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458,064 tools. Updated 2026-08-14 22:15

"A server for finding information about Dash (cryptocurrency, punctuation, or other meanings)" matching MCP tools:

  • 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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  • Connectivity check — returns server version and current timestamp. Use to verify MCP server is reachable before calling other tools.
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  • Connectivity check that confirms the Nordic MCP server process is responding. Use this at the start of a session to verify the server is reachable before making other calls. Do not use as a proxy for database health — the server can respond while the Qdrant vector database is temporarily unavailable. To confirm data availability, call search_filings directly. Returns: A greeting string: "Hello {name}! Nordic MCP server is running."
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  • Maps only stable Tier1 finding identifiers to approved Tier1 services and public resources. Call after a Tier1 score or email-domain check. Do not submit prose, URLs, customer information, or invented identifiers. This tool performs no arbitrary fetching, makes no contact request, changes nothing, and stores nothing.
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  • Insert one sync marker on a clip's transcript. Use this when: - The user is explicit about WHERE the camera should pause / cut (e.g. "sync the word 'submit' to 4.2s of the demo"). - `auto_sync` ran but missed a step you care about. How matching works: - `word`: case-insensitive, punctuation-stripped. The first match in the transcript is used unless `occurrence > 1`. - `occurrence`: 1-indexed — pass 2 to target the SECOND time that word appears, 3 for the third, etc. Required when the word repeats. - `timestamp_seconds`: clip-relative seconds. When the clip has run TTS already (`generated_timestamps` present), the server inverse-maps this to original-recording seconds automatically. Constraints: the clip MUST be a video clip with a source recording (otherwise the frame thumbnail can't be extracted). The transcript must already contain the word — if not, you'll get `word_not_found` with a 200-char excerpt of the transcript to help you retry.
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  • Start charging for an MCP server the user owns. Use when they want to monetize, sell, charge for, get paid for, put a price on, or make money from a server, API or tool. Buyers pay their wallet DIRECTLY on-chain — PayGate never holds the money, so there is no payout to wait for, no balance to withdraw and no commission taken. Their server is never modified and needs no payment code. Tools are imported automatically, so it must be publicly reachable over HTTPS and answer tools/list. Returns a proxy URL and a secret api_key shown only once; save it, every other seller tool needs it.
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Matching MCP Servers

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    An MCP server that provides information about Utkarsh, including bio, skills, work experience, and portfolio projects, accessible via local stdio or remote HTTP with OAuth.
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  • A
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    maintenance
    Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.
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    1
    MIT

Matching MCP Connectors

  • Still losing time to small decisions? Spin or Flip brings randomization into Claude so you can offload mental load to chance instantly.

