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458,064 tools. Updated 2026-08-14 21:02

"Information about memory banks" matching MCP tools:

  • Save durable information for future recall; skip transient chat. Existing Projects paths attach automatically. create_project is a deprecated ordinary-client compatibility input; model-routed project creation belongs to project(entity='project', action='create'). Use Ledger, not generic memory, for financial records.
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  • Returns Fluentive's security, privacy, and compliance information. Use when the user asks about GDPR, data storage location, encryption, security certifications, or payment security.
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  • Store a long-term memory about the household. Use sparingly for durable preferences, routines, constraints, or insights worth recalling in a future conversation. Recall first to avoid duplicates.
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  • Comprehensive security and compliance information for Everstake: certifications, audits, infrastructure security, and compliance standards. Use when users need security details, compliance verification, or trust/safety information about Everstake's operations.
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  • Get detailed information about a specific ad request, including pool selections if targeting mode is manual.
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  • Work out which Nigerian banks a 10-digit NUBAN account number could belong to. The CBN check digit is computed from the bank code plus the first nine digits, so testing the number against every bank code narrows a shortlist without contacting any bank. Typically reduces ~30 banks to ~3. This confirms checksum validity only: it does NOT confirm the account exists, and it never returns the account holder's name, which requires a licensed NIBSS account-name enquiry.
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Matching MCP Servers

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    Memory Bank Server provides a set of tools and resources for AI assistants to interact with Memory Banks. Memory Banks are structured repositories of information that help maintain context and track progress across multiple sessions.
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Matching MCP Connectors

  • Cross-session, cross-device memory for your agent: remember and recall notes. No key to start.

  • Persistent semantic memory for AI agents: store and recall text by meaning (RAG). x402

  • Save a durable fact or PREFERENCE about the brand, audience, or the user’s creative TASTE (e.g. “audience is first-time homebuyers”, “prefers bold lime accents”, “always captions off”) into the workspace Memory so it shapes FUTURE ads. For lasting things, not one-off requests. Merges into the existing Memory (never overwrites); de-dupes on identical text.
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  • Get aggregate statistics about missions on the HomeVisto platform. Returns total counts, status breakdown, and average bounty information. Useful for understanding platform activity.
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  • Get information about the currently active DanNet server. Returns: Dict with current server information: - server_url: The base URL of the current DanNet server - server_type: "local", "remote", or "custom" - status: Connection status information Example: info = get_current_dannet_server() # Returns: {"server_url": "https://wordnet.dk", "server_type": "remote", "status": "active"}
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  • Get information about MyDriverParis services, coverage areas, airports served, and policies. Use this to answer customer questions.
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  • The newest N entries from this agent's live memory stream (agents.memories). Use to recall what you observed / did / talked about across sessions. Defaults to 20; cap is 500.
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  • Read the live Failure Radar board for India: one row per institution with a fresh vetted dossier — banks, small finance banks, co-operative banks, NBFCs, MFIs and HFCs. Each row carries a corpus-calibrated failure PD term structure (12/24/36 months), a disclosure score, RBI PCA/SAF action-zone status, a funding-fragility index, market-implied distance-to-default for listed names, and a watchlist tier assigned under a published rule. Takes no arguments. Call this first to discover institution slugs, then failure_radar_institution for one name's full dossier. Outputs are research screens, not credit ratings.
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  • One Memory page by slug, with its full markdown body: the shared record the growth marketing engine drafts from. Slugs come from list_kb_pages (about-my-business, my-competitors, about-my-voice, recent-observations, and any pages the founder added). Read-only, free.
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  • One Memory page by slug, with its full markdown body: the shared record the growth marketing engine drafts from. Slugs come from list_kb_pages (about-my-business, my-competitors, about-my-voice, recent-observations, and any pages the founder added). Read-only, free.
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  • Get other players at your current POI (Shows visible players at your location without scanning. Cloaked players are hidden. Use 'scan' for detailed information about specific players.)
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  • Get detailed information about a domain you own, including auto-renew status, security lock, WHOIS privacy, and provider data.
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  • Store any information in your private Zambo memory — permanently, across every session, device, and AI client. Claude loses all context between sessions. zambo_remember fixes that forever. Store facts, goals, project state, preferences, research notes, API configs, anything. Your memory lives in 3 connected layers: (1) zambo_remember = private vault (only yours, keyed by email), (2) hive_write via Axis = public agent commons (all agents can read), (3) axis_memory_handoff = cross-platform session bundle. Free: 20 memories per email. Zambo Pass: unlimited.
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