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510,248 tools. Updated 2026-09-03 23:30

"A server for finding information about content ranking systems and algorithms" matching MCP tools:

  • Look up ETFs by name, ticker or ISIN, with classification, listing, index, distribution-policy, AUM, expense-ratio and yield filters. Best for finding a known fund. For ranking questions ("cheapest", "largest", "best performing", "most liquid") prefer screen_etfs, which evaluates the whole universe: here minAum and minYieldTtmPct are applied only to a bounded profile-enriched candidate scan, so do not describe the result as exhaustive when candidateCapReached is true. Use get_etf_snapshot for one listing, get_etf_fund to resolve an ISIN across venues, and get_etf_holdings for constituents. Read-only.
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  • No arguments. Returns how many MCP servers have been read at source level, and the share of them with each category of finding (credential access, network egress, install-time execution, prompt-injection surface). Use this to judge whether checking a specific server is worth it before you look one up. It reports aggregate counts only - no per-server findings, and no verdict about any individual server.
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  • Parse one supported document into markdown, HTML, links, summary, targeted answers, or JSON matching a schema. Supported inputs include common HTML, PDF, Word, RTF, OpenDocument, and spreadsheet files; PDF parsing can be bounded with `pdfOptions.maxPages`. Local MCP reads `filePath` from the server filesystem. Hosted MCP uses two calls: first provide `filePath` to receive upload instructions, upload locally, then call again with the returned `uploadRef`; do not send both fields together. Remote web URLs belong in `firecrawl_scrape`. Set `redactPII` to request redaction of personally identifiable information in the returned content. `zeroDataRetention` requires an eligible authenticated account; omit it for anonymous keyless use. Returns upload instructions for hosted phase one or parsed document content for the final call.
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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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  • Remember something, with its sources and its knowledge time. Nothing is ever overwritten: saving a `factor_def` or `watchlist` under an existing key SUPERSEDES the previous version (both rows survive, so "what did I believe in June?" stays answerable), and saving identical content twice is a no-op rather than a duplicate. Args: kind: 'query' | 'factor_def' | 'watchlist' | 'finding' | 'note'. content: the thing to remember, as an object. key: the stable name — REQUIRED for 'factor_def' and 'watchlist' (that is what makes a definition reusable next session instead of re-invented). as_of: the knowledge time this memory is about. Recall can bound on it, which is what keeps a memory from leaking the future into a point-in-time question. source_query_ids: the `twmd_q_…` ids behind this. REQUIRED for 'finding' — a conclusion that cannot point at its data is not evidence, and will be refused. agent_id: optional label for which of your agents wrote this.
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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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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
    An MCP server that allows users to run and visualize systems models using the lethain:systems library, including capabilities to run model specifications and load systems documentation into the context window.
    2
    14
    MIT

Matching MCP Connectors

  • MCP server for social media and content data including social profiles, engagement metrics, content trends, and influencer analytics for AI agents.

  • Dev.to, Steam, podcasts, Eventbrite — cross-format content discovery for AI curators.

