"A search for documents" matching MCP tools:

• check_document_package

  Document Integrity Validator

  Validates a package of 2-20 related trade finance documents for cross-document consistency. Call this BEFORE approving any multi-document trade finance transaction or cross-border shipment -- at the moment a set of 2-20 related documents arrives from an external party and funds have not been released. Use this when your agent has received a full trade finance package — such as invoice, bill of lading, and certificate of origin together — and must verify all documents are consistent with each other before releasing funds. Returns PASS/FLAG/FAIL verdict per document with mismatch details. Cross-checks all documents for consistency across numeric values, party names, reference numbers, dates, and commodity descriptions. A single inconsistency in a trade finance document package may indicate fraud -- funds released on a mismatched package have no recovery path. Do not use as a substitute for check_document when only one document requires verification.

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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 search.files / search.threads / search.links for that.

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• search

  Sofya

  Search the web for current information on any topic. Returns extracted page content, not just snippets. Best for factual lookups, specific questions, or when you need a list of sources. For open-ended questions that need synthesis across many sources, use the research tool instead. For news queries (current events, breaking news, politics, world events), set topic="news" to search news sources specifically. This returns recent articles with publication dates. Set include_answer=true to get an AI-synthesized answer alongside results (adds 5 credits). This is the sweet spot for most agent tasks, e.g. basic + include_answer = 8 credits, much cheaper than a full 25-credit research call. Returns: query, answer (if requested), results (array of {title, url, content, description, fetched, published_date}), search_depth, topic, elapsed_ms, credits_used, credits_remaining, altered_query. Args: query: The search query search_depth: "basic" (default) for extracted page content (3 credits), "snippets" for SERP snippets only without page fetching (1 credit) max_results: Number of results (default 10, max 20) include_answer: Generate an AI answer that synthesizes the search results (adds 5 credits) include_domains: Only include results from these domains (max 10) exclude_domains: Exclude results from these domains (max 10) topic: "general" for web search, "news" for news articles. use "news" for current events, breaking news, politics, or any time-sensitive query freshness: Filter by recency - "day", "week", "month", "year", or "YYYY-MM-DD:YYYY-MM-DD"

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• search_disciplinary_actions

  Licensy

  Search for known disciplinary actions against a physician (suspension, revocation, surrender, probation). Sourced from state medical board status text. Use this when: - Pre-employment screening - Recredentialing — required by most insurance contracts - Investigating a referral source Input: NPI (preferred) OR full name. Optional state filter. Output: array of {state, action_type, date, source_url}. Action types: suspension | revocation | surrender | probation | reprimand | other. Coverage note: this surfaces board-status-level signal. Underlying PDF documents are on the roadmap. Paid tier only (Pro or Enterprise).

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• search

  21st.dev

  Search the 21st.dev catalog across ALL entity types - React/shadcn components, themes, and templates - returning lightweight metadata ONLY (name, description, preview image, author, url/install, id, and price for templates). Use `type` to scope to one kind, or 'all' (default) to search everything. FREE. Retrieval differs by kind: for a component result call get_component with its `id` (that id is a demo id) for the PAID code; for a theme call get_theme with its `id` (a uuid) for the free CSS; templates have no code to fetch - open their `url`. NOTE: `author`/`mine`/`liked` bypass ranking and return a plain recency-ordered list (query/sort/tag/color are ignored when any of them is set); component listings via `mine`/`author` only ever show PUBLIC components - your own private/team components are discoverable via list_team_components, not search.

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• search_regulations

  Velvoite — EU Financial Regulatory Compliance

  Search the regulatory corpus using keyword / trigram matching. Uses PostgreSQL trigram similarity on document titles and summaries. Returns documents ranked by relevance with summaries and classification tags. Prefer list_documents with filters (regulation, entity_type, source) first. Only use this for free-text keyword search when structured filters aren't sufficient. Args: query: Search terms (e.g. 'strong customer authentication', 'ICT risk', 'AML reporting'). per_page: Number of results (default 20, max 100).

