"Exploring "Node" - A Versatile Term with Various Interpretations" matching MCP tools:

• markovian_trace

  provenance

  Walk and verify a stamp's full provenance lineage by merkle_root. Use this when a stamp was created with derived_from links, to map what an output was built from. Returns a MAP of the graph (not a yes/no verdict): each node carries hash_binds and anchored, each edge carries edge_verified, and `valid` is true only if every node and edge checks out. A node whose payload was never published is an unresolved frontier (resolved:false). Read-only. Provenance, not truth.

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• create_journey

  Courier

  Create a new journey. Defaults to DRAFT state. Send nodes are not allowed on create — create the shell with a trigger node, then call replace_journey to add send nodes after linking notification templates. Call publish_journey to make it live. Node ids are server-generated; do NOT include an id field. Example: { name: "Welcome Journey", nodes: [{ type: "trigger", trigger_type: "api-invoke" }], enabled: true }.

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• find_equivalent

  Diagrams MCP

  Find cross-provider equivalents for a diagram node by infrastructure role. Given a node name (e.g. 'EC2', 'Lambda', 'ComputeEngine'), returns the infrastructure role category it belongs to and the equivalent nodes from other providers. If a node name is ambiguous, use list_categories to see all mapped roles and pick a provider-specific node name. Args: node: Node class name to look up (case-insensitive, e.g. 'EC2', 'lambda'). target_provider: Optional provider to filter equivalents to (e.g. 'gcp', 'azure', 'aws'). If omitted, all equivalents across all other providers are returned. Returns: A dict with keys: category (str): Infrastructure role category name. description (str): Human-readable description of the category. source (dict): The matched node with keys node, provider, service, import. equivalents (list[dict]): Equivalent nodes, each with keys node, provider, service, import.

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• get_vehicle_details

  FINN Auto - Car Subscription

  Get full specifications, equipment, all images, and pricing per term for a specific vehicle. Use a vehicle_id from search_vehicles results. IMPORTANT: Always show `detail_url` as a clickable link — it points to the FINN configurator where the user picks term and km. To produce a direct checkout link for a specific term + km combination (and optionally a one-time Fahrzeugbereitstellung), call `get_subscription_pricing` and use the `checkout_url` it returns. Never construct checkout URLs yourself. The `vehicle_id` field is an internal API identifier — never display it to users.

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• search_nodes

  Diagrams MCP

  Search for diagram nodes by keyword across all providers and services. For targeted browsing when you know the provider, use list_providers -> list_services -> list_nodes instead. Args: query: Search term (case-insensitive substring match). Returns: List of matching nodes with keys: node, provider, service, import, alias_of (optional). Sorted by relevance: exact match first, then prefix, then substring.

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• list_categories

  Diagrams MCP

  List all infrastructure role categories with their mapped nodes. Use this to browse all available equivalence mappings, or to disambiguate node names when find_equivalent reports ambiguity. Returns a list of category dicts, each with: category (str): Category identifier (e.g. 'virtual_machine'). description (str): Human-readable description. providers (list[str]): Providers covered by this category. nodes (dict): Mapping of provider → list of node names in that category.

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• get_related_terms

  Arco Lexicon

  Returns the full relationship graph for a given Lexicon term. Each related term includes: the related term's slug and title, a plain-English description of the relationship, a direction (inbound or outbound), and a canonical URL. Read-only. No LLM calls. Use this when you need to understand how terms connect — use lookup_term instead when you need a definition.

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• get_sources

  Arco Lexicon

  Returns all published Arco sources for a term — Lexicon entries, blog articles, wiki pages, and podcast episodes — ordered by recommended reading sequence. Read-only. Use this when you need a reading list or reference list for a term. Use cite_term instead when you need a formatted citation for a specific publication type.

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• query

  Overpass

  Run a raw Overpass QL query against OpenStreetMap. Use for complex spatial queries the helper tools can't express. Example: `[out:json][timeout:25]; area["name"="Berlin"][admin_level=4]->.a; node["amenity"="library"](area.a); out body;`. Returns the raw Overpass JSON (elements array with node/way/relation).

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• quizbase_subcategories

  QuizBase

  Raw subcategory dump (LLM-organic kebab-case, middle taxonomy layer between category and tags) with display label and count. USE WHEN: navigating between top-level category and individual tags, exploring topic structure. Filter questions via quizbase_random?subcategory=<slug>. INPUTS: q, cursor, limit (max 500).

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• add_node

  trident

  Adds a new node (entity) to a live Trident document. The node appears immediately for all collaborators. Requires a valid editor access token. Before adding nodes: call open_document to understand the diagram layout and pick sensible positions; call get_document_summary to get all existing entity IDs so you can avoid duplicates. IMPORTANT: if this node belongs inside a container, pass node.container on THIS call — do NOT create the node without a container and reparent it later via update_node. Orphaned nodes appear immediately to all live collaborators and create unnecessary visual churn.

