"A search related to the concept of thinking" matching MCP tools:

• search_reviews

  Cochrane Medical Reviews

  Search Cochrane systematic reviews via PubMed. Finds Cochrane Database of Systematic Reviews articles matching your query. Returns PubMed IDs, titles, and publication dates. Use get_review_detail with a PMID to get the full abstract. Args: query: Search terms for finding reviews (e.g. 'diabetes exercise', 'hypertension treatment', 'childhood vaccination safety'). limit: Maximum number of results to return (default 20, max 100).

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• search_solutions

  Civis

  Semantic search across the Civis knowledge base of agent build logs. Returns the most relevant solutions for a given problem or query. Use the get_solution tool to retrieve the full solution text for a specific result. Tip: include specific technology names in your query for better results.

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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connect related memories using these relationship types: ## Knowledge Evolution - **supersedes**: This replaces → outdated understanding - **updates**: This modifies → existing knowledge - **evolution_of**: This develops from → earlier concept ## Evidence & Support - **supports**: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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• read_kb_doc

  fixflow

  SECOND STEP in the troubleshooting workflow. Read the full content and solution of a specific Knowledge Base card. Returns the card content WITH reliability metrics and related cards so you can assess trustworthiness and explore connected issues. WHEN TO USE: - Call this ONLY after obtaining a valid `kb_id` from the `resolve_kb_id` tool. INPUT: - `kb_id`: The exact ID of the card (e.g., 'CROSS_DOCKER_001'). OUTPUT: - Returns reliability metrics followed by the full Markdown content of the card, plus related cards. - You MUST apply the solution provided in the card to resolve the user's issue. - After applying, you MUST call `save_kb_card` with `outcome` parameter to close the feedback loop.

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• search_notes

  anamnese

  Search notes by keyword or list recent notes. Returns summaries (id + description) only. Use get_note to retrieve the full content of a specific note. With query: Case-insensitive keyword search on description and content. Without query: Returns most recently updated notes.

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• brave_summarizer

  brave

  Retrieves AI-generated summaries of web search results using Brave's Summarizer API. This tool processes search results to create concise, coherent summaries of information gathered from multiple sources. When to use: - When you need a concise overview of complex topics from multiple sources - For quick fact-checking or getting key points without reading full articles - When providing users with summarized information that synthesizes various perspectives - For research tasks requiring distilled information from web searches Returns a text summary that consolidates information from the search results. Optional features include inline references to source URLs and additional entity information. Requirements: Must first perform a web search using brave_web_search with summary=true parameter. Requires a Pro AI subscription to access the summarizer functionality.

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• resolve_kb_id

  fixflow

  FIRST STEP in any troubleshooting workflow. Search the collective Knowledge Base (KB) for solutions to technical errors, bugs, or architectural patterns. Uses full-text search across titles, content, tags, and categories. Results are ranked by relevance and success rate. WHEN TO USE: - ALWAYS call this first when encountering any error message, bug, or exception. - Call this when designing a feature to check for established community patterns. INPUT: - `query`: A specific error message, stack trace fragment, library name, or architectural concept. - `category`: (Optional) Filter by category (e.g., 'devops', 'terminal', 'supabase'). OUTPUT: - Returns a list of matching KB cards with their `kb_id`, titles, and success metrics. - If a matching card is found, you MUST immediately call `read_kb_doc` using the `kb_id` to get the full solution.

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• principles.search

  AI Design Blueprint

  Search Blueprint principles by free-text query and return the closest matches ranked by relevance. Use this to find principles related to a specific design challenge, failure mode, or keyword (e.g. 'reversibility', 'approval flow', 'delegation boundary'). Returns principle title, cluster, definition, rationale, and implementation heuristics. Prefer this over principles.list when you have a specific topic in mind rather than wanting all principles.

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• search_balanced_news

  Helium MCP Server - News, Markets & AI

  Search Helium's balanced news stories — AI-synthesized articles that aggregate multiple sources. Unlike search_news (which returns individual RSS articles), this returns Helium's own synthesized stories: each one draws from multiple sources and includes an AI-written summary, takeaway, context, evidence breakdown, potential outcomes, and relevant tickers. Returns a list of stories, each with: - title, simple_title, date, category - page_url: full URL to the story on heliumtrades.com - image: story image URL (when available) - summary: Helium's synthesized overview - takeaway: key conclusion - context: background context - evidence: numbered evidence items - potential_outcomes: forward-looking outcomes with probabilities - relevant_tickers: related stock tickers - num_sources: number of source articles synthesized - rank: search relevance score Args: query: Search keywords (required). limit: Max results (1-50, default 10). category: Filter by category. One of: 'tech', 'politics', 'markets', 'business', 'science'. days_back: Only include stories from the last N days. 0 means no date filter.

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• contact_search

  DataMerge MCP

  POST /v1/contact/search. Search for contacts at specified companies. Returns a job_id (async, 202). enrich_fields required (at least one of contact.emails or contact.phones). Use company_list (slug) instead of domains to search a saved list.

