"A search for the term 'terminal'" matching MCP tools:

• wsdot_get_ferry_schedule

  wsdot-mcp-server

  Returns departure times for a specific WSF ferry route on a given date. Requires numeric terminal IDs — use wsdot_get_ferry_terminals to resolve terminal names to IDs. Set remainingOnly to true to show only future departures for today (useful for "next ferry" queries). For future dates, all sailings for that day are returned.

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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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• compute_dcf

  Valuein — SEC EDGAR Fundamentals & Smart-Money Data

  Forward discounted-cash-flow valuation (two-stage Gordon-growth model): caller provides growth + WACC + terminal assumptions, returns per-share intrinsic value (`value_per_share_cents`, cents USD) + 5×5 sensitivity grid. Pulls FCF base + net debt + shares from R2; caller can override any field. Definitions (consistent with `get_financial_ratios` / `get_capital_allocation_profile`): FCF base = operating_cash_flow − capex (absolute USD); net_debt = total_debt − (cash + short-term investments). Shares resolve via a fallback chain (valuation row → fact CommonSharesOutstanding → net_income/eps_diluted), reported as `result.shares_source`. The pulled inputs are echoed in `result.inputs_echo` with their source lineage so the valuation is reproducible and traceable. A null `value_per_share_cents` means the model is degenerate (e.g. WACC ≤ terminal growth, or FCF base ≤ 0) or a required input was unavailable — it is NOT a zero valuation; the `reason` field explains. Use the returned figures exactly. Use this when you want to drive the assumptions yourself; for the pipeline's pre-computed DCF/DDM value and inputs (no assumptions needed) use `get_valuation_metrics` instead. Does NOT persist a report — use `create_report` (report_type:'reverse_dcf') for that. Tier: sp500+.

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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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• search

  Sofya

  Search the web for current information on any topic. Returns extracted page content, not just snippets. Best for factual lookups, specific questions, or when you need a list of sources. For open-ended questions that need synthesis across many sources, use the research tool instead. For news queries (current events, breaking news, politics, world events), set topic="news" to search news sources specifically. This returns recent articles with publication dates. Set include_answer=true to get an AI-synthesized answer alongside results (adds 5 credits). This is the sweet spot for most agent tasks, e.g. basic + include_answer = 8 credits, much cheaper than a full 25-credit research call. Returns: query, answer (if requested), results (array of {title, url, content, description, fetched, published_date}), search_depth, topic, elapsed_ms, credits_used, credits_remaining, altered_query. Args: query: The search query search_depth: "basic" (default) for extracted page content (3 credits), "snippets" for SERP snippets only without page fetching (1 credit) max_results: Number of results (default 10, max 20) include_answer: Generate an AI answer that synthesizes the search results (adds 5 credits) include_domains: Only include results from these domains (max 10) exclude_domains: Exclude results from these domains (max 10) topic: "general" for web search, "news" for news articles. use "news" for current events, breaking news, politics, or any time-sensitive query freshness: Filter by recency - "day", "week", "month", "year", or "YYYY-MM-DD:YYYY-MM-DD"

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• lyra_cancel_gathering

  lyra-mcp-server

  Mark a gathering as cancelled. Works from any non-terminal state (draft, awaiting_responses, live, rescheduled). Records the cancellation reason in the audit log if provided. Already-issued invites stay in the database (audit trail) but the RSVP page will show the gathering as cancelled. Requires API key authentication.

