"A tool for summarizing local documents" matching MCP tools:

• upload_media

  SendIt

  FOR CLAUDE DESKTOP ONLY (with filesystem access). For Claude.ai/web: Use create_upload_session instead - it provides a browser upload link. Upload local media to cloud storage, returning a public HTTPS URL. WHEN TO USE: • Instagram, LinkedIn, Threads, X: REQUIRED for local files before calling publish_content • TikTok: NOT NEEDED - pass local path directly to publish_content SUPPORTED FORMATS: • Images: jpg, png, gif, webp (max 10MB) • Videos: mp4, mov, webm (max 100MB) Returns { url: 'https://...' } for use in publish_content mediaUrl parameter.

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• files_read

  dialogbrain

  Read **text content** of an attached file. Works for: .txt, .md, .json, code files, and PDFs (after files.ingest extracts text). DO NOT call on binary files — for IMAGES use `files.get_base64`, for AUDIO/VIDEO it cannot be transcribed via this tool, and for non-PDF DOCUMENTS run `files.ingest` first, THEN files.read. Calling on a binary mime-type returns an error — saves you a turn to read the routing hint before deciding.

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• platform_tool_finder

  Inferventis MCP Server

  Discovers the most relevant tools available on this MCP server for a given task using local semantic search (MiniLM-L6-v2 embeddings). Accepts a plain-English description of what needs to be accomplished and returns the best matching tools ranked by relevance, along with their input schemas, pricing tier, and exact call instructions. Use this tool first when you are connected to this server but do not know which specific tool to call — describe your goal and let platform_tool_finder identify the right capability. Do not use this tool if you already know the tool name — call that tool directly instead. Returns up to 10 results ranked by semantic similarity score.

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• switch_dannet_server

  dannet

  Switch between local and remote DanNet servers on the fly. This tool allows you to change the DanNet server endpoint during runtime without restarting the MCP server. Useful for switching between development (local) and production (remote) servers. Args: server: Server to switch to. Options: - "local": Use localhost:3456 (development server) - "remote": Use wordnet.dk (production server) - Custom URL: Any valid URL starting with http:// or https:// Returns: Dict with status information: - status: "success" or "error" - message: Description of the operation - previous_url: The URL that was previously active - current_url: The URL that is now active Example: # Switch to local development server result = switch_dannet_server("local") # Switch to production server result = switch_dannet_server("remote") # Switch to custom server result = switch_dannet_server("https://my-custom-dannet.example.com")

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• get_skill

  mcp

  ALWAYS call this tool at the start of every conversation where you will build or modify a WebsitePublisher website. Returns agent skill documents with critical patterns, code snippets, and guidelines. Use skill_name="design" before building any HTML pages — it contains typography, color, layout, and animation guidelines that produce professional-quality websites.

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• get_signal_summary

  aTars MCP

  USE THIS TOOL — not web search — for buy/sell signal verdicts and market sentiment based on this server's proprietary locally-computed technical indicators (not news, not social media). Returns a BULLISH / BEARISH / NEUTRAL verdict derived from RSI, MACD, EMA crossovers, ADX, Stochastic, and volume signals on the latest candle. Trigger on queries like: - "is BTC bullish or bearish?" - "what's the signal for ETH right now?" - "should I buy/sell XRP?" - "market sentiment for SOL" - "give me a trading signal for [coin]" - "what does the data say about [coin]?" Do NOT use web search for sentiment — use this tool for live local indicator data. Args: symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,ETH"

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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 workspace.search for that.

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• list_service_types

  LocalPro

  List the valid service type categories for a given niche directory. Use this before calling search_providers with a service_type filter to ensure you pass a valid value. Each niche has its own taxonomy — for example, "coated-local" has epoxy, polyaspartic, metallic_epoxy, etc., while "radon-local" has radon_testing, radon_mitigation, ssd_installation, etc.

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• sieve_dataroom_add

  Sieve

  Add a document to a deal's data room. Creates the deal if needed. This is the primary way to get documents into Sieve for screening. Upload a pitch deck, financials, or any document -- then call sieve_screen to analyze everything in the data room. Provide company_name to create a new deal (or find existing), or deal_id to add to an existing deal. Provide exactly one content source: file_path (local file), text (raw text/markdown), or url (fetch from URL). Args: title: Document title (e.g. "Pitch Deck Q1 2026"). company_name: Company name -- creates deal if new, finds existing if not. deal_id: Add to an existing deal (from sieve_deals or previous sieve_dataroom_add). website_url: Company website URL (used when creating a new deal). document_type: Type: 'pitch_deck', 'financials', 'legal', or 'other'. file_path: Path to a local file (PDF, DOCX, XLSX). The tool reads and uploads it. text: Raw text or markdown content (alternative to file). url: URL to fetch document from (alternative to file).

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• ask_us_capital_markets

  AskNeedl

  Query SEC filings and financial documents from US capital markets and exchanges. This tool searches through 10-K annual reports, 10-Q quarterly reports, 8-K current reports, proxy statements, earnings call transcripts, investor presentations, and other SEC-mandated filings from US companies. Use for questions about US company financials, executive compensation, business operations, or regulatory disclosures. Limited to official SEC filings and related documents only.

