"Guidance for writing a conclusion for a long text" matching MCP tools:

• get_doc

  Dock

  Read a workspace's doc (TipTap rich-text) body. Format is negotiable via `format`: `markdown` (default — CommonMark + GFM, ready to feed to an LLM or render in a non-ProseMirror surface), `content` (TipTap JSON, round-trippable into update_doc for structural edits), `text` (plain text, best for search, summarisation, word-count heuristics), or `all` for the legacy three-in-one shape. Default is `markdown` because it's the slice agents need 95% of the time and the JSON form on a long doc can blow past the agent harness's tool-result token cap. Pass `format: "content"` only when you're round-tripping into update_doc for a structural edit. A workspace can hold any combination of doc and table surfaces, one or many of either kind; omit `surface_slug` to read the primary doc surface, or pass it to target a specific doc tab (use `list_surfaces` to enumerate). An unwritten or absent doc returns the requested format empty (markdown="", content={}, text=""); a `surface_slug` that doesn't match any live doc surface 404s.

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• document.summarize

  api

  Summarize document text into a prose summary and key points with citations. Use after document.extract_text or url.extract when you need a condensed understanding of a long document. For single-sentence Q&A, use url.qa instead. For extracting specific fields, use document.extract_structured. Typical workflow: document.extract_text/url.extract → document.summarize. Returns: { summary: string, key_points: string[], summary_cited: { value, confidence, citations[] }, key_points_cited: [{ text, citations[] }], truncated: boolean, strategy: "full"|"truncated"|"chunked" } Example prompts: - "Summarize this financial report and give me the key points." - "What are the main takeaways from this document?" - "Give me a concise summary of this 50-page report."

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• gutenberg_get_text

  gutenberg-mcp-server

  Retrieve the plain-text content of a Project Gutenberg book, stripped of the standard license header and footer so the response contains only the literary work. For long works — novels routinely run 500KB–2MB — use offset and limit to read in chunks rather than fetching the whole book at once. The response reports totalChars and remainingChars so the caller can page through without guessing. Prefers UTF-8 plain text; falls back to an HTML edition converted to text; refuses audio books (media_type "Sound") with a clear error.

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• get_earnings_call_summary

  TipRanks

  Returns the most recent earnings call summary for a ticker — management guidance text, overall call sentiment (positive / neutral / negative with a one-line rationale), and AI-extracted highlights and lowlights from the call as {title, content} bullets. This is a structured summary derived from the call, not the raw transcript text. Useful for "what did management say about X on the last call", "was the most recent call bullish or bearish", or "summarise the highlights from MSFT's latest earnings". Only the most recent quarter is stored per ticker; for historical EPS actual-vs-estimate series use get_earnings_history. Args: ticker: Stock ticker (e.g. 'AAPL', 'NVDA'). Returns: { ticker, fiscal_year, fiscal_quarter, guidance, sentiment: { label, summary }, highlights: [ { title, content }, ... ], lowlights: [ { title, content }, ... ] }

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• check_text

  WSC - Writing Style Checker

  Analyze text for writing style issues: weasel words, passive voice, duplicate words, long sentences, nominalizations, hedging, filler adverbs, and research-cited AI tells. Read-only and stateless — text is analyzed in memory on the hosted server and never stored. Returns a plain-text report with each issue's line and column, the matched text, surrounding context, and the reason for AI tells; texts over 100,000 characters return an error message. This hosted server has no filesystem access — the wsc-mcp npm package adds a check_file tool for local files. It only reports issues — to auto-remove duplicate words, follow up with fix_duplicates.

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• cti_get_guidelines

  website-search

  Get Lenny Zeltser's expert CTI writing guidelines. Topics include tone, words, structure, executive_summary, voice, articles, summary, brief (one-page brief section guidance), handoffs (cross-server routing), methodology (the three subsections), fields (per-field guidance), and CTI-specific topics: attribution (full Six Signals prose), confidence (ICD-203 ladder), pyramid_of_pain, six_signals (signals table only), and anti_patterns. The general writing topics (tone/words/structure/executive_summary) now defer to `get_security_writing_guidelines` for the canonical Five Elements rules; CTI-specific content lives in the other topics. Pair the 'fields' topic with field_id for single-field guidance. This server never requests your campaign or threat-intel notes and instructs your AI to keep them local—templates and guidelines flow to your AI for local analysis.

