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

• 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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• 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. Sailing times are ISO 8601 UTC while tripDate is the Pacific service day, so evening sailings carry the next UTC date — convert to America/Los_Angeles before quoting a clock time. Cancellations are not carried here — WSF drops a cancelled sailing from the schedule instead of flagging it, so a listed sailing is not confirmation that it will run. Check wsdot_get_ferry_alerts for disruptions; those are scoped to a route, not an individual sailing.

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• get_asma_ul_husna

  Wasilah

  Look up the 99 Names of Allah (Asma ul Husna). Returns Arabic, transliteration, English and Bengali. Give a number for one name, a search term to match by meaning or transliteration, or neither to get all 99.

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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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• 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. `fcf_source` (default "trend"): "trend" compounds a single FCF base by `stage1_growth_rate` every year (the original behavior, unchanged). "three_statement" instead runs a full linked Income Statement / Balance Sheet / Cash Flow projection (`project_three_statement`'s engine) and feeds its year-by-year FCF stream into the same PV math — `stage1_growth_rate` is then ignored (kept for echo only) because revenue growth + margins drive FCF instead of a flat compounding rate. The projection detail (including per-year `tie_out_ok`) is returned in `three_statement_detail` when used. Tier: sp500+.

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• eia_search_routes

  eia-energy-mcp-server

  Fuzzy text search across route names, descriptions, and category labels. Resolves natural-language queries like "electricity retail sales by state" or "natural gas imports" to matching route paths. Multi-term queries are also matched term by term, so combining a commodity, a metric, and a sector — "electricity price residential", "coal generation industrial sector" — reaches the route carrying that data even when no single entry reads like the whole phrase. STEO series names are indexed so queries like "ethanol net imports" or "crude oil production forecast" also resolve, and so are facet values, so a fuel type or sector term like "wind" or "anthracite coal" resolves to the route that exposes it, with filter_hint carrying the filter to pass on. Results include isLeaf so you know whether to browse further or query directly. Results with score > 0.72 are weak matches — try a more specific query or use eia_browse_routes to explore the taxonomy. The first call after server start waits 24-30s while the index warms, and at most 45s; every later call returns in milliseconds. Check indexComplete before reading anything into a short or empty result set.

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• wsdot_get_ferry_terminals

  wsdot-mcp-server

  Returns all WSF ferry terminals with their numeric IDs, names, and abbreviations. Call this first to resolve human-readable terminal names (e.g. "Bainbridge Island", "Seattle", "Kingston") to the numeric terminal IDs required by the schedule and space tools. The terminal list is small (20 terminals) and rarely changes.

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• wsdot_get_terminal_space

  wsdot-mcp-server

  Returns real-time drive-up and reservable vehicle space available at WSF terminals for upcoming sailings. Use for "will I make the ferry?" or "how full is the next sailing?" questions. Optionally filter to a specific terminal by ID (use wsdot_get_ferry_terminals for the ID). driveUpSpaceCount is the key field — zero means the drive-up lane is full. Destinations are arrivingTerminalIds, not the itineraryLabel string: a sailing can serve several terminals, and those IDs are what wsdot_get_ferry_schedule accepts. Results are paged by terminal (default 5, max 20): offset/limit select whole terminals and totalCount counts matching terminals, not sailings — every sailing of a returned terminal is included, so page size varies with how many departures each terminal carries.

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• keyword_list

  Prowlo — Reddit & X for AI agents

  [DEPRECATED — renamed tag_rule_list. Will be removed after 2026-10-07.] List your org's TAGGING RULES (the dashboard's 'Tagging rules') — labels applied to posts your Watchers already ingest. NOT the dashboard's Keyword Monitor: for the keywords that search all of Reddit daily, use keyword_monitor_list. Each rule tags matching Dataset records whose title or body mentions its term as a whole word. Returns the term, active status, and match statistics. Changes take effect on the next scheduled processing cycle. Existing opportunity scores and matches are not retroactively updated. (requires a free Prowlo account — call it to get a signup link)

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• tag_rule_list

  Prowlo — Reddit & X for AI agents

  List your org's TAGGING RULES (the dashboard's 'Tagging rules') — labels applied to posts your Watchers already ingest. NOT the dashboard's Keyword Monitor: for the keywords that search all of Reddit daily, use keyword_monitor_list. Each rule tags matching Dataset records whose title or body mentions its term as a whole word. Returns the term, active status, and match statistics. Changes take effect on the next scheduled processing cycle. Existing opportunity scores and matches are not retroactively updated. (requires a free Prowlo account — call it to get a signup link)

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• string_proteins_for_term

  STRING Database MCP Server

  Retrieve proteins annotated with a functional term or descriptive text in a single species. You can query for tissues, compartments, diseases, processes, pathways, and domains. IMPORTANT: For cross-species comparisons, run this tool separately for each species. Select relevant model organisms to search or ask user to provide the selection. The results reflect annotation depth within each category; use caution when interpreting. If no results are found, try simplifying the query. For tissue queries, follow BRENDA tissue nomenclature and omit the word "tissue" (e.g. use "skin" instead of "skin tissue"). Output fields: - category: Source database of the matched functional term (e.g. GO, KEGG, Reactome, Pfam, InterPro). - term: Exact identifier for the functional term. - description: The free text description of the term. - proteinCount: Number of proteins annotated with that term - preferredNames: Full protein-name list when `detail_for_term` is set - stringIds: STRING protein identifiers when returned - preferredNames_omitted: True when a row omits the protein-name list - stringIds_omitted: True when STRING identifiers are omitted