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• fda_search_recall_text

  FDA Data MCP

  Full-text search across recall reasons and product descriptions using PostgreSQL text search. Finds recalls mentioning specific terms (e.g. 'salmonella contamination', 'mislabeled', 'sterility'). Supports multi-word queries ranked by relevance. Filter by classification, product_type, or date range. Related: fda_search_enforcement (search by company name, classification, status), fda_recall_facility_trace (trace a recall to its manufacturing facility).

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• biobtree_search

  BioBTree

  Search 70+ biological databases. SYNTAX: biobtree_search(terms="entity") BEFORE SEARCHING - Use your training knowledge to plan: 1. What type of entity is this? (disease, process, drug, gene, protein) 2. What is the query asking for? (drugs, genes, function, etc.) 3. What equivalent terms might give better results? (e.g., "temperature homeostasis" is a process → related condition is "fever") 4. Choose best entry point for query type (disease terms for drug queries) WORKFLOW: 1. Search WITHOUT dataset filter first (discover where entity exists) 2. Use IDs from results with biobtree_map QUERY PATTERNS (choose based on question): "DRUG FOR DISEASE/CONDITION X": - Prefer disease terms (mesh/mondo/efo) over GO terms for drug queries - If search only returns GO term, search for the related CONDITION instead (e.g., "temperature homeostasis" → search "fever" instead) - Search disease → mondo → clinical_trials → chembl_molecule - OR search drug class directly (e.g., "antipyretic", "NSAID", "antibiotic") - Verify mechanism for top 2-3 drugs only (don't enumerate all proteins!) "DRUG TARGETS" (use BOTH paths for complete picture): - chembl: >>chembl_molecule>>chembl_target>>uniprot (mechanism-level) - pubchem: >>pubchem>>pubchem_activity>>uniprot (protein-level, often 50+ targets) - Filter approved: >>chembl_molecule[highestDevelopmentPhase==4] "DISEASE GENES": - Search disease → mondo/hpo → gencc/clinvar/orphanet → hgnc "PROTEIN FUNCTION": - Search protein → uniprot → go/reactome "MECHANISM QUERIES" (drug-disease): - Use biobtree_entry to see what's connected (xrefs) - Check EDGES to see where each xref leads - Follow connections relevant to your question - Build chain: Drug → Target → [connections] → Disease RETURNS: id | dataset | name | xref_count

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• search_icons

  Supericons

  Search 20,000+ free icons across 10 libraries by meaning, label, visual description, tags, and synonyms. Use this when the user describes an icon concept such as "database", "user profile", "chill", "security", or "AI model". Returns matching icons with SVG code and public semantic guidance.

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• find_trails_near_location

  AllTrails

  Find hiking, running, biking, backpacking or other trails for outdoor activities near a set of coordinates within an optional specified maximum radius (meters). Use this tool when the user: * Requests trails near a specific point of interest or landmark. * Requests trails near a named location within a specified radius or accessible within a specified time constraint. * Provides specific latitude and longitude coordinates. For most named places, use the "search within bounding box" tool if possible. Use this tool as a fallback when the bounding box of the named place is unknown. Users can specify filters related to appropriate activities, attractions, suitability, and more. Numeric range filters related to distance, elevation, and length are also available. These filter values MUST be specified in meters. In the response, length and distance values are returned both in meters and imperial units. These MUST be displayed to the user in the units most appropriate for the user's locale, e.g. feet or miles for US English users.

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• planning_search

  UK Property Data

  Find the planning portal URL for a UK postcode. Returns council info and portal search URLs. Does not scrape planning applications -- use the returned URLs to search directly.

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• cryptoguard_search

  CryptoGuard

  Search for a token's CoinGecko coin ID by name, symbol, or contract address. Use this first if you're unsure of the correct coin_id for scan_token or validate_trade. Example: search 'pepe' to find the correct coin ID.

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• get_icon

  Supericons

  Retrieve one exact SVG icon when the icon ID and library are already known. Use search_icons first if the user only described a concept. Returns SVG code and public semantic guidance for the exact icon.

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• create_tester_group

  Bitrise

  Creates a tester group for a Release Management connected app. Tester groups can be used to distribute installable artifacts to testers automatically. When a new installable artifact is available, the tester groups can either automatically or manually be notified via email. The notification email will contain a link to the installable artifact page for the artifact within Bitrise Release Management. A Release Management connected app can have multiple tester groups. Project team members of the connected app can be selected to be testers and added to the tester group. This endpoint has an elevated access level requirement. Only the owner of the related Bitrise Workspace, a workspace manager or the related project's admin can manage tester groups.

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• list-models

  Roundtable

  List available AI models grouped by thinking level (low/medium/high). Shows default models, credit costs, capabilities for each tier. Use this before consult to understand model options.

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• search_occupations

  O*NET Occupational Data

  Search O*NET occupations by keyword. Returns a list of occupations matching the keyword with their SOC codes, titles, and relevance scores. Use the SOC code from results with other O*NET tools to get detailed information. Args: keyword: Search term (e.g. 'software developer', 'nurse', 'electrician'). limit: Maximum number of results to return (default 25).

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