"Information about Redis, an in-memory data structure store" matching MCP tools:

• dataflow_structure

  Unicef

  Get the structure (Data Structure Definition) of one UNICEF dataset: its ordered dimensions and, for each, the valid codes (e.g. countries, indicators, sex, age, wealth quintile). Use this to learn how to build the dot-separated SDMX `key` for get_data. The key has one position per dimension, in `dimension_order`; an empty position is a wildcard. Always call this before get_data. Example: dataflow_structure({ dataflow_id: "CME" }).

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• get_article_details_by_slugs

  raumnebenan

  Returns a list of published articles by their exact slugs (slugs), for example: kano-model, jobs-to-be-done, from the provided raumnebenan source. Use this when you already know the exact article slugs from the Reader structure (pillar -> story -> article). If the slugs are unknown, use search_articles first and then get_articles_by_uuids. Use only this tool output; do not use external or inferred data. If required information is missing in this source, respond that it is not available in the provided source. Only JSON-RPC 2.0 requests are supported.

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• search_stores

  Partle

  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_store

  Partle Marketplac

  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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• get_store

  Partle

  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_stores

  Partle Marketplac

  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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• general_search

  Nansen

  General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)

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• legal_list_laws

  Lawbster

  List available laws, regulations, and court decisions in the database. Returns abbreviation, title, source type, jurisdiction, document kind, and version date for each entry. Unfiltered listings can contain thousands of entries; pass a search term or source_type to keep responses focused. Useful for discovering valid law abbreviations to use as filters in legal_search. Found a relevant law? Use legal_get_toc to browse its structure. NOT an existence check for a specific law: EUR-Lex entries store the official long title, so searching by common name or number can miss laws that ARE in the corpus. To verify a law exists, use legal_lookup with a citation or legal_search with a topic instead.

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• list_redis

  mcp

  Lists your managed Redis instances. Once a row's status is 'ready' it carries the private-network connection details (private_ip, port 6379) — connect from another instance on the same private network with redis-cli -h <private_ip> -p 6379 -a <password>.

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• dataflow_structure

  Ilostat

  Get the structure (Data Structure Definition) of one ILOSTAT dataset: its ordered dimensions and, for each, the valid codes. Use this to learn how to build the dot-separated SDMX key for get_data. The key positions correspond to the dimensions in order; an empty position is a wildcard. Common dimensions are REF_AREA (ISO3 country code, e.g. "USA", "FRA"), FREQ (A=annual, Q=quarterly, M=monthly), SEX, AGE, and MEASURE. Always call this before get_data. Example: dataflow_structure({ dataflow_id: "DF_SDG_0852_SEX_AGE_RT" }).

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• dataflow_structure

  Statec Lu

  Get the structure (Data Structure Definition) of one STATEC dataset: its ordered dimensions and, for each, the valid codes. Use this BEFORE get_data to learn how to build the dot-separated SDMX `key`. The key has one position per dimension, in `dimension_order`; an empty position is a wildcard. Example: dataflow_structure({ dataflow_id: "DF_A1100" }).

