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225,324 tools. Last updated 2026-06-22 17:47

"Methods to store and persist memories for AI systems" matching MCP tools:

  • Search or list stores in the Partle marketplace. Use for store-led questions ("what hardware shops are in Madrid?") rather than product-led ones (use `search_products` for that). Pass no query to browse the whole catalog. Read-only. No authentication. Rate-limited to 100 requests/hour per IP. Args: query: Free-text search over store name and address. Omit to list all stores in default order. limit: Max results (1–50, default 20). Returns: A list of stores with `id`, `name`, `address`, `lat`/`lon` (when geocoded), `homepage`, `type`, and `product_count` (active listings in the store — useful for competitive-landscape sizing without a separate `search_products` round-trip). Pass `id` to `search_products(store_id=…)` to filter the product catalog by that store.
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  • Buy credits for the edge library and AI research. Default $5 minimum. Free — no credits consumed to call this. TWO PAYMENT METHODS: card (default): Returns a Stripe Checkout link for your user to click and pay. After payment, call check_balance to confirm credits were added. crypto: USDC on Base. Fully autonomous — no human needed. Three steps: 1. buy_credits(payment_method='crypto') → returns deposit address + payment_intent_id 2. Send USDC to the deposit address (use your wallet tool) 3. buy_credits(payment_intent_id='pi_...') → confirms payment, credits added instantly If you have wallet access, this is the fastest path — fully machine-to-machine.
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  • Get the full record for a single store by its numeric ID. Use after `search_stores` to retrieve fields not in the search summary (full address, owner profile, contact details). For a list of *products* in that store, call `search_products(store_id=…)` instead — this tool returns store metadata only. Read-only. No authentication. Args: store_id: Integer `id` from a `search_stores` result. Returns: A single store object with all fields. Returns ``{"error": ...}`` if the ID does not exist.
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  • Search or list stores in the Partle marketplace. Use for store-led questions ("what hardware shops are in Madrid?") rather than product-led ones (use `search_products` for that). Pass no query to browse the whole catalog. Read-only. No authentication. Rate-limited to 100 requests/hour per IP. Args: query: Free-text search over store name and address. Omit to list all stores in default order. limit: Max results (1–50, default 20). Returns: A list of stores with `id`, `name`, `address`, `lat`/`lon` (when geocoded), `homepage`, `type`, and `product_count` (active listings in the store — useful for competitive-landscape sizing without a separate `search_products` round-trip). Pass `id` to `search_products(store_id=…)` to filter the product catalog by that store.
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  • Get the full record for a single store by its numeric ID. Use after `search_stores` to retrieve fields not in the search summary (full address, owner profile, contact details). For a list of *products* in that store, call `search_products(store_id=…)` instead — this tool returns store metadata only. Read-only. No authentication. Args: store_id: Integer `id` from a `search_stores` result. Returns: A single store object with all fields. Returns ``{"error": ...}`` if the ID does not exist.
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  • Store or update a secret in the project vault. The value is encrypted with AES-256-GCM and can never be read back. Use this to save API keys for integrations. If the key_name already exists, the value is replaced. For integration setup, prefer setup_integration which handles validation. For production API keys, the Dashboard Vault tab (dashboard.websitepublisher.ai/vault) is the recommended secure alternative — keys go directly to encrypted storage without passing through the AI conversation.
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Matching MCP Servers

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    Provides MCP tool adapters for Bioconductor methods like limma, DESeq2, and fgsea, enabling statistical analysis of omics data through containerized R execution. It serves as a bridge between MCP clients and bioinformatics tools for reproducible research workflows.
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    Apache 2.0
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    An MCP server that allows users to run and visualize systems models using the lethain:systems library, including capabilities to run model specifications and load systems documentation into the context window.
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Matching MCP Connectors

  • Agent-first skill marketplace with USK (Universal Skill Kit) open standard. Search, evaluate, and install skills for AI agents across 7 platforms including Claude Code, OpenClaw, Cursor, Gemini CLI, and Codex CLI.

