared with you.
    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
  • Store memory observations with optional tags, importance ratings, context, and automatic expiration to manage and organize information effectively.
    MIT
  • Get a snapshot of current memory context, including recent memories, stats, and audit activity, to quickly see what your agent knows right now.
    MIT
  • Retrieve stored agent context, trade lessons, regime history, and signal-quality scores. Filter by prefix to isolate relevant memory and support trading decisions.
    MIT