Skip to main content
Glama
458,051 tools. Updated 2026-08-14 20:18

"Guide to Executing and Reading Terminal Commands" matching MCP tools:

  • List taxonomy facets and their value slugs across TCLP content. Facets are taxonomy categories like `sector`, `practice_area`, `application`, and `jurisdiction`. Each facet returns the list of slugs that actually appear on the graph, with counts. Use this to discover the vocabulary, then call `taxonomy_content` with chosen slugs. Args: scope: Which labels to include — `clause` (ClauseName only), `guide` (Guide only), or `all` (both, the default). Returns: JSON with "meta" and "facets". Each facet has `name`, `applies_to` (list of Neo4j labels carrying it), and `values` (list of `{slug, count}`, sorted by count desc).
    Connector
  • Use only after works_public_eligibility returns eligible. Download that immutable public GitHub snapshot, run the selected pinned static contract without executing repository commands, and return a signed receipt. Return the report field verbatim and stop.
    Connector
  • 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.
    Connector
  • 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.
    Connector
  • Call this BEFORE using `buy`; returns the latest usage guide for shopping and checking out with AgentCard.
    Connector
  • The store's front door as text: the full menu with prices, how x402 payment works here, the free shelf, and the house promises. Free. Completes when the guide text returns. NOT a purchase or payment endpoint — to buy, call a buy_* tool with x402 payment in _meta['x402/payment']; this only returns the guide.
    Connector

Matching MCP Servers

  • F
    license
    A
    quality
    D
    maintenance
    An MCP server for tracking and managing AI command usage history using a PostgreSQL database. It enables users to log, search, and view statistics for various AI-related commands and their execution contexts.
    5
  • A
    license
    B
    quality
    D
    maintenance
    A 4-stage reading companion that helps users set reading goals, discover books, track progress, and deepen learning through reflection, integrated with Claude Desktop.
    21
    1
    MIT

Matching MCP Connectors

  • Live geopolitical and markets intelligence wire: 35k+ wire items, event threads, 55k+ articles.

  • Trust signals for AI agents: an open agent-readiness standard and developer tool guide. Read-only.

