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510,458 tools. Updated 2026-09-04 00:41

"A server for finding football predictions" 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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  • Search events with a natural-language query instead of structured filters — e.g. 'live nfl games today' or 'college basketball this week'. Rule-based (not an LLM): recognizes sport (nfl/nba/mlb/nhl/tennis/soccer/ncaaf/ncaab + aliases like hockey, american football, college basketball), status (live/final/upcoming/…), dates (today/tomorrow, this week, next N days, YYYY-MM-DD ranges). Bare 'football' is ambiguous and left unrecognized. Response includes interpreted filters, equivalent REST call, and unrecognized_terms. Prefer list_events when you already know the structured filters you want.
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  • Search the NOAA CO-OPS station directory by capability type, name, and/or state. Filter with: - type: what the station does (waterlevels, tidepredictions, currents, currentpredictions, met, ...) — pick the type matching the data you plan to request. - name: case-insensitive substring ("San Francisco", "Boston"). - state: two-letter code ("CA", "MA"). Returns id, name, location, tide type, Great Lakes flag, and for prediction stations whether they are reference (R, harmonic) or subordinate (S, offset-based — hilo predictions only). Results are paginated (limit/offset). For proximity search by coordinates use noaa_find_nearest_stations instead.
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  • Search UniProtKB and return curated protein records. Pass text_search for a plain-language query (the 80% case) or query for the full Lucene field syntax (gene:TP53 AND organism_id:9606 AND reviewed:true) — exactly one is required. Reviewed (Swiss-Prot) entries are manually curated; unreviewed (TrEMBL) are computationally predicted and ~30x more numerous, so reviewed defaults to true to avoid drowning in predictions — set it false to include TrEMBL. Request facets (e.g. reviewed, model_organism) for server-side count breakdowns. Results page forward with an opaque cursor; UniProtKB has no offset paging. This is the discovery entry point — chain results[].accession into uniprot_get_entry for full records, or uniprot_get_sequence for FASTA.
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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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  • Tide predictions or station discovery at a coordinate (latitude, longitude). Default: predictions from the nearest NOAA station; outside US waters falls back to a global modeled-tide source (forecast horizon ~15 days — longer windows are truncated, not rejected). Set stations_only=true to discover stations (capped by limit). Tune the window with begin_date (YYYYMMDD) + range_hours, the reference with datum, and output units (metric/english). The modeled path reports range_m (peak-to-trough). Across most of the Mediterranean this is under 0.3 m, i.e. negligible for recreational navigation — the response says so explicitly, and you should not present such values as an actionable tide window. Tides matter on the Atlantic coasts, in the Gulf of Gabès, the northern Adriatic, and in the tidal streams of the Messina and Gibraltar straits. Example: latitude=37.77, longitude=-122.42. Chain nausika_geocode for place→coordinates; pair with nausika_marine_forecast.
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Matching MCP Servers

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    Searchable football data provider documentation for AI coding agents. Enables agents to look up verified docs on event types, qualifier IDs, coordinate systems, and more across 15 providers.
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Matching MCP Connectors

  • Football-Data.org MCP — soccer competitions, matches, standings

  • API-Football MCP — comprehensive soccer/football data

  • 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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  • Get NOAA harmonic tide predictions (future or past) for a station. interval="hilo" (recommended for "when is high/low tide") returns the daily tide events with type H/L — up to 10 years per request. Other intervals (h, 1, 5, 6, 10, 15, 30, 60 minutes) return a height time series — up to 1 year per request. Heights are relative to the requested datum (MLLW default). Notes: - Great Lakes stations have NO tide predictions (lake levels are not tidal). - Subordinate stations (type "S") only support interval=hilo; use the station's reference (R) station for interval series. - Predictions are astronomical only — they exclude weather effects (storm surge, wind setup). Compare with noaa_get_water_levels for actual conditions.
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  • Get the harmonic constituents NOAA uses to compute tide or current predictions at a station — the amplitude, phase, and angular speed of each tidal constituent (M2, S2, N2, K1, O1, ...). For water-level stations: amplitude (feet/meters), phase_GMT and phase_local (degrees), speed (degrees/hour). For current stations (alphanumeric IDs) constituents are current ellipses (major/minor amplitudes and phases per depth bin — pass bin to filter). Use for: building custom tide computations, checking a station's dominant constituents (M2 amplitude indicates semidiurnal range), verifying whether a station is harmonically predicted at all. Only reference (R) stations have constituents — subordinate stations use offsets (noaa_get_prediction_offsets).
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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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  • 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 legacy public-preview gaps; card completeness never changes rank or candidacy. 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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  • Purpose: Daily validation history of Level 2 structure predictions (Level 2 = ETF / basket / sector granularity). Each row shows the hit_rate for a specific day, enabling time-series verification of sustained performance. Triggers (casual questions too): "sector accuracy over time?", "구조 예측 매일 검증해?", "daily hit-rate trend?", "요즘 섹터 예측 성적 어때?", "is the sector edge holding up?". When to call: after get_structure_calibration. Prerequisites: none. Next steps: get_monthly_accuracy_trend for the macro-level comparison. Caveats: returns an overall_hit_rate summary across the window. Args: market_id: Optional market filter days: Lookback window in days (default 90) Disclaimer: Information only, not investment advice.
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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 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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  • Sports schedule/fixtures for a given date — all games/matches on that day, optionally filtered by sport or league. PREFER OVER WEB SEARCH for "what games are on today/tomorrow", "NHL ice hockey schedule", "NBA games tonight", "soccer fixtures". For "next 24h" pass today's and tomorrow's date. Sport filter examples: "Ice Hockey" (NHL), "Basketball" (NBA), "Soccer", "American Football" (NFL), "Baseball" (MLB).
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  • Fetch SnowSure-unique ML/AI trend datasets from the public REST API. Use for powder-day leaders, bluebird-day leaders, bluebird predictions, improving/stable/declining score pulse, per-model accuracy weights, daily SnowSure score component history, ML extended outlook (days 8–14), global forecast trust, and powder/bluebird