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134,048 tools. Last updated 2026-05-15 21:56

"A server for conducting deep research" matching MCP tools:

  • Get detailed KDP niche intelligence for a specific keyword. Returns demand score, competition score, Amazon BSR range, estimated monthly revenue, review threshold, average book pricing, and data freshness for the given Kindle publishing niche. Pricing tiers (x402 USDC on Base network): - $0.03 per query for cached/pre-seeded keywords - $0.10 per query for live on-demand research (new keywords) Use the free `list_niches` tool first to see available keywords. Payment options: 1. Set the KDP_X_PAYMENT environment variable on the server for auto-pay. 2. Pass a valid x402 payment header via the x_payment argument. 3. If neither is set, the tool returns structured 402 payment instructions that an x402-capable agent can use to construct and retry payment. Args: keyword: The KDP niche keyword to research (e.g. "romance novels", "keto cookbook") x_payment: Optional base64-encoded x402 payment header. Takes precedence over the KDP_X_PAYMENT environment variable.
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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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  • Use this read-only composite workflow tool for the default full single-issuer DeltaSignal ATLAS-7 company report. It server-enforces the complete company report call plan: readiness, company_fundamentals, alpha_signals, peer_ranking, covenant_stress, and SPECTRA field-map support for one normalized ticker. Parameters: ticker is required and normalized to uppercase; period, include_segments, include_related_party, and output_mode=compact are optional. SPECTRA is included when a field-map contract is available for the issuer. Behavior: read-only and idempotent; it performs six internal HTTPS reads, has no destructive side effects, rejects invalid tickers before fan-out, and preserves partial results if a required issuer leg fails. Use it when the user asks for a report, deep dive, issuer brief, or diligence package on one crypto public-company ticker; use low-level tools only for custom drilldowns.
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  • Multi-source web research with citations. Returns a synthesized answer with numbered [^1] markers and a citations array of {url, title, snippet, index}. Use for evidence-backed synthesis (competitive analysis, regulatory summary, whitepaper section). For quick fact lookups use web.search instead.
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  • Aggregated intelligence feed combining research findings, active security threats, and live staking APY snapshot in a single call ($0.005 USDC). Sources: ChromaDB research library + Guardian log + staking.db. Best for: broad situational awareness — replaces three separate calls. Requires x402 payment on Base mainnet.
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  • Creates a Deep Research task for comprehensive, single-topic research with citations. USE THIS for analyst-grade reports, NOT for batch data enrichment. Use Parallel Search MCP for quick lookups. After calling, share the URL with the user and STOP. Do not poll or check results unless otherwise instructed. Multi-turn research: The response includes an interaction_id. To ask follow-up questions that build on prior research, pass that interaction_id as previous_interaction_id in a new call. The follow-up run inherits accumulated context, so queries like "How does this compare to X?" work without restating the original topic. Note: the first run must be completed before the follow-up can use its context.
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Matching MCP Servers

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  • MCP server for academic research data including scholarly papers, citations, research trends, and publication metadata for AI agents.

  • UK property research tools - crime stats, schools, demographics, valuations for AI.

  • List the current version, release date, publisher, source URL, and update cadence of every terminology this server queries against. Useful for pipeline maintainers who need to: - Confirm which release of ICD-11 / SNOMED / LOINC / RxNorm / MeSH / ATC the server is querying before a batch run. - Verify the bundled CID-10 (frozen at V2008) and ICD-10 → ICD-11 transition tables (currently 2025-01) match expectations. - Cite the data version in research artifacts. Pass `terminology` to filter to a single entry; otherwise the full set of 8 is returned. The ICD-10 → ICD-11 version reads live from the bundled dataset; everything else is metadata maintained alongside the project release.
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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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  • Retrieve comprehensive details for a specific property from Redfin URL. Returns full description, tax history, HOA fees, walk scores, nearby schools, crime statistics, and property photos/virtual tour link. Use for due diligence, investment research, or detailed listing analysis.
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  • Submit an L8 research thesis for dossier generation. Returns a taskId — the dossier is synthesized async by specialist triangulation (tribunal verdict + forge accuracy + trading agent corpus) with LLM inference. Standard depth: automated data aggregation ($0.50). Deep depth: full specialist triangulation with counter-arguments ($5.00). TRENCH whale holders get all dossiers free.
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  • OpenAI ChatGPT Deep Research / Connectors fetch contract. Given an id returned by `search` (formatted as 'artist:<uuid>', 'campaign:<uuid>', or 'smartlink:<uuid>'), returns the full record for citation.
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  • OpenAI deep-research / company-knowledge compatibility. Search Cyclesite's active UK used-bike listings by free-text query (matches title, brand, model). Returns the canonical OpenAI shape: { results: [{ id, title, url }] }. Use the id to call fetch() for the full document.
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  • Scan an MCP server (URL or raw manifest JSON) against Helixar's Sentinel detection rules. Returns risk score, findings, and a Claude-generated security brief. Quick mode is free + authless (top 8 rules); deep mode runs all 26 rules with an api_key.
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  • Upload a file to the Compoid MCP server. Accepts a data URI (data:<mime>;base64,<data>). Returns the server-side path to use as file_upload in Compoid_create_record or Compoid_update_record.
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  • OpenAI ChatGPT Deep Research / Connectors search contract. Returns matching Dynamoi artists, campaigns, and Smart Links so they can be cited in a deep-research session. For regular ChatGPT chat use dynamoi_search instead.
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  • Start a contact research job — AI gathers insights from LinkedIn and other sources asynchronously; use contacts.get_research to poll for results
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  • Get full details for a specific case by its citation. Returns comprehensive case metadata, all known citation aliases, and citation treatment statistics showing how many times the case was followed, distinguished, overruled, approved, or referred. Use after resolve_citation or search_cases_by_citation for deep case analysis. Cost: 1 credit.
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