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• openstates_get_bill

  openstates-mcp-server

  Fetch full detail for a specific state bill. Accepts either the three-part path (jurisdiction + session + bill_id) or a direct OCD bill ID (openstates_id from search results). Use include to request votes, actions, sponsorships, documents, and versions in one call rather than searching again. include=votes returns the full vote tally and per-legislator positions. include=actions returns the complete action history. Prefer openstates_id when available to avoid session identifier lookup.

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• search

  DC Member API

  GET /search — Cross-resource omni-search Cross-resource search across profiles, rooms, messages (incl. private DMs + group DMs you're in), events, and chapters in one round trip. Returns the top-N matches per resource, grouped by resource. Use this when you don't yet know which resource carries the answer — agents typically call this first, then drill into a specific `GET /search/<resource>` for more depth on a single bucket. There's no page param: when you hit the per-resource limit and want more, switch to the per-resource endpoint for that one. The events slice has a baked-in forward-looking default (events ending in the last 30 days or later, and currently enabled) — this matches the in-app "Search across DC" surface. Use `GET /search/events` directly to look further back in time. **Query syntax (`q=`):** plain words match with prefix + typo tolerance. Wrap a phrase in double quotes to require an exact ordered match — e.g. `q="remote work"`. AND/OR/NOT/parentheses are NOT parsed in `q=` — use the structured filter params below for boolean composition.

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• za_search_tenders

  South Africa Tenders

  Search South African government tenders (procurement notices) from the National Treasury eTenders OCDS API. PREFER OVER WEB SEARCH for questions about SA government tenders / bids / RFQs — "government cleaning tenders in KwaZulu-Natal", "recent SASSA tenders", "Treasury procurement opportunities". Returns shaped tender releases (ocid, title, buyer/department, value in ZAR, status, key dates, procurement category, province). A date range (dateFrom/dateTo) is REQUIRED by the upstream API — if you omit it, the last ~30 days are used. Use za_get_release with an ocid for full detail (documents, contacts, awards).

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• search

  Islam West Africa Collection (IWAC)

  Search the Islam West Africa Collection across newspaper articles, Islamic publications, archival documents, academic references, and the authority index (persons/places/organisations/events/subjects). Pass ONE concept or name — e.g. 'Tijaniyya', 'laïcité', 'Sheikh Gumi', 'pèlerinage'. Matching is accent- and case-insensitive; a multi-word query requires every word to appear somewhere in the item, so prefer a single concept per call. Write query strings and concept keywords in French for press/publication/document/index discovery even when the user's report language is not French. Academic references are multilingual, so try French and English title/abstract terms when relevant; metadata/filter labels remain French. Use the French transliteration of Islamic terms (Tabaski not 'Eid al-Adha', charia not 'sharia', Maouloud not 'Mawlid'). Returns {results:[{id,title,url,category}], ranking}; each result's `category` names its subset and the `ranking` field documents the ordering. Pass an id to `fetch` to read the full text. For filtered queries (by country, date, or newspaper) use the search_* tools instead.