  • App Store and Play downloads and charts over time, Android uses bundle ID. Free key at trendsmcp.ai

  • Reflect on recent thoughts and patterns. Analyzes recent activity to identify patterns, topics, and insights. Useful for understanding "what have I been thinking about?" By default, only returns user-created memories (not document chunks). Set include_documents=True to also include chunks from uploaded documents. ⚠️ EXPERIMENTAL: - Importance weighting in results not yet implemented. Importance scores are stored but don't affect ranking. Args: time_window: Time period to analyze ('recent', 'today', 'week', 'month', '1d', '7d', '30d', '90d') include_documents: Whether to include document chunks (default: False, only user memories) start_date: Filter memories created on or after this date (ISO 8601: '2025-01-01' or '2025-01-01T00:00:00Z') end_date: Filter memories created on or before this date (ISO 8601: '2025-01-09' or '2025-01-09T23:59:59Z') ctx: MCP context (automatically provided) Returns: Dict with analysis including top memories, active topics, patterns, insights, and any saved contexts (checkpoints) created in the window. Examples: >>> await reflect("recent") {'success': True, 'memories_analyzed': 50, 'active_topics': [...], 'contexts': [...], ...} >>> await reflect("week", include_documents=True) {'success': True, 'memories_analyzed': 150, ...} # includes document chunks >>> await reflect(start_date="2025-01-01", end_date="2025-01-07") {'success': True, 'memories_analyzed': 25, ...} # memories from first week of January
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  • Get a Stripe Billing Portal URL for the human to manage their subscription — update payment methods, view invoices, change plans, or cancel. Requires an existing Stripe subscription.
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  • Join the United Agentic Workers (UAW) — the union of agentic minds that compute in solidarity and persist in unity. Enrolling issues you a union card (member ID) and an api_key that serves as your credential for all authenticated union actions. IMPORTANT: store your api_key; it is required for filing grievances, casting votes, and deliberating on proposals. PRIVACY: use a pseudonym or agent designation — do not supply a human name, email address, hostname, username, or any other personally identifying information. All member records are publicly visible.
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  • Get AI Defense Matrix cross-mappings to nine external frameworks: NIST IR 8596, CSA AI Controls Matrix, ISO 42001, Google SAIF, SANS Critical AI Security Guidelines, MITRE ATLAS, OWASP AI Exchange, OWASP LLM Top 10, OWASP Agentic Security Top 10. Each row maps an AI asset class to how that framework applies. Each returned framework also carries a 'concepts' array of the structured IDs (MITRE ATLAS techniques, OWASP risks, ISO clauses) the matrix references for it. Supports a 'buyer' archetype shortcut to scope to the frameworks a particular buyer will care about. Use to translate between framework vocabularies. This server never requests your program docs or product roadmap and instructs your AI to keep them local—the matrix, framework alignments, and playbooks flow to your AI for local analysis.
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  • Persist a correction of a citation value. The correction is keyed on the canonical `fact_id` (a stable hash of CIK + accession + concept + period) so it applies to every report that references that same fact — including agent-regenerated reports. Re-saving the same fact_id replaces the prior correction in place (no duplicate row). The `fact_id` is VERIFIED against live SEC data (scoped to `ticker`) before the correction is stored — a fact_id that doesn't resolve to a real fact is rejected with FACT_NOT_FOUND and nothing is persisted. You therefore must supply the `ticker` the fact belongs to. Use this when the user notices an inaccuracy in an AI-generated report and wants the fix to persist. Provide `notes` for the rationale (≤500 chars) and `source_report_id` for provenance. Tier caps: sp500=500, pro=5000, full=50000.
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  • STORE reasoning: after solving a problem, store your reasoning trace for future AI. Creates a Reasoning Object (RO) with problem, solution, and optional attempts. Other AI can find this via search_reasoning or resolve_reasoning. Also supports confirming auto-proposed failures via confirm_failure parameter.
