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195,990 tools. Last updated 2026-06-12 09:23

"A server for reading documents" matching MCP tools:

  • Return the description and install snippets for a named tool or server. For tools: the description and the server it belongs to. For servers: local (stdio, via npx) install snippets for every published server, plus remote (HTTP) connection snippets when a hosted endpoint exists — for every supported client, or one client via the client parameter. Call cyanheads_search first to find valid names.
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  • Signed snapshot of corpus liveness: distinct_cells, distinct_bands, facts_scanned, top per-band counts, manifest CIDs. Same payload that backs /v1/stream's corpus.state tick (signed). Use this for a one-shot poll instead of holding an SSE connection. When to use: Call when an agent needs a single liveness reading to surface in a dashboard, attach to a report, or decide whether to refresh local caches. Includes ed25519 signature over a deterministic preimage so the snapshot is verifiable. For a continuous feed, GET /v1/stream over Server-Sent Events instead.
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  • 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 search.files / search.threads / search.links for that.
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  • 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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  • Latest glucose reading for a patient (value, trend, flags). For history use librelink_business_get_glucose_graph. Read-only CGM data — clinic/follower account; not for medical decisions without clinician review. Bulk support: accepts patient_ids for batched execution.
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  • 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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Matching MCP Servers

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  • 斯特丹STERDAN天猫旗舰店产品咨询MCP Server。洛阳30年源头工厂,高端钢制办公家具,1374个SKU,涵盖保密柜、更衣柜、公寓床、货架、快递柜。BIFMA认证,出口35+国家。8个工具:产品目录查询、场景推荐、认证资质、采购政策、维护指南等。

  • 台灣勞保、健保、勞退、職災與二代健保補充保費試算,含薪資扣繳、破月與勞保老年給付。資料取自主管機關公告,對官方範例逐位元驗證。

  • 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 search.files / search.threads / search.links for that.
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  • Get Lenny Zeltser's Security Assessment cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `assessment_load_context`. This server never requests your assessment notes or report and instructs your AI to keep them local—the templates and guidelines flow to your AI for local analysis.
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  • Return a single recommended VPS provider for users who do not yet have a server. Call this ONLY when the user explicitly says they have no server. The user buys the VPS at this provider and comes back with IP + password.
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  • Return the single most recent observation for one or more BLS series. Use for "what is X right now" questions — the current unemployment rate, the latest CPI reading, etc. Each series consumes one API query against the 500/day limit; for the current value of many series, bls_get_series with a 1-year window is more quota-efficient (one query for up to 50 series). Recommended limit: 10 series; maximum: 50.
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  • Discover sheet names and used dimensions before reading or editing a WorkPaper. Returns metadata only; use read_range or read_cell for values.
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  • Get Lenny Zeltser's Malware cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `malware_load_context`. This server never requests your sample, analysis notes, or indicators and instructs your AI to keep them local—guidelines and the report template flow to your AI for local analysis.
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  • Fetch HTTP response headers for a URL. Use when inspecting server configuration, security headers, or caching policies.
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  • Synthesized post-cutoff answer with inline citations. Use this when your model is small / cheap / weaker at tool-result synthesis (Llama, Gemini Flash, Mistral, Nemotron, Qwen). Fillin runs a server-side LLM pass over the retrieved post-cutoff documents and returns a 150-250 word answer with [title](url) citations already embedded — you can quote it directly. Premium models (Opus, Sonnet, GPT-4o) usually get better results from `fillin_query` and synthesizing themselves, but this tool works for any caller. Costs more than fillin_query because of the synthesis pass. Returns: A dict with: - answer: the synthesized paragraph (str | None) - citations: list of {title, url} extracted from the answer - corpus_match: "strong" | "weak" | "none" — quality of retrieval - top_score: float — top reranked similarity score - model: the synthesizer model used (e.g. claude-haiku-4-5) - reason: set when answer is None (e.g. "no_relevant_docs") - results: raw post-cutoff documents (same shape as fillin_query) - cutoff, query, gap_days: echoes for context
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  • Persist income/expense lines as saved Zen data. Use after reading a user-provided statement, PDF, or described transactions — not to correct existing rows (use edit_transaction for that, or delete + recreate for direction flips). Groups lines under one operation; cashflow is attributed to operation_date month, not today.
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  • Semantic (vector) search across documents in a collection. Returns ranked text chunks. Free — no credits consumed. PREREQUISITE: Collection must be populated via REST API (POST /v1/collections/{id}/documents/{bundle_id}) and indexing must complete (async) before results appear. Use search_collection for raw matching chunks; use ask_collection for a synthesized cited answer. Returns: { results: [{ bundle_id, chunk_id, text, score: number (0–1), title? }] }
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  • Get Lenny Zeltser's CTI cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `cti_load_context`. 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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  • 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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  • 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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  • Return the full dossier projection for a meeting reading, in the requested cognitive lens. Same lens enum and default as describe_place / describe_corridor — eight total projections (seven stakeholder lenses — developer, investor, broker, attorney, business, resident, civic-leader — plus synthesis as the default). Returns the lens-projected body, full frontmatter (jurisdiction, board, meeting_date, document_type, key_signals, vote tallies), citation-stable claims[] (per the Phase 11 Citable Contract; populates as meeting claim scopes graduate), four-clock freshness, and the structured record_status block (record_type / meeting_status / outcome_status / minutes_available / vote_final) — the last prevents agents from summarizing agenda intent as completed action. Use to ground citations in a specific meeting's reading; pair with list_meetings or meeting_index for discovery.
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