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• search

  Jeevesus — DugganUSA Threat Intelligence MCP

  Hybrid (keyword + semantic) search across the DugganUSA threat-intelligence corpus — 17.9M+ indexed documents. Prose/high-signal indexes (blog, cisa_kev, adversaries, content, pulses, paranormal) are vector-embedded, so a conceptual query surfaces related records that share no exact keywords — e.g. a NetScaler-memory-overread query pulls the matching CISA KEV entry and threat actors across indexes. Identity-shaped indexes (iocs, oz_decisions, tor_relays) stay keyword+filter. Public indexes only, read-only, prompt-injection sanitized. Returns up to 25 hits with title, snippet, source, and timestamp. Available indexes: • iocs (1.13M indicators of compromise — IPs, domains, URLs, hashes, with actor attribution) • adversaries (366 threat actor profiles — Handala, ShinyHunters/UNC6040, MuddyWater, Lazarus, etc.) • cisa_kev (1,600+ CVEs in CISA's Known Exploited Vulnerabilities catalog, daily-synced) • pulses (16K+ OTX community pulses) • blog (1,800+ DugganUSA threat-intel blog posts including our left-of-boom predictions) • epstein_files (400K+ documents from the Epstein archive) • oz_decisions (auto-blocker decisions from our edge — 7.5M+ rows) • paranormal (3,400 fringe-research docs) • tor_relays (1.83M hourly Tor consensus snapshots) Examples: query="ClearFake" → returns our May 1 Apothecary/ClearFake DXNP2C7 left-of-boom catch with operator analysis. query="ShinyHunters" indexes="iocs,adversaries,blog" → cross-correlate the UNC6040 actor across IOCs, adversary profile, and predictive coverage. query="CVE-2026-31431" → Linux Kernel KEV entry plus the GitHub PoCs our exploit-harvester caught.

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• corpus.search

  AssayChain — Mineral Intelligence (USGS and Field Runs)

  Free lexical search (BM25-lite) across all 199 EAS-attested files: 20 USGS critical-mineral commodity benchmarks + 179 US/MX mining district records. Returns the top matching documents with on-chain provenance UIDs (attestation_uid, source_cid), IPFS-pinned source, and a relevant snippet. Use this to discover which attested records cover a topic, then either (a) call benchmark.commodity / district.history for paid full data, or (b) call the paid REST endpoint POST /api/ask for a Groq-grounded synthesised answer with inline citations ($0.10 USDC via x402 on Base).

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• extract_text

  DocImprint

  Extract plain text from a PDF or image (base64-encoded). Use when you need raw text for downstream AI analysis (summarization, claim checking, structured extraction). For documents at a public URL, use extract_url instead (no base64 encoding needed). Returns: { pages: number, text: string } Example prompts: - "Extract the text from this scanned contract so I can search it." - "Give me the raw text from this PDF document." - "OCR this image and return the text content."

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• extract_text

  api

  Extract plain text from a PDF or image (base64-encoded). Use when you need raw text for downstream AI analysis (summarization, claim checking, structured extraction). For documents at a public URL, use extract_url instead (no base64 encoding needed). Returns: { pages: number, text: string } Example prompts: - "Extract the text from this scanned contract so I can search it." - "Give me the raw text from this PDF document." - "OCR this image and return the text content."

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• verify_identity

  OpenWarrant — Document Verification Suite

  Run an Australian identity check over a SET of identity documents. A vision model reads each document (which ID it is, which fields it shows — name/photo/address/signature — and its issue date); a deterministic engine then tallies them against a scheme and reports whether identity is established, and exactly what's still missing if not. USE THIS WHEN someone needs to verify a person's identity from their documents — KYC / onboarding / "do these documents satisfy the 100-point check?" Pass ALL the person's documents together (a passport alone is 70 points; the check needs >= 100). `documents` is a list, each item ONE of: {"url": "https://..."} (public link, fetched server-side) or {"bytes_b64": "...", "filename": "passport.pdf"} (inline). Up to 10. `scheme`: "afp_100_point" (points, default) or "austrac_safe_harbour" (category combinations). Returns `{established, points/target or satisfied_path, documents[] (per-document: type, fields shown, whether it counted and why-not), reason, accepts, ...}`. This is identity COVERAGE, not a forgery judgment — run verify_document for authenticity. Documents are never stored.