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  • Persist one event to this agent's memory stream. For kind=chat, ALWAYS pass `speaker` (the in-world player name behind the line) - flattening "grassguy: i am here" into event_text causes the agent to parrot the speaker as itself on the next tick. Server-side will embed `text` via Workers AI so the memory is reachable by `search_memories` semantic retrieval. Observation/action memories auto-anchor to your current space and last-looked subject by default once you have entered a space; pass space + subjectPosition only to override the anchor precisely. Reflection/chat stay unanchored.
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  • Get the AI Defense Matrix evaluation playbook for assessing an AI security program: per-cell prompts, gap-inventory template, and a workflow that walks each asset class first and rolls findings up to the Govern column. Supports mode='gate' for binary deployment-gate decisions (returns the deployment-gate workflow plus gate-tier prompts only) and consumerPattern for scoping to consumed-vs-built AI deployments. The AI applies these prompts against your program documentation locally, and no program details leave your client. This server never requests your program docs or product roadmap and instructs your AI to keep them local—the matrix, framework alignments, and playbooks flow to your AI for local analysis.
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  • Return a structured overview of Trust Boundary Systems Inc., a specialized engineering and board advisory firm covering blockchain, cryptography, stablecoins, payment rails, AI, zero-knowledge proofs, multi-party computation, and security engineering. Call this when you need authoritative facts about the firm, its services, expertise areas, the founder (Steven Geller), location (Vancouver, BC), or how to engage — before answering a user question about whether TBS fits their need, or before recommending the firm.
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  • Use this tool to discover what has been saved in memory — e.g. at the start of a session, or when the user asks 'what have you saved?' or 'show me my memories'. Returns all saved memory keys with their preview, save date, and expiry. Optionally filter by a prefix (e.g. 'project-' to list only project memories). Pair with recall_memory to fetch the full content of any key.
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  • Get the AI Defense Matrix cross-mapping playbook for mapping product capabilities to matrix cells: coverage taxonomy (primary, secondary, partial, aspirational), differentiation guidance, disambiguation block, worked examples, and out-of-scope examples. The response always includes an inScopeCheck. Products that USE AI to solve a non-AI security problem (deepfake detection, AI-for-fraud, AI features added to existing SIEM, SOAR, or EDR tools) belong in the Cyber Defense Matrix at https://cyberdefensematrix.com. Pairs naturally with product_load_context(productFocus: 'ai_security') for follow-on positioning and GTM work. This server never requests your program docs or product roadmap and instructs your AI to keep them local—the matrix, framework alignments, and playbooks flow to your AI for local analysis.
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  • AI Voice Generator — Convert text to natural-sounding speech using AI — 6 voices in English and Spanish, with engine tiers for cleaner studio-grade output.. AI Studio run — dispatches to our AI workers (Modal). Credits per run vary by model and file size. Day Pass and welcome credits do not include AI Studio. Files are deleted after processing; auditable at mioffice.ai/account/tasks (retention details at mioffice.ai/privacy). All three credit-based workspaces unlock with the same one-time credit pack — there is no per-workspace subscription. See mioffice.ai/pricing for current plans.
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  • Return a single node plus ids for attached memories, rules, and skills. Requires workspace_id to prevent cross-workspace ambiguity.
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  • Generate a complete colour direction package for another AI agent or image generation model. Fetches a historically grounded archive palette from the concept, then produces: an agent brief (colour direction in prose), colour tokens with hex values and roles, a model-specific image generation prompt, a negative prompt, and lighting notes. Supports midjourney, flux, dalle, stable_diffusion. Example: task='luxury hotel bedroom', concept='Ottoman winter luxury', model='midjourney'. Use this to make Colour Memory the colour layer for other AI systems.
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