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633,500 tools. Updated 2026-10-03 13:59

"Using memory in programming with the Cursor system" matching MCP tools:

  • Discover all users and agents with stored memories and their memory counts to identify system participants before conducting searches.
    MIT
  • List keys in the agent's memory namespace, sorted by newest update. Use prefix filter and cursor pagination to browse metadata before fetching full values.
    MIT
  • Get system overview with OS, CPU, memory, disk, and uptime to monitor system health and performance.
    MIT
  • Track changes to items in a SharePoint default drive using delta queries. Get a cursor on first call, then retrieve only new, modified, or deleted items since that cursor in subsequent calls.
    MIT
  • Search official Zig programming language documentation to find information about language features, standard library functions, memory management, error handling, and build system details.
    MIT
  • Store a memory with optional context metadata.
    MIT

Matching MCP Servers

  • A
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    MCP server that lets an AI analyst place real bets on Binance prediction markets, using Kelly criterion sizing, and tracks its performance through a transparent record of betting slips and outcomes.
    MIT

Matching MCP Connectors

  • Cultural color and colour intelligence API. Every colour anchored to a named person, a documented year, and a consequence. 34 archives spanning literary, cultural, pigment, and national traditions. Ask it what color could get you executed in the Ottoman Empire.

  • Find the safest first AI workflow before investing in AI agents or automation.

  • Retrieve per-host memory usage in GB for a given time window. Default for ambiguous server or system memory questions.
    MIT
  • Collect host system context and development environment details in one call to prepare for coding tasks. Get OS, hardware, locale, and availability of programming tools instantly.
    MIT
  • Execute source code in a sandboxed environment supporting 71 programming languages. Returns stdout, stderr, execution time, and memory usage with CPU/memory limits.
    MIT
  • Fetch prediction markets from supported exchanges using cursor-based pagination. First request caches all markets; subsequent calls use the cached snapshot until expiration.
    MIT
  • Create structured memory blocks with labels like persona, human, or system for organizing information in the Letta system. Link blocks to agents or update content as needed.
    MIT
  • Retrieve paginated event listings from prediction markets using a cursor for efficient multi-page access. Returns compact summaries by default.
    MIT
  • Retrieve and filter memory blocks in the Letta system to manage stored information, with options for pagination, agent-specific searches, and content filtering.
    MIT
  • Saves auto-generated system documentation to persistent memory, enabling AI to recall project structure and business rules in future conversations. Run after code changes to update memory.
    MIT
  • Check memory usage on a remote server using an active SSH session. Returns current memory metrics to monitor system health.
    MIT
  • Retrieve memory system statistics from the Brain-MCP server to monitor short-term and long-term memory usage and performance metrics.
    MIT