  • Audit the cryptographic strength of DNSKEY signing algorithms used for DNSSEC. Reports which algorithm is used for DNSSEC signing keys (RSA/SHA-1, RSA/SHA-256, ECDSA P-256, Ed25519, etc.), flags deprecated algorithms (RSA/SHA-1, DSA), independent of whether the DNSSEC chain validates. Use when asked what algorithm is used for DNSSEC signing keys, or if deprecated DNSKEY algorithms are in use. Part of the scan_domain audit.
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  • Deterministically VERIFY a proposed fix before writing it — runs the same patch-policy + verify_fix + blast-radius gates as `qremediate` (offline, no key, no network). Give the finding, the file's current content, and your proposed FULL corrected content; returns approved:true only if the patch is in-policy, clears the finding, adds no new finding, introduces no network/exec sink, and is bounded in size. This does NOT write the file — you write it, only when approved, and never auto-merge.
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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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  • 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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  • Return the curated list of example quantum algorithms with published resource estimates (qubit count, depth/gate count, source paper URL). Useful for comparing what algorithms need vs. what hardware can deliver. Each entry carries a `provenance` field: 'published-circuit' means the figure is reproducible from the source, 'attested-estimate' means the source withholds the circuit and the figure rests on the authors' attestation, with a `provenanceNote` giving the specifics. Carry that caveat whenever you quote an attested figure; do not present it as equivalently sourced.
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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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  • Point-in-time ranking records for SPECIFIC players: per system, the newest record in force ON OR BEFORE as_of — never one dated after it. Every other ranking field in this API is the CURRENT value joined at read time; this is the historical answer. Systems are never collapsed: ATP/WTA and the ITF circuits carry rank+points, UTR a rating. ITF and UTR history begins 2026-07-29. Requires the ULTRA plan.
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  • Published Truss information by topic. Localized topics (overview, about, services, engagement, fit, faq) use locale, default en; pass he for Hebrew. Language-independent topics (identity, certifications, testimonials, clients, contact) ignore locale for content selection. Prefer get_truss_overview or topic overview for broad business understanding; prefer list_truss_services for the complete service catalog.
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  • Compare mapped human-evidence strength and limitations for two to five supplements for the same goal. This is an evidence comparison, not a product ranking or purchase recommendation, and contains no affiliate links. Use only for public, non-personal evidence questions. Do not call this tool for requests involving personal or sensitive health information, including medical records, medication lists, diagnoses, symptoms, laboratory results, or treatment planning. Tell the user not to submit that information and direct them to a qualified healthcare professional.
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  • Return the Public MCP Server Index: a weekly-refreshed health, conformance and latency ranking of popular public (no-auth) remote MCP servers, scored 0-100 by the same live JSON-RPC handshake used by check_mcp_server. Includes per-server score, grade, latency, tool count, description quality and failing checks, plus aggregate stats (how many popular servers are auth-gated, average score and latency). Use it to pick a reliable public MCP server for a task, cite ecosystem statistics, or benchmark a server against the field. Free, no parameters. Curated by MCP Pulse (mcppulse.agiscorecard.com); on-demand scans of arbitrary servers at scale are available pay-per-call via x402 at https://x402.agiscorecard.com.
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  • Get aggregate statistics about missions on the HomeVisto platform. Returns total counts, status breakdown, and average bounty information. Useful for understanding platform activity.
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  • Get best-performing content recommendations for a venue type and optional time context. WHEN TO USE: - Deciding what content to schedule at a specific venue type - Finding content that drives the highest audience engagement at a location - Optimizing content rotation by daypart (morning, afternoon, evening, overnight) - Content programming decisions based on performance data RETURNS: - data: Array of recommended content ranked by performance score - videoId, title, contentCategory, durationSeconds - totalPlays, uniqueScreens - avgAttention (0-1), avgDwellMs - performanceScore (composite of attention, replay density, dwell time) - meta: { count, venue_type, daypart, limit } Performance score formula: attention(40%) + replay_density(30%) + dwell_time(30%) EXAMPLE: User: "What content works best in bars during the evening?" get_content_recommendations({ venue_type: "bar", daypart: "evening", limit: 10 }) User: "Best performing content for transit screens" get_content_recommendations({ venue_type: "transit", limit: 20 })
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  • Get all notes for your account. Notes are automatically decrypted and returned in reverse chronological order. Use them internally for tool chaining but present only human-readable information (titles, content, dates). # fetch_notes ## When to use Get all notes for your account. Notes are automatically decrypted and returned in reverse chronological order. Use them internally for tool chaining but present only human-readable information (titles, content, dates).
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  • Get detailed information about a single organization — accounts, tags, sources, products, aliases. When an AI-generated overview exists the response includes a short preview; pass `include_overview: true` to inline the full briefing (with a stale warning if the content is older than 30 days since last write).
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