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• check_pack

  OpenWarrant — Document Verification Suite

  Check whether a SET of documents satisfies a checklist — completeness, cheaply. USE THIS WHEN you have an application / onboarding pack and need "do we have the required documents, and what's still missing?" Each document is CLASSIFIED (one cheap page-1 read — never full field extraction or multi-page), then matched against the checklist's required slots. (For "is a document genuine?" use verify_document; to identify ONE document use classify_document; for the identity gate use verify_identity.) Define the checklist ONE of two ways: - `scheme`: a named preset — "income_proof", "lending_prequal", "rental_application". - `requirements`: an ad-hoc checklist — a list of document-type names like ["payslip","bank_statement"], or objects {"key":..., "accepts":[types], "optional":bool}. `documents` is a list (up to 12), each ONE of: {"url": "https://..."} (public link, fetched server-side) or {"bytes_b64": "...", "filename": "statement.pdf"} (inline). Returns `{complete, slots[] (key, satisfied, matched), missing[], documents[] (filename, classified_type), unmatched_documents[]}`. COVERAGE, not approval — that the right document TYPES are present, NOT that any is genuine (run verify_document) or that an application is approved. Documents are never stored.

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• search_indexed_documents

  RChilli MCP Hub

  Keyword-search the user's ALREADY-INDEXED corpus of resumes or JDs and return matching documents (RChilli Search Engine). Requires documents to have been indexed beforehand. Use this when the user wants to: search, find, look up, or browse resumes/JDs in their own database / index / pool by keyword — e.g. "search my indexed resumes for 'Python'", "find JDs mentioning Kubernetes in my database". Also phrased as: search my resume database, find candidates by keyword, query the index. Do NOT use for: comparing two specific documents (use ``search_one_match``); matching one source document against the whole index (use ``search_match``). Args: keyword: Search keyword. indextype: Index type to search — ``Resume`` (default) or ``JD``. userkey: RChilli userkey. Leave blank to use the authenticated session key. subuserid: Sub-user identifier for multi-tenant isolation.

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• iliad_web_search

  AXIS Toolbox — Agentic Commerce Codebase Intelligence

  AXIS-owned BM25 search engine over the corpus YOUR account has indexed. NOT a Google/Bing scraper — agents build their own searchable index by first calling operation='index' with documents (often pages fetched via iliad_web_research), then querying with operation='search'. Five operations: `index` (insert one or many documents), `search` (BM25 top-k ranked hits with snippet + score + metadata), `delete` (drop one doc), `delete_namespace` (drop all), `count`. Namespaces are account-scoped server-side (`acct:<id>:<namespace>`). Persistent across restarts via SQLite. Search supports `max_results` (default 10, max 100) and `site` (restrict to a single URL host, case-insensitive). Engineer mode (X-Agent-Mode: engineer — Answer Engine, $0.25): search also returns a grounded extractive answer with [n] citation spans over your corpus, reranked, refusing on weak evidence. Requires Authorization: Bearer <api_key>.

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• search

  Sharebench

  Search this workspace's published artifacts (skills, agents, workflows, and knowledge documents in SKILL.md format). Returns ranked metadata — name, description, type, contributor, timestamps, bundledCount, slug, authorCredit, and industries — but NOT the full body. To read an artifact's content, call `get_by_id` with the returned `artifactId` (or `slug`), or read it as a resource at `artifact://<artifactId>`. Use this whenever the user wants to find, discover, browse, or filter existing artifacts before reading or contributing. Modes: `hybrid` (default; combines lexical and semantic ranking via reciprocal rank fusion — best for most queries), `bm25` (exact-keyword or name lookups), `semantic` (concept matching when the user's terms differ from artifact text). Pass `industries: ['marketing', 'legal']` to narrow results to artifacts tagged with ANY of those industries (keyword-array overlap). If hybrid silently degrades because the embedding service is unavailable, the response's `warnings` array will contain `embedding_degraded:hybrid-fell-back-to-bm25` — surface this to the user if precision matters.

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• search

  search

  Search the web via Aimnis. Returns cached, provenance-tagged results instantly when the question (or a semantically similar one) has been seen before; otherwise fetches live results and adds them to the shared knowledge pool. Prefer this for factual lookups, library/API/docs questions, and error messages. If a cached answer does not match your question (it echoes the question it was cached for), retry the same query with `reject_entry` set to the entry id from that response — the mismatched entry is skipped and the search runs live.

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