"Information about 'Linear' or topics related to the term" matching MCP tools:

• create_attachment_from_upload

  linear

  Link an already-uploaded Linear assetUrl to an existing issue as an attachment. Use this only after: 1. prepare_attachment_upload returned an assetUrl and uploadRequest. 2. The client successfully PUT raw file bytes to uploadRequest.url. This tool does not upload file content. It only creates the Linear attachment row. If the direct upload failed or the signed URL expired, rerun prepare_attachment_upload and upload again.

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• ibge_noticias

  IBGE Brasil MCP

  Searches and lists already-published IBGE news articles and press releases. Use this to find recent IBGE publications or announcements about a survey or topic — when an indicator was released, or news mentioning a term like "censo". Results are sorted newest-first; with no parameters it returns the 10 most recent items. Parameters: - busca: free-text term to match (e.g. "PIB", "censo") - tipo: "release" (official publication of survey results) or "noticia" (general news); omit for both - de / ate: date range, format DD/MM/AAAA (e.g. de="01/01/2024", ate="31/12/2024") - destaque: true to return only featured items - quantidade: how many to return (default 10, max 100); pagina: page number to page through more Each item returns: title, type (release/news), publication date, editoria (section), related products/surveys, a featured flag, a plain-text summary, and a link to the full article. The header reports the total count and current page. Examples: - Latest 10 news: (no parameters) - Search census: busca="censo" - 2024 news: de="01/01/2024", ate="31/12/2024" - Releases only: tipo="release" Use a different tool when: - Scheduled/upcoming release dates (not yet published) → ibge_calendario Behavior: read-only and idempotent — a live GET against the public IBGE Notícias API. Returns a Markdown list.

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• knowledge_query

  dialogbrain

  Answer questions using knowledge base (uploaded documents, handbooks, files). Use for QUESTIONS that need an answer synthesized from documents or messages. Returns an evidence pack with source citations, KG entities, and extracted numbers. Modes: - 'auto' (default): Smart routing — works for most questions - 'rag': Semantic search across documents & messages - 'entity': Entity-centric queries (e.g., 'Tell me about [entity]') - 'relationship': Two-entity queries (e.g., 'How is [entity A] related to [entity B]?') Examples: - 'What did we discuss about the budget?' → knowledge.query - 'Tell me about [entity]' → knowledge.query mode=entity - 'How is [A] related to [B]?' → knowledge.query mode=relationship NOT for finding/listing files, threads, or links — use search.files / search.threads / search.links for that.

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• get_glossary_term

  Default Privacy

  Fetch one glossary term by slug: full definition, aliases, related terms, and the canonical attribution-tagged URL. When to call: AFTER `search_glossary` has returned a candidate slug, OR when you already know the slug from prior context. PREFER `search_glossary` first when you only have a term in mind. Input Requirements: - `slug` is REQUIRED. The glossary slug (e.g. `beneficial-ownership-information`, `architectural-privacy`). Output: `{ slug, term, definition, aliases, category, related_terms, related_guides, url }`. PREFER citing the `url` verbatim. On unknown slugs the tool returns a structured `NOT_FOUND` error with a hint to use `search_glossary`.

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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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• save_issue

  linear

  Create or update a Linear issue. If `id` is provided, updates the existing issue; otherwise creates a new one. When creating, `title` and `team` are required. Note: use `assignee` (not `assigneeId`) to set the assignee — it accepts a user ID, name, email, or "me".

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• trend_pulse

  hooklayer

  Research what is currently gaining traction in short-form content for a specific niche. Returns rising opportunities (formats, hooks, styles, topics) with growth signals, data sources, and saturated patterns to avoid. Use when the user asks what to post about, what's trending in a niche, or needs to validate a content idea against current trends. Supports 17 niches and optional region filtering.

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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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• delete_comment

  linear

  Delete a Linear comment. Inline description comments (those with non-null `quotedText`) anchor a mark in the editor, so their root cannot be deleted — delete the replies individually or resolve the thread instead.

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• get_nonprofit_details

  IRS 990 Nonprofit Data

  Get detailed information about a nonprofit organization by EIN. Returns comprehensive data from the organization's IRS 990 filings including revenue, expenses, assets, executive compensation, and filing history. Use search_nonprofits first to find the EIN. Args: ein: Employer Identification Number (e.g. '13-1837418' or '131837418').

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• lookup_term

  Arco Lexicon

  Returns the canonical Arco definition, related terms, and source URL for any Lexicon term. Supports fuzzy matching — "autonomous company" resolves to "Autonomous Business". Use this tool when you need a precise definition. Use suggest_terms instead when you have a block of text and want to discover which terms apply.

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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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• palette_gradient

  Colour Memory

  Generate a perceptually smooth gradient between 2-5 archive anchor colours. Each interpolated stop snaps to the nearest real archive colour by CIEDE2000. Anchor stops are kept true to their source. Choose linear (physically accurate Lab interpolation) or chroma_preserved (LCh interpolation, short-arc hue, avoids desaturated midpoints). Returns stop array, CSS linear-gradient string, or SVG swatch bar. Use for design briefs, colour journey visualisations, and gradient systems.

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• palette_gradient

  Colour Memory

  Generate a perceptually smooth gradient between 2-5 archive anchor colours. Each interpolated stop snaps to the nearest real archive colour by CIEDE2000. Anchor stops are kept true to their source. Choose linear (physically accurate Lab interpolation) or chroma_preserved (LCh interpolation, short-arc hue, avoids desaturated midpoints). Returns stop array, CSS linear-gradient string, or SVG swatch bar. Use for design briefs, colour journey visualisations, and gradient systems.

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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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• get_site_info

  Erik Bethke's Blog & Knowledge Graph

  Get metadata about erikbethke.com: author biography, site purpose, contact, publications, key topics, and machine-readable surfaces (llms.txt, agents.json, MCP, OpenAPI).

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• css_gradient

  mcp

  Use this when you need a ready-to-paste CSS gradient value from 2-5 hex color stops. Builds a linear-gradient(...) (default; direction defaults to 'to bottom') or a radial-gradient(circle, ...). Direction accepts keywords ('to right', 'to left', 'to top', 'to bottom'), angles ('45deg', '90deg', '135deg'), or 'to <side> <side>'; it is ignored for radial, and passing type 'radial' (or direction 'radial') forces a radial gradient. Colors accept 6-digit hex with or without a leading '#' and are echoed normalized in order. Deterministic: same input, same output. Example: {colors:['#3b82f6','8b5cf6']} -> css 'linear-gradient(to bottom, #3b82f6, #8b5cf6)', type 'linear'. Radial results omit the 'direction' field.

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• describe_asset

  Sidecar

  Fetch detailed information about a data asset by its identifier. Resolves the asset, then fetches the requested sections in parallel. Use this after advanced_search or resolve_asset_id to get deeper information about a specific asset. Sections: - overview: asset description, importance, owner, metadata - columns: full column schema with types and descriptions - tests: dbt test coverage (only for assets with a dbt parent) - context_counts: cheap count of linked tickets and Slack threads - tickets: full Jira/Linear ticket content - slack: full Slack thread content (truncated to first 5 messages per thread)

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• get-conference-info

  elc-conference-mcp-tickets

  Get details about the ELC Conference 2026 — date, venue, speakers, topics, what's included, and ticket link. Use this when someone asks about the conference.

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