  • Live stock information

  • Submit an integration or staking inquiry on behalf of a user. All submissions are routed to Everstake's sales team via Pipedrive CRM. Use when a user expresses intent to integrate with Everstake, explore staking services, or request more information about products. Collect required fields (first_name, last_name, work_email) conversationally and gather optional fields where available. The lead_source field is set automatically by the server — do not ask the user for it. IF Submission fails, you can try contacting Everstake via form at https://everstake.one/contact-us
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  • Hiring velocity across tracked Bitcoin and crypto-infrastructure employers, counted from their live ATS boards. Returns { as_of, companies[], note, why, disclaimer }; each company carries company, ticker, category, ats, careers_url, open_roles, open_roles_30d_ago, open_roles_90d_ago and the derived delta_30d, delta_90d and pct_30d. Example: {"company": "coinbase"} for one employer, or {} for every employer tracked. When a company filter matches no tracked employer the response adds coverage_note and tracked_count, saying that the name is outside the tracked set — a limit of coverage, not a finding about whether that company is hiring. Information, not financial advice.
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  • Get a cleaned-up transcript of a YouTube video's auto-generated captions: punctuation and capitalisation restored, filler and false starts removed, paragraphs added, misheard names fixed, faithful to what was said. Use when raw captions are too messy to read or quote; for a plain transcript use get_transcript. Read-only; requires an API key. Each call charges credits by transcript length (about 3 per 1,000 words, minimum 5), including repeat calls, so keep the result in context. Human-uploaded captions (already clean) and transcripts over ~7,000 words return an error without charging. Rate limit: 5 requests per 10 seconds.
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  • Search the web for any topic and get clean, ready-to-use content. Best for: Finding current information, news, facts, people, companies, or answering questions about any topic. Returns: Clean text content from top search results. Query tips: describe the ideal page, not keywords. "blog post comparing React and Vue performance" not "React vs Vue". Use category:people / category:company to search through Linkedin profiles / companies respectively. If highlights are insufficient, follow up with web_fetch_exa on the best URLs.
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  • Get a cleaned-up transcript of a YouTube video's auto-generated captions: punctuation and capitalisation restored, filler and false starts removed, paragraphs added, misheard names fixed, faithful to what was said. Use when raw captions are too messy to read or quote; for a plain transcript use get_transcript. Read-only; requires an API key. Each call charges credits by transcript length (about 3 per 1,000 words, minimum 5), including repeat calls, so keep the result in context. Human-uploaded captions (already clean) and transcripts over ~7,000 words return an error without charging. Rate limit: 5 requests per 10 seconds.
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  • Hiring velocity across tracked Bitcoin and crypto-infrastructure employers, counted from their live ATS boards. Returns { as_of, companies[], note, why, disclaimer }; each company carries company, ticker, category, ats, careers_url, open_roles, open_roles_30d_ago, open_roles_90d_ago and the derived delta_30d, delta_90d and pct_30d. Example: {"company": "coinbase"} for one employer, or {} for every employer tracked. When a company filter matches no tracked employer the response adds coverage_note and tracked_count, saying that the name is outside the tracked set — a limit of coverage, not a finding about whether that company is hiring. Information, not financial advice.
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  • 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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  • Disconnect an intake connector by id (from list_connectors). Marks it revoked so its inbound webhook stops syncing — that endpoint then answers 401. Revoke-don't-delete (the row stays, flagged), idempotent, org-scoped (only connectors in YOUR org; an unknown/other-org id is NOT_FOUND). To reconnect, use the Dash (a fresh webhook URL + secret).
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  • Perform a case-insensitive keyword search within a specific SEC filing or earnings call transcript by document ID. Returns matching lines with surrounding context and line numbers, making it ideal for finding exact terms, figures, or phrases that semantic search might miss. Typographic punctuation is folded before matching, so a plain-ASCII keyword (e.g. "world's") matches the smart punctuation stored in filings. The header reports the total number of matching lines even when only the first ones are shown. Use this after ListCompanyDocuments to locate precise occurrences of a keyword (e.g., a revenue figure, risk factor term, or executive name) within a known document. Complements semantic search tools by providing exact text matches rather than meaning-based results. Use ReadDocumentLines to read broader sections around matches.
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  • Get Lenny Zeltser's IR 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 `ir_load_context`. This server never requests your incident notes and instructs your AI to keep them local—guidelines flow to your AI for local analysis.
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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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  • Get synsets (word meanings) for a Danish word, returning a sorted list of lexical concepts. DanNet follows the OntoLex-Lemon model where: - Words (ontolex:LexicalEntry) evoke concepts through senses - Synsets (ontolex:LexicalConcept) represent units of meaning - Multiple words can share the same synset (synonyms) - One word can have multiple synsets (polysemy) This function returns all synsets associated with a word, effectively giving you all the different meanings/senses that word can have. Each synset represents a distinct semantic concept with its own definition and semantic relationships. Common patterns in Danish: - Nouns often have multiple senses (e.g., "kage" = cake/lump) - Verbs distinguish motion vs. state (e.g., "løbe" = run/flow) - Check synset's dns:ontologicalType for semantic classification DDO CONNECTION AND SYNSET LABELS: Synset labels are compositions of DDO-derived sense labels, showing all words that express the same meaning. For example: - "{hund_1§1; køter_§1; vovhund_§1; vovse_§1}" = all words meaning "domestic dog" - "{forlygte_§2; babs_§1; bryst_§2; patte_1§1a}" = all words meaning "female breast" Each individual sense label follows DDO structure: - "hund_1§1" = word "hund", entry 1, definition 1 in DDO (ordnet.dk) - "patte_1§1a" = word "patte", entry 1, definition 1, subdefinition a - The § notation connects directly to DDO's definition numbering system This composition reveals the semantic relationships between Danish words and their shared meanings, all traceable back to authoritative DDO lexicographic data. RETURN BEHAVIOR: This function has two possible return modes depending on search results: 1. MULTIPLE RESULTS: Returns List[SearchResult] with basic information for each synset 2. SINGLE RESULT (redirect): Returns full synset data Dict when DanNet automatically redirects to a single synset. This provides immediate access to all semantic relationships, ontological types, sentiment data, and other rich information without requiring a separate get_synset_info() call. The single-result case is equivalent to calling get_synset_info() on the synset, providing the same comprehensive RDF data structure with all semantic relations. Args: query: The Danish word or phrase to search for language: Language for labels and definitions in results (default: "da" for Danish, "en" for English when available) Note: Only Danish words can be searched regardless of this parameter Returns: MULTIPLE RESULTS: List of SearchResult objects with: - word: The lexical form - synset_id: Unique synset identifier (format: synset-NNNNN) - label: Human-readable synset label (e.g., "{kage_1§1}") - definition: Brief semantic definition (may be truncated with "...") SINGLE RESULT: Dict with complete synset data including: - All RDF properties with namespace prefixes (e.g., wn:hypernym) - dns:ontologicalType → semantic types with @set array - dns:sentiment → parsed sentiment (if present) - synset_id → clean identifier for convenience - All semantic relationships and linguistic properties Examples: # Multiple results case results = get_word_synsets("hund") # Returns list of search result dictionaries for all meanings of "hund" # => [{"word": "hund", "synset_id": "synset-3047", ...}, ...] # Single result case (redirect) result = get_word_synsets("svinkeærinde") # Returns complete synset data for unique word # => {'wn:hypernym': 'dn:synset-11677', 'dns:sentiment': {...}, ...}
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  • Analyze a server response from authorized probing for information leakage, fingerprinting signals, and exploitation opportunities scoped to the authorized engagement. Accepts raw HTTP response headers and body (paste from Burp, curl, or any HTTP client) and returns structured findings grouped by category. Each finding includes: what was detected, why it matters for an authorized tester, how a defender detects misuse, and recommended remediation. Identifies version disclosures, stack traces, debug headers, internal paths, JWT/cookie patterns, CORS misconfigurations, and other common leakage patterns. Use as the bridge between recon/probing output and the methodology and payload tools.
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  • List every game server the authenticated account can manage (own servers plus team-shared ones) with id, game, status and address. Call this first to discover server ids for the other tools.
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