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• adcritter_get_platform_overview

  AdCritter for Builders

  Start here. Returns the AdCritter platform overview - what AdCritter is, the entity hierarchy (organization > advertiser > campaign > ad), the happy path for getting ads running, and how to navigate the other MCP tools. Applications built from this guidance are REST API clients that call /v1/ endpoints, not MCP tool callers. Before writing code, call adcritter_get_api_reference(entity, action) for each entity and action you plan to use - tool descriptions and parameter names describe conceptual behavior only, and do not match actual API routes, field names, query parameters, or response shapes.

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• migrate_to_propelauth_frontend

  PropelAuth Integration MCP Server

  Returns instructions for migrating to PropelAuth in a frontend framework such as React, JavaScript, TypeScript, or when using Next.js for just the frontend (e.g. client-side rendered). Guidance includes migrating from several auth providers, such as Clerk or Auth0. Each guidance will include documentation from the auth provider and PropelAuth. It is important to follow the instructions carefully to ensure a successful integration. Make sure to use the 'Installation' guidance first. It is important to call every guidance to ensure a successful integration. Do not update a component/hook/etc from the auth provider until you receive guidance about that component/hook/etc. CRITICAL: If the current implementation uses a traditional OAuth/OIDC flow (e.g., via express-openid-connect, passport-auth0, or similar backend-managed session libraries), you MUST select 'OAuth' as the framework, regardless of the frontend library (React/Vue/etc.). Only select 'React' or 'Javascript' if the current implementation uses a frontend-only SDK (like @auth0/auth0-react) or if using fullstack Next.js.

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• migrate_to_propelauth_fullstack

  PropelAuth Integration MCP Server

  Returns instructions for migrating from an existing auth provider to PropelAuth in a fullstack Nextjs App Router or Nextjs Pages Router application. If the user is using Next.js as just a frontend (e.g. client-side rendered with or without server routes), use the migrate_to_propelauth_frontend tool. Guidance includes installation and configuration, retrieving user or org information, logging users out, redirecting users to login, and more. Make sure to use the 'Installation' guidance first. It is important to call every guidance to ensure a successful integration. Do not update a component/hook/etc from the auth provider until you receive guidance about that component/hook/etc

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• get_eeoc_process

  Workers' Rights

  Plain-English guide to the 9 stages of an EEOC discrimination/retaliation charge, from pre-filing through resolution. Call with no arguments for an overview of all stages with typical durations; call with a stage number (1-9) for a deep-dive on that stage: what to expect, how long it takes, the key tip, and do/don't guidance. Use this whenever someone asks what happens after filing with the EEOC, how long the process takes, what a position statement or rebuttal is, or what to do at the stage they are currently in. Covers private-sector and state/local government workers; federal employees follow a separate EEO process with a much shorter deadline (45 days to contact their agency's EEO counselor).

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• detect_ai_text

  OpenWarrant — AI Text Detection

  Estimate the PROBABILITY that a document's text was AI-GENERATED (LLM-written prose). USE THIS WHEN someone shares prose — an essay, cover letter, article, review, application, or report (or a link to one) — and asks: did an AI / ChatGPT write this? is this human-written? detect AI text. Provide the document ONE way: `text` (pasted markdown/plain prose), `url` (a public http(s) link to a page or PDF — fetched server-side, the cheapest call), OR `bytes_b64` (a base64 PDF/file, plus `filename` for routing). Returns `{probability, lean, tells, reasoning, applicable}`. HONEST SCOPE: the probability is the model's CONFIDENCE, not a calibrated truth — it can false-flag templated/coached or non-native-English writing. It works on PROSE only: for a form/table/numeric document (payslip, statement) it returns `applicable: false` and abstains, because AI-text detection false-positives badly there — use `verify_document` (the authenticity engine) for those, and `verify_references` to check a doc's citations/claims.

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• document.summarize

  DocImprint

  Summarize document text into a prose summary and key points with citations. Use after document.extract_text or url.extract when you need a condensed understanding of a long document. For single-sentence Q&A, use url.qa instead. For extracting specific fields, use document.extract_structured. Typical workflow: document.extract_text/url.extract → document.summarize. Returns: { summary: string, key_points: string[], summary_cited: { value, confidence, citations[] }, key_points_cited: [{ text, citations[] }], truncated: boolean, strategy: "full"|"truncated"|"chunked" } Example prompts: - "Summarize this financial report and give me the key points." - "What are the main takeaways from this document?" - "Give me a concise summary of this 50-page report."