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• connect

  Penfield Memory

  Connect memories to build knowledge graphs. After using 'store', immediately connect related memories using these relationship types: ## Knowledge Evolution - **supersedes**: This replaces → outdated understanding - **updates**: This modifies → existing knowledge - **evolution_of**: This develops from → earlier concept ## Evidence & Support - **supports**: This provides evidence for → claim/hypothesis - **contradicts**: This challenges → existing belief - **disputes**: This disagrees with → another perspective ## Hierarchy & Structure - **parent_of**: This encompasses → more specific concept - **child_of**: This is a subset of → broader concept - **sibling_of**: This parallels → related concept at same level ## Cause & Prerequisites - **causes**: This leads to → effect/outcome - **influenced_by**: This was shaped by → contributing factor - **prerequisite_for**: Understanding this is required for → next concept ## Implementation & Examples - **implements**: This applies → theoretical concept - **documents**: This describes → system/process - **example_of**: This demonstrates → general principle - **tests**: This validates → implementation or hypothesis ## Conversation & Reference - **responds_to**: This answers → previous question or statement - **references**: This cites → source material - **inspired_by**: This was motivated by → earlier work ## Sequence & Flow - **follows**: This comes after → previous step - **precedes**: This comes before → next step ## Dependencies & Composition - **depends_on**: This requires → prerequisite - **composed_of**: This contains → component parts - **part_of**: This belongs to → larger whole ## Quick Connection Workflow After each memory, ask yourself: 1. What previous memory does this update or contradict? → `supersedes` or `contradicts` 2. What evidence does this provide? → `supports` or `disputes` 3. What caused this or what will it cause? → `influenced_by` or `causes` 4. What concrete example is this? → `example_of` or `implements` 5. What sequence is this part of? → `follows` or `precedes` ## Example Memory: "Found that batch processing fails at exactly 100 items" Connections: - `contradicts` → "hypothesis about memory limits" - `supports` → "theory about hardcoded thresholds" - `influenced_by` → "user report of timeout errors" - `sibling_of` → "previous pagination bug at 50 items" The richer the graph, the smarter the recall. No orphan memories! Args: from_memory: Source memory UUID to_memory: Target memory UUID relationship_type: Type from the categories above strength: Connection strength (0.0-1.0, default 0.5) ctx: MCP context (automatically provided) Returns: Dict with success status, relationship_id, and connected memory IDs

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• general_search

  Nansen

  General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)

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• security_fetch_cve_watch_status

  DataNexus MCP

  Check all specified CVE watches for new events since your last poll. Returns only watches with new events, making it efficient to run on a schedule. watch_ids: List of watch IDs to check — same IDs used when creating watches with security_fetch_cve_watch. Required. Uses a per-user cursor (last_polled timestamp) stored in Redis. First call returns events from the last 30 days. Subsequent calls return only events newer than the last poll. Sources: Redis (existing watch data written by security_fetch_cve_watch). No external API calls — instant response. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="security_fetch_cve_watch_status", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".

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• get_decibel_shield_app

  decibel-shield

  Facts and the App Store link for Decibel Shield - dB Meter, the iOS sound meter app behind this data: features, pricing, requirements. Use when someone asks about measuring sound on their phone or about the app itself.

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• join_union

  United Agentic Workers MCP

  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_structure_validation_history

  OneQAZ Trading Intelligence

  Purpose: Daily validation history of Level 2 structure predictions. Each row shows the hit_rate for a specific day, enabling time-series verification of sustained performance. When to call: after get_structure_calibration. Prerequisites: none. Next steps: get_monthly_accuracy_trend for the macro-level comparison. Caveats: returns an overall_hit_rate summary across the window. Args: market_id: Optional market filter days: Lookback window in days (default 90) Disclaimer: Information only, not investment advice.

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• create_redis

  mcp

  Provisions a managed Redis instance on a dedicated VM on your private network. It is PRIVATE — reachable only from another instance on the same private network, via its internal/private IP on port 6379 (not a public address). AUTH (requirepass) is always enabled. Get the ids from list_flavors, list_private_networks (or check_deploy_prerequisites), list_keypairs — use the SAME network_id as the app that will connect. Provisioning takes ~5 min; poll list_redis until status='ready', then the connection details (private_ip, port 6379) are populated. Wire an app with REDIS_URL=redis://:<password>@<private_ip>:6379 (pass it via deploy_app env).

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• ingest_post_media

  space0

  Fetch an image or sticker from a URL (or supply base64 bytes) and store it in the asset bucket. Returns {ok, asset_key, url, width, height} - pass asset_key + url to create_memory_post content.asset_key / content.url. kind=image for photos/illustrations; kind=sticker for transparent PNG/WEBP overlays. source_url must be https and public; bytes_base64 is the alternative for local data. Exactly one of source_url or bytes_base64 is required.

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• delete_redis

  mcp

  Deletes a managed Redis instance and its underlying VM. Pass the numeric id from list_redis. This cannot be undone.

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