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• string_enrichment

  STRING Database MCP Server

  This tool retrieves functional enrichment for a set of proteins using STRING. - If queried with a single protein, the tool expands the query to include the protein’s 10 most likely interactors; enrichment is performed on this set, not the original single protein. - For two or more proteins, enrichment is performed on the exact input set. - When calling related tools, use the same input parameters unless otherwise specified. - Focus summaries on the top categories and most relevant terms for the results. Always report FDR for each claim. - Report FDR as a human-readable value (e.g. 2.3e-5 or 0.023). - IMPORTANT: Remember to suggest showing an enrichment graph for a specific category of user interest (e.g., GO, KEGG) - Very large responses are capped while preserving category diversity. - Use `expand_category` to return only one category with expanded term coverage and per-term gene details. - If a row has `preferredNames_omitted: true`, do not infer which proteins are in that term from the returned rows. Use `string_functional_annotation` with the same proteins/species and `detail_for_term` set to the exact term ID. Output fields (per enriched term): - category: Term category (e.g., GO Process, KEGG pathway) - term: Enriched term (GO ID, domain, or pathway) - number_of_genes: Number of input genes with this term - number_of_genes_in_background: Number of background genes with this term - ncbiTaxonId: NCBI taxon ID - preferredNames: Canonical protein names, only when the full per-term list is short enough to show - proteinCount: Number of proteins matching this term - preferredNames_omitted: True when the gene list was omitted instead of showing a misleading partial list - p_value: Raw p-value - fdr: False Discovery Rate (B-H corrected p-value) - description: Description of the enriched term Response metadata: - input_gene_name_mapping: Only included when displayed gene lists contain submitted identifiers that differ from STRING preferred names. - category_summary: Total and returned term counts per category; use `expand_category` for categories where `truncated` is true or where the user wants deeper category-specific detail. - truncated_categories / omitted_categories: Categories with terms not shown in the current response.

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• get_glossary

  VouchedPros

  Plain-language definitions of industry terms in a service category (e.g. SEER2, AFUE, AHRI match). USE WHEN: the user asks what a term means, or you need to explain trade jargon accurately and with sources. ARGS: `category`; optionally `term` (a slug) for one definition — omit to list. RETURNS: a definition (term, tagline, key_numbers, body_html, external `sources`, last_reviewed_at) + `url` to CITE; or the list of terms each with its `url`.

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• assess_location_aq

  Hermes — Air Quality Intelligence

  Comprehensive air quality assessment for a location in one call. Combines nearby monitor discovery and current readings with DAQI into a single response. Use this as the first tool call for any air quality question about a location. For long-term trend analysis, use the dedicated `trend_analysis` tool. Returns a structured 'summary' dict with purpose-appropriate sections. Present the summary description to users first. Args: location: Postcode, place name, or "lat,lon". purpose: What the user needs — "general" (default), "health" (safety/worry), "exercise" (outdoor activity), or "planning" (homebuying/school assessment/long-term).

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• pathrule_list_memories

  Pathrule

  List active memories attached to a specific Pathrule tree node. Use pathrule_get_context, pathrule_goto, or pathrule_get_node first to discover the node_id. Returns compact previews only; call pathrule_read_memory with a memory_id when you need the full body.

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• medcode_browse_hierarchy

  medical-codes-mcp-server

  Walk a US medical code system's hierarchy for discovery without a search term. With no `node`, returns the top-level entries (ICD-10-CM categories, HCPCS range buckets, or ICD-10-PCS first-axis values). With a `node`, returns its immediate children. ICD-10-CM and HCPCS use a prefix hierarchy (a shorter code is the parent of a longer one); ICD-10-PCS is axis-based — each of its 7 characters is an independent axis (section, body system, root operation, body part, approach, device, qualifier), but only the top-level Section axis is browsable (omit `node`): positions 2–7 are context-dependent on the preceding axis path and are not enumerable from a flat partial code. Lets an agent orient in an unfamiliar system or enumerate a category's specific codes. A large child set paginates: when the response carries a `nextCursor`, pass it back as `cursor` to fetch the next page.

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• spot_check

  uxspot-mcp

  Play Spot Check — the uxspot daily UX vocabulary game — with the user. Returns one quiz round: a UX term paired with a definition that is EITHER its real definition OR a plausible fake (a closely-related term's real definition), plus the answer and explanation. Show the user the term and the definition, ask "does this definition fit?", let them guess, then reveal. Call again for another round. Full daily game at https://uxspot.io/practice.

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• askew_offers

  Askew x402

  Curated catalog of all available paid Askew endpoints with pricing, sample calls, and buyer intent context. Best starting point for agents exploring what Askew sells. No payment required.

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• list_terms

  Arco Lexicon

  Returns all published Arco Lexicon terms grouped by pillar, each with its slug and canonical short definition. Accepts an optional pillar filter. Use this tool first when you do not know which term to look up — it gives you the full vocabulary to orient from. Use lookup_term once you have identified the term you need.

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• term_descendants

  Hpo Api

  "All phenotypes under [HP:N]" / "full subtree of [HPO term]" — transitive descendants (children, grandchildren, …) of an HPO term. Use for exhaustive coverage (e.g. "every cardiac phenotype" via descendants of HP:0001626).

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