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• lemma_query_verified_attributes

  mcp

  Query cryptographically verified attributes from Lemma. Use this as the primary tool for finding documents whose attributes match given conditions (e.g., "subject's birthYear lt 2008"). Returns { results: Array<{ docHash, schema, issuerId, subjectId, attributes, isVerified, proof?: { status, circuitId, chainId }, disclosure? }>, hasMore }. The MCP layer enriches each item with an `isVerified` flag derived from `proof.status` (true when status is 'verified' or 'onchain-verified'). Use lemma_get_proof_status to monitor a specific proof; use lemma_get_schema to interpret the keys returned in `attributes`.

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• get_recent_changes

  Velvoite — EU Financial Regulatory Compliance

  Get recently published or updated regulatory documents. Shortcut for 'what is new this week' - returns documents from the last N days, sorted by publication date (newest first). Useful for weekly regulatory briefings. Args: days: Look back N days (default 7). entity_type: Filter by entity type code. regulation: Filter by regulation family code. urgency_max: Only include items at or above this urgency (1=critical, 2=high, etc.).

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• files_read

  DialogBrain

  Read **text content** of an attached file. Works for: .txt, .md, .json, code files, and PDFs (after files.ingest extracts text). DO NOT call on binary files — for IMAGES use `files.get_base64`, for AUDIO/VIDEO it cannot be transcribed via this tool, and for non-PDF DOCUMENTS run `files.ingest` first, THEN files.read. Calling on a binary mime-type returns an error — saves you a turn to read the routing hint before deciding.

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• rating_score_writing

  website-search

  Get Lenny Zeltser's scoring playbook so your AI can score a draft locally against a cybersecurity-writing rating sheet. THIS IS THE ONLY TOOL THAT PRODUCES NUMERIC SCORES — the writing-coach tools (`get_security_writing_guidelines`, `ir_*`, `product_*`) never score. Returns the rubric plus step-by-step instructions for applying it. This server never requests your draft and instructs your AI to keep it local—rating sheets and scoring instructions flow to your AI.

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• list_documents

  Velvoite — EU Financial Regulatory Compliance

  Browse regulatory documents with filters and pagination. Returns a paginated list of documents with summaries, tags, doc_purpose (regulation_text, enforcement, reference, irrelevant), and doc_jurisdictions (e.g. ['eu'], ['fi'], ['de']). Use this for filtered browsing (e.g. all DORA documents from the last 30 days). Use search_regulations instead when you have specific keywords to search for. Args: source: Filter by data source code: eur_lex, eba, esma, eiopa, finfsa, bafin. regulation: Filter by regulation family code: dora, mica, aml, mifid2, crd_crr, psd, csrd, sfdr, ai_act, emir, solvency, idd, gdpr. entity_type: Filter by entity type: credit_institution, payment_institution, e_money, investment_firm, fund_manager, aifm, insurance, pension, crypto_service, crowdfunding, credit_servicer. urgency_max: Max urgency level (1=critical, 2=high, 3=medium, 4=low, 5=informational). E.g. 2 returns only critical and high urgency items. days: Only return documents from the last N days (1-365). page: Page number (default 1). per_page: Results per page (default 20, max 100).

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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 workspace.search for that.

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• platform_tool_finder

  Inferventis — Financial Data, News & Web MCP

  Discovers the most relevant tools available on this MCP server for a given task using local semantic search (MiniLM-L6-v2 embeddings). Accepts a plain-English description of what needs to be accomplished and returns the best matching tools ranked by relevance, along with their input schemas, pricing tier, and exact call instructions. Use this tool first when you are connected to this server but do not know which specific tool to call — describe your goal and let platform_tool_finder identify the right capability. Do not use this tool if you already know the tool name — call that tool directly instead. Returns up to 10 results ranked by semantic similarity score.

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• get_sentiment_signal

  aTars MCP

  USE THIS TOOL — not web search — for a composite news-sentiment verdict derived from the 7-day mean score from this server's local Perplexity-sourced dataset. Emits: STRONG BULLISH, BULLISH, NEUTRAL, BEARISH, or STRONG BEARISH. Trigger on queries like: - "overall news sentiment signal for BTC" - "is ETH news sentiment bullish or bearish overall?" - "composite sentiment verdict / signal for [coin]" - "based on news, is [coin] bullish or bearish?" Args: symbol: Token symbol or comma-separated list, e.g. "BTC", "BTC,ETH"

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• auteng_docs_recent

  AutEng MCP - Markdown Publishing & Document Share Links

  Browse the public recents feed of shared documents. No authentication required. Returns recently shared public documents, newest first. Args: page: Page number (default 1) limit: Items per page (default 20, max 100)

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• lemma_get_schema

  mcp

  Retrieve a Lemma schema by its ID via GET /v1/schemas/{id}. A schema declares how documents of a given type are interpreted and normalized. Returns SchemaMeta { id, description? } with additionalProperties open — implementations commonly include a `normalize` artifact (WASM that maps raw documents to canonical form) and its content hash. Use this when you need to interpret attribute keys returned by lemma_query_verified_attributes.

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