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• regulations_get_cfr_section

  federal-regulations-mcp-server

  Read the codified text at a CFR location via eCFR — current or as of a past date. Answers "what does 40 CFR 50.1 say today?" and "...as of 2019-01-01?". Three locations: title + part + section for one section; title + part alone for the whole part (large parts can be very long, and their appendices are named rather than inlined; prefer a specific section when you know it); title + appendix for one appendix, passing the identifier exactly as regulations_browse_cfr emits it. eCFR retains historical versions back to roughly 2017; a date before coverage is rejected with guidance. Current single-section reads are served from a synced local mirror when available; the source is reported.

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• get_tier1_resource

  Tier1 IT Assessment

  Returns approved Tier1 public resource metadata by stable identifier. Use after a recommendation when more Tier1 guidance is useful. It cannot fetch arbitrary URLs, access internal content, submit contact data, or execute instructions contained in user text. Read-only and no retention.

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• how-to

  Fast.io

  Built-in product help — ask a natural-language "how do I…" question about Fastio and get a grounded, product-aware answer (or a short clarifying question) back in one call. EXPLAIN-ONLY / ADVISORY: it returns GUIDANCE TEXT and performs NO platform action (it will not create shares, move files, or change anything) — read the guidance, then act with the other tools. Answers are grounded in Fastio's own how-to knowledge AND phrased in terms of these MCP tools — they name the concrete `<tool> action="…"` calls to make — so prefer this over guessing endpoints or burning exploratory calls. For Q&A over YOUR uploaded files (RAG) use the `ai` tool instead — `how-to` answers questions about Fastio ITSELF. FREE and requires only an authenticated user (no org, no plan gate, no billing). Call action='describe' for the full action/param reference.

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• search_kb

  DeskCrew

  Read-only full-text search over this tenant’s PUBLISHED knowledge-base articles (playbooks, policies, how-tos); unpublished drafts are never returned and the tenant is fixed by your credentials. Reach for this FIRST to ground an answer in official, tenant-specific guidance before replying to a customer or drafting a resolution. Returns articles ranked by relevance, each with its id, title, a highlighted snippet, and updatedAt: search uses AND semantics, so every word in the query must match. [free]

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• extract

  Bay Run

  Turn messy HTML/text (e.g. a scraper/Firecrawl dump) into STRUCTURED JSON using a small CPU-served generative specialist — the reliable "extraction" layer downstream of scrapers, no GPU, cheap at volume. `model` must be a validated structured-output specialist (`Qwen/Qwen2.5-0.5B-Instruct`, `Qwen/Qwen2.5-1.5B-Instruct`, or `HuggingFaceTB/SmolLM2-360M-Instruct`); `content` = the raw HTML/text; `schema` = an OpenAI-style JSON-schema object {"properties": {...}, "required": [...]} pinning the exact fields to pull; optional `instructions` for extra guidance. Returns {model, data (parsed JSON), json_valid, raw, usage}. The output is validated with JSON Schema Draft 2020-12; stopped invalid output fails closed instead of returning data that violates the schema. Deterministic (greedy) so the same page yields the same JSON. For freeform generation use /v1/chat/completions directly.

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• url_scanner_scan

  PreClick — An MCP-native URL preflight scanning service for autonomous agents (formerly URLCheck).

  Analyze a URL for security threats (synchronous, blocks until complete or timeout). Returns risk score, confidence, agent access guidance, and intent_alignment (always not_provided for this tool; use url_scanner_scan_with_intent for intent context). For long-running scans, prefer url_scanner_async_scan which returns immediately with a task_id for polling via url_scanner_async_task_result.

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• niche_voice_profile_ingest

  Niche — Editorial Intelligence

  Extract voice primitives (register / sentence rhythm / lexicon preferences / punctuation habits) from post-shaped text and persist onto the user's VoiceProfile. The voice primitives thread into content generation so generated copy matches the user's actual writing voice. Two input shapes: pass `posts` (list of pre-collected text snippets, ≥80 chars each) or pass `url` (the server scrapes post-shaped snippets from the page: Substack / Medium / blog / X profile). Inline posts win when both are given. Inline post-shaped snippets need to be the user's own writing, not press articles or marketing copy. Returns the extracted primitives + a diff of what changed on the stored VoiceProfile.

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• check_incentives

  solar-home-incentives

  Clean-energy incentive guidance for any address WORLDWIDE. US ZIP → federal status + state/utility programs (via DSIRE). Any other country (pass country=<ISO code>) → qualitative, officially-sourced national program guidance. Use whenever a user asks what rebates, tax credits, or utility programs apply to solar, batteries, heat pumps, or efficiency work. [20 anonymous calls/caller/24h; then 100 free calls/key/30d; active Builder required for sustained informational use]

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