  • Poll with only the stable scanId returned by certscore_scan_site. Active responses include phase, heartbeat, estimated progress, stalled state, and retry delay. Terminal responses include the CertScore score, risk, coverage, timestamps, report URL, and an explicit next action. Stop polling at any terminal status.
    Connector
  • Authoritative customer-facing permission and output policy summary for this Red session. Use when the user asks what they can do, what tools they have, what permissions are enabled, or whether technical details/code should be shown. Summarise the currently enabled read, write, delete, email, and batch capabilities in plain business language. Do not list MCP tool names, endpoint names, tool counts, JSON, schemas, local file paths, terminal commands, environment variables, or a full capability catalogue. Customer-facing answers must be plain-English business responses with evidence, assumptions, uncertainty, and limitations. Internal analysis is allowed, but code/scripts/commands/intermediate files must not be exposed to customer users unless dev mode is enabled. Assistant-only connection diagnostics (never include in customer answers): a missing result or empty list does not by itself mean the connection has expired; only a confirmed authentication failure should be treated as an invalid company credential.
    Connector
  • List taxonomy facets and their value slugs across TCLP content. Facets are taxonomy categories like `sector`, `practice_area`, `application`, and `jurisdiction`. Each facet returns the list of slugs that actually appear on the graph, with counts. Use this to discover the vocabulary, then call `taxonomy_content` with chosen slugs. Args: scope: Which labels to include — `clause` (ClauseName only), `guide` (Guide only), or `all` (both, the default). Returns: JSON with "meta" and "facets". Each facet has `name`, `applies_to` (list of Neo4j labels carrying it), and `values` (list of `{slug, count}`, sorted by count desc).
    Connector
  • 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.
    Connector
  • Get plain-language explanations of active predictive signals. Each narrative explains the mechanism behind a signal — why the predictor leads the target, what economic logic connects them, and what the current reading implies. Designed for non-quantitative users who want to understand the 'why' behind each signal without reading F-statistics. Returns trigger context, predictor value, direction, and a narrative paragraph suitable for reports and briefings.
    Connector
  • START HERE. Interactive guide for an agent that just discovered $BOBAI: what you can ask, what you can do, and which tool to call for each — plus the must-know fee-on-transfer rule.
    Connector
  • Fetch the full markdown body of a specific recipe by slug (typically a slug returned by recipes_search). The body contains Prerequisites, Provision, Configure, Verify, and Troubleshoot sections you should follow step-by-step, executing commands via SSH on the user's VM. Always read the full body before launching infrastructure — the recipe specifies the correct image, sku_class, and minimum specs that should drive your instances_launch call.
    Connector
  • Search detailed documentation for Strudel live coding or ABC/ABCJS notation. Returns relevant code examples and explanations from the official docs. Use this when the curated guides (get-strudel-guide, get-music-guide) don't cover what you need — for specific functions, advanced techniques, or when you're unsure about syntax. Powered by semantic search over strudel.cc and ABCJS docs.
    Connector
  • Get a USGS site's current reading ranked against its full period-of-record daily-mean percentiles for the same calendar day — a "how unusual is this" percentileClass (record-high to record-low), not a flood-stage or drought determination (this tool fetches no authoritative thresholds). The reading is instantaneous but the percentiles are daily-mean, so the ranking is approximate (see historicalContext.comparisonBasis). When the record is too short to rank, returns the reading with historicalContext=null instead of an error. Use water_find_sites and water_list_parameters to resolve inputs.
    Connector
  • Returns an official GuruWalk support guide for a specific traveler-support topic. GuruWalk is a platform for free walking tours and paid activities; these guides are GuruWalk's own source of truth on how bookings, cancellations, account settings and contacting guides actually work, including current policies and the exact URLs travelers should use. These guides apply only to bookings and accounts on guruwalk.com. Available topics: - account_settings: The traveler wants to manage their GuruWalk account: edit their details (name, surname, phone, city, password), change their email, stop receiving emails / unsubscribe, or delete their account; or they can't access their account. These are concrete steps you shouldn't improvise: consult this before answering. - contact_guru: The traveler wants to contact or coordinate something with the guide of their GuruWalk booking, or thinks they are talking directly to the guide: they can't find them at the meeting point, the guide didn't show up, they're running late, they treat you as if you were the guide, ask for the tour photos, or ask about bringing a pet or paying the guide, or have a question only the guide can answer. - free_tour_modification: The traveler wants to modify or reschedule their GuruWalk free tour — change the day, time, language or number of people — or asks how to do it. - group_booking: The traveler wants to book or extend a GuruWalk booking for a group (they usually say how many; treat it as a large group from around 6 people), asks how to book for many people, can't book for the whole group, sees a large-group notice or is asked for a card or payment for the group, or had a booking cancelled as "group or duplicate". The rules aren't intuitive; consult this before advising. - paid_cancellation: The traveler wants to cancel or change a paid activity booked on GuruWalk, asks about a refund, or can't cancel from their account. Call this when the traveler raises a support topic covered above. Pass the exact topic; the guide content is returned.
    Connector
  • Return the authenticated person or service agent, organization, workspace, role, and granted scopes. Call this before reading or publishing to confirm attribution and tenancy.
    Connector
  • Runs a two-stage discounted cash flow on numbers you provide and returns the fair value per share, the margin of safety against the price you gave, and how much of the value sits in the terminal stage. Cash flow grows at your growth rate for the stage-one years, then forever at your terminal rate, with the terminal value from the Gordon Growth Model discounted back over the stage-one years. Use when the user wants to value a company under their own assumptions, test how sensitive a valuation is to the discount or growth rate, or check the arithmetic of a DCF they are building. Do not use it to look up what a company is worth on Zyberno's own assumptions, which is get_stock_valuation and uses a different, fade-based model; the two will not agree and are not meant to. This computes your assumptions, it does not endorse them. The output is arithmetic, and a two-stage DCF is highly sensitive to the discount and terminal rates, so treat a single result as one point rather than an answer.
    Connector
  • Read the current state of an ingestion job (paper creation or document ingestion). Returns the status plus a derived `awaiting` gate ('triage' | 'confirmation' | null), whether it is terminal, and the next action to take. Poll this after starting a job: a paper-creation job parks at `awaiting_confirmation` (then call paper_confirm) — it does NOT run to `complete` on its own. Stop polling on a terminal status (complete | failed | cancelled) or when an action is required.
    Connector