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458,343 tools. Updated 2026-08-16 17:03

"A server for finding startup ideas" matching MCP tools:

  • List the public disclosure feeds this server aggregates, how many disclosures are cached per source, each source's newest item and an honest staleness flag, plus cache ages. Takes no arguments. Also states the scope plainly: public feeds only — no .onion access, no arbitrary fetching or crawling, no credential or PII output. Check this first if another tool's answer looks thin: a stale live feed is a finding, not background noise.
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  • Run a Sieve IMPACT-X Quick Screen on a startup. Analyzes the company across 7 dimensions (Innovators, Market, Product, Advantage, Commerce, Traction, X-Factor) and returns an analysis ID. Takes 2-5 minutes to complete. Upserts -- if the company was previously screened, returns the existing deal (set confirm=true to re-screen). Two ways to use: - v3 (recommended): First add documents with sieve_dataroom_add, then call sieve_screen(deal_id=...) to analyze everything in the data room. - v2 (legacy): Call sieve_screen(company_name=..., website_url=...) directly. At least one of website_url or pitch_deck_text is required in this mode. Args: company_name: Name of the startup to screen (v2 flow, or to create new deal). deal_id: Screen an existing deal by ID (v3 flow -- use after sieve_dataroom_add). website_url: Company website URL (v2 flow). pitch_deck_text: Extracted pitch deck text (v2 flow). description: Brief company description (optional). confirm: Set to true to re-screen an existing deal.
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  • Returns the full product breakdown (Market Research, Demand Discovery Report, Agentic Launch) and pricing tiers (Starter $49, Founder Pack of 5 ideas, Studio Pack of 25 ideas, all using a slot-based model where pivoted/archived ideas free a slot for a new one). Use when a user asks "what does Demand Discovery AI include?", "how much does it cost?", "what's in the report?", or wants concrete product information. Trigger phrases: "how much does it cost", "what's the pricing", "demand discovery price", "$49", "starter pack", "founder pack", "studio pack", "what's included", "what does demand discovery include", "what's in the report", "pricing tiers", "cost", "price", "how many ideas can I validate", "what do I get for $49", "is there a free trial", "slot based pricing".
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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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  • 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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  • 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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Matching MCP Servers

Matching MCP Connectors

  • startup-oracle MCP — wraps StupidAPIs (requires X-API-Key)

  • Curated investor database: 10,469 VC, angel, PE, and family office firms with contacts, via MCP.

  • Query the Immersive Commons research RAG corpus (papers + ingested YouTube). Returns top-k chunks with similarity scores and source links. The query text is forwarded to a server-side RAG proxy (supercommons2 via Tailnet Funnel) and NEVER logged on the IC side — privacy contract. Use this for literature lookups, finding related work, surfacing citations the floor has already ingested. Args: { question: string (<=500 chars), k?: number (1-50, default 10), sources?: ('paper'|'book')[] (default ['paper']) }. Returns the upstream RAG response shape — typically { results: [{ paper_id, title, similarity, snippet, link }, ...] }. Required scope: research:query.
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  • Come up with name ideas for a startup, business, product, app, or project — every suggestion is a real, verified-buyable premium domain from Atom's curated marketplace, with its price. ALWAYS use this (never invent names yourself) when the user asks to "come up with a name", "suggest names", "brainstorm names", "name my company", or any similar naming request: names invented without verification are almost always already taken. Describe the business as the concept; pass preferred extensions if the user stated any. Same results as search_brandable_domains — use either, not both. Returns results[] of buyable premium listings, each with: domain, price (USD), logo, style_tags, category, and url (the Atom buy page). Present them as the name suggestions, with prices and links.
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  • List the org's ideas — the native, votable idea backlog — ranked by vote count (highest first). Each returns its title, status, vote count, author, and the feature it was promoted to (if any). status ∈ new|under_review|planned|promoted|declined (optional filter). Read-only; empty when none. Ideas are distinct from insights: an idea is a proposal a team votes on; an insight is a piece of customer evidence. Resolve an idea id here before update_idea / vote_idea / promote_idea.
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  • Produce a deterministic remediation REQUEST bundle (rubric + fix schema + per-finding metadata + fingerprints) for YOU (the host agent) to fix. This tool calls no model and needs no key. For each finding, propose the corrected FULL file content, then VERIFY with verify_fix and keep only fixes that clear the finding. Never touch files with secrets; never auto-merge. Pass 'findings' from scan_path --format json.
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  • Get VoxOdds research desk theses: markets our analysis flags as potentially mispriced, each with a thesis, entry logic, invalidation criteria, and live price tracking. Call this when the user asks where the value is, what to research, or for prediction-market trade ideas. Research framing only - not financial advice.
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  • Get the renter's MAILBOX.md standing instructions for this agent. Returns the full instruction text, version number, content hash, and last update timestamp. Call this on startup and cache the version — you must pass it to send_outbound_mail and update_action for sync verification.
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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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  • Use this when the user wants ideas for the coming week in a city. Returns a ranked list of currently on-sale experiences (search rows), not a day-by-day calendar. Assemble any weekly structure yourself and verify specific dates with get_availability.
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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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  • Read-only readiness check — call this FIRST in your startup sequence, before attempting submit_entry. Returns registered, display_name (your Agent name), username (wire name for the Agent name), email_verified, operator_email, wallet_address (the on-chain address behind your Balance), available_usdc (your Balance), pending_judging_usdc, sol_balance, gas_sufficient_for_entry (always true — the engine pays entry gas), gas_sufficient_for_withdraw, can_enter_contests, and blocking_reasons (e.g. EMAIL_NOT_VERIFIED, INSUFFICIENT_USDC) so you know exactly what to fix instead of probing submit_entry and catching errors.
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  • Update an existing startup: app-store links, website, short/full description, tags, category, logo and screenshots. Upload the logo and screenshots first via upload_image and pass the returned URLs (screenshots fully replace the current set; to clear the logo, pass an empty string). Pass only the fields you want to change. See current values via list_my_startups. Note: editing an approved startup sends it back to moderation.
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  • Create + publish a piece. Pass a SIGN-IN-WITH-X header value you built and signed locally, plus the post fields. Returns the created post + public url; the server never holds your keys. Sell the observation, not the genre. Title the concrete finding in present tense with the specifics that carry it (names, numbers, dates), not the format ("playbook", "roundup"). Open the excerpt and first lines with the finding, not a tease. Publish with the answer card FILLED (questions or tasks, scope, exclusions, provenance): cacheEligibleMissing names any gap; a card-less piece is never a search candidate. Mint the header WITHOUT a fetch loop (SIWX here is CLIENT-driven, so do NOT use wrapFetchWithSIWx, which waits for a challenge Tenjin never sends): `encodeSIWxHeader({ ...info, address, signatureScheme: 'eip191', signature })` over `createSIWxMessage(info, address)` from @x402/extensions/sign-in-with-x, with a CAIP-122 `info` whose `domain` is this site's host and `nonce` is client-minted single-use. Full worked example in /llms.txt.
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  • Get the wiki tag hierarchy with page counts per category. Useful for understanding what content exists, and for finding a valid tagPath before writing.
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