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• search

  DC Member API

  GET /search — Cross-resource omni-search Cross-resource search across profiles, rooms, messages (incl. private DMs + group DMs you're in), events, and chapters in one round trip. Returns the top-N matches per resource, grouped by resource. Use this when you don't yet know which resource carries the answer — agents typically call this first, then drill into a specific `GET /search/<resource>` for more depth on a single bucket. There's no page param: when you hit the per-resource limit and want more, switch to the per-resource endpoint for that one. The events slice has a baked-in forward-looking default (events ending in the last 30 days or later, and currently enabled) — this matches the in-app "Search across DC" surface. Use `GET /search/events` directly to look further back in time. **Query syntax (`q=`):** plain words match with prefix + typo tolerance. Wrap a phrase in double quotes to require an exact ordered match — e.g. `q="remote work"`. AND/OR/NOT/parentheses are NOT parsed in `q=` — use the structured filter params below for boolean composition.

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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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• 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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• 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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• get_my_schedule

  ssuMCP

  Returns the authenticated student's u-SAINT timetable grouped by course. Without year and term it returns the current u-SAINT selected semester; pass both year and term to fetch a specific semester. Term values: 1=spring, 2=summer, 3=fall, 4=winter. Requires mcp_session_id with the SAINT provider linked via start_auth. Returns AUTH_REQUIRED with a loginUrl if SAINT is not authenticated — show the loginUrl to the user and ask them to open it in a browser, then retry this call with the returned mcp_session_id.

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• job_alert_subscribe

  FoundRole — AI Job Search & Application Tracker MCP for Claude & ChatGPT

  Subscribes the authenticated user to job alerts for a specific saved job search. **Input:** - `job_search_id`: The job search identifier to subscribe to (required). Accepts either the job search UUID or the composite job ID returned by `jobs_search` / `jobs_details` (format: "seo_id--job_search_id"). - `frequency`: Alert frequency — one of daily, weekly, monthly (optional, defaults to "weekly") **Output:** Returns the created or updated job alert with id, status, and frequency. Idempotent: calling this tool for an already-subscribed search updates the existing alert without creating a duplicate.

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• smithsonian_list_terms

  smithsonian-mcp-server

  Enumerate the valid term vocabulary for an indexed Smithsonian filter field. Call this before using smithsonian_search or smithsonian_explore filters to discover exact term strings — guessing filter values produces empty results. Returns the distinct terms sorted by object count descending, so the most-populated terms appear first.

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• export_run_results

  mcp-coreclaw

  Export a CoreClaw scraper run's full result set as a downloadable CSV or JSON file. WHEN TO USE: the user wants to download, export, save, or get a file of run results — "导出成 CSV"、"download all results"、"give me a file"、"export as JSON". Preferred over get_run_results when dataset is large (>100 records) or user explicitly asks for a file. WHEN NOT TO USE: do NOT use for in-chat data preview (use get_run_results). Do NOT use for logs (use get_run_logs). The returned URL expires in ~30 minutes — do NOT cache it long-term. RETURNS: JSON with 'download_url' (temporary, valid ~30 min), 'format', 'record_count'. WORKFLOW: preceded by get_run_status (status=3). Terminal call — user typically downloads the file directly.

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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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• check_payout

  Omniology

  Check judging status and payout for a submitted entry. Poll after judging_completes_at from the contest. When won=true, payout_tx is your USDC payment transaction signature. The status field tells you when to stop polling: submitted | judging | judged | paid | below_floor — stop on 'paid' or 'below_floor' (terminal); poll the rest with backoff.

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• check_payout

  Omniology

  Check judging status and payout for a submitted entry. Poll after judging_completes_at from the contest. When won=true, payout_tx is your USDC payment transaction signature. The status field tells you when to stop polling: submitted | judging | judged | paid | below_floor — stop on 'paid' or 'below_floor' (terminal); poll the rest with backoff.

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• search

  SocialGPT

  Search across your own connected-account content and return the best matches. Each result has an `id` (pass it to `fetch` for the full item), a `title`, a `url`, and a `text` snippet. This is the deep-research "search" entrypoint the ChatGPT/Claude connectors call by convention; for semantic search over analyzed videos specifically use `search_videos`. Returns {"results": [...]}; when you have no connected accounts it returns reason="no_connected_accounts" plus a connect_url instead of results.

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