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• search_references

  Islam West Africa Collection (IWAC)

  Search academic references (journal articles, book chapters, theses, books, reports) by keyword and metadata. `keyword` is a single substring match over title + abstract, so search ONE term per call (combined terms like 'pèlerinage Mecque' miss results). References are multilingual: try French and English title/abstract keywords when relevant; metadata/filter values such as `reference_type` and `language` use French labels. Results include a short abstract snippet — use get_reference for the full abstract and bibliographic detail.

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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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• browse_collections

  Remember Me Collections

  Browse published Bible verse collections. Search by keyword, filter by language, sort by popularity. Each result includes the collection's raw cover `image` — the URL the publisher set, or null if they set none (the app may still show an auto-generated cover when null). This is the stored value, not the computed display image. Args: search: Search term to filter by name, description, or publisher name. language: Language code prefix (e.g. "en", "de", "ja", "zh"). ordering: Sort order: -downloads (default), -created, name. limit: Number of results (1-100, default 20). offset: Starting position for pagination.

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• browse_collections

  Remember Me Collections

  Browse published Bible verse collections. Search by keyword, filter by language, sort by popularity. Each result includes the collection's raw cover `image` — the URL the publisher set, or null if they set none (the app may still show an auto-generated cover when null). This is the stored value, not the computed display image. Args: search: Search term to filter by name, description, or publisher name. language: Language code prefix (e.g. "en", "de", "ja", "zh"). ordering: Sort order: -downloads (default), -created, name. limit: Number of results (1-100, default 20). offset: Starting position for pagination.

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• search_translations

  Source Library

  RETURNS QUOTABLE PASSAGES (page-level snippets + citation URLs), matched by KEYWORD/term. PICK THIS to find a quote or textual evidence on a topic across the whole library. → If the modern word won't literally appear in historical texts, use search_concept (matches by meaning); to list which BOOKS cover a topic use search_library; to dig inside one known book use search_within_book; if the user named an author/work, get_book first (its AI summary is usually the right first read). Query tips: single distinctive terms ("memory palace", "wax tablet") work best; multi-word natural-English queries ("unity of the intellect") may return fewer results because matching is term-based, not phrase-based. Each snippet has a snippet_type — "translation"/"ocr" means it is a verbatim extract from the source text; "summary" means it is AI-generated description (do not quote those as the author's words). Response includes total_matches, returned, and offset for pagination. Cross-cultural tip: for pre-modern or non-Western topics, search source-tradition vocabulary rather than modern English terms — e.g. for seminal economy search "jing" or "bindu" or "istimnāʾ", not "semen retention"; for female homoeroticism search "tribade" or "sahq", not "lesbian". The corpus is indexed via period translations that use tradition-internal terminology.

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• keyword_demand

  amazon-product-research-mcp

  Keywords observed in Amazon's own autocomplete suggestions for a seed term, per marketplace: the current suggestion list(s) for the seed's prefix (each term with its position 1-10 within that list) plus related observed vocabulary starting with the seed, with the marketplaces each term was observed in. Use for listing/backend keyword language, 'what do buyers type for X', or seeding niche/product research with real buyer phrases. No volume figures and no organic-ranking data — observed suggestion vocabulary only. Amazon marketplaces only.

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• pathrule_get_local_runtime_upgrade

  Pathrule

  Explain what Pathrule CLI (power-user, terminal-first) and Pathrule Studio (GUI) unlock beyond Remote MCP. Call this when the user asks 'is there a better way?', 'why do I need to install something?', wants hook-level automation, or wants to compare surfaces. The response splits the pitch by audience (CLI for terminal-first, Pathrule Studio for GUI) and explains the real token-savings angle: hooks fire before every AI tool call and inject context for free, while remote MCP is manual mode where the AI spends tokens on each context fetch.

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• tf_harnesses

  terminalfeed

  Returns a snapshot of public agentic-coding benchmark scores across SWE-bench Verified, Terminal-Bench, Aider Polyglot, and METR HCAST. Each row pairs a harness with a model. Same model can score very differently on different harnesses; that gap is the value-add. Pass ?view=summary for top 10 combined leaderboard plus biggest harness gaps; ?view=gaps for full per-model harness deltas; ?view=combined for normalized cross-benchmark ranking; ?view=raw (default) for the full benchmark/result graph. Source: hand-curated from upstream leaderboards (swebench.com, terminal-bench.org, aider.chat, metr.org). Cache TTL 12h. Use when the agent needs to recommend a harness/model combo or explain why two agents using the same model perform differently.

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• get_run_status

  Hydrata - ANUGA Flood Simulation

  Lightweight status check for a simulation run (fast, <50ms). Use this for polling instead of get_run. Returns only: id, status, progress_pct (0-100), eta_seconds, error_message, and compute_backend. Poll every 5-10 seconds. Terminal states: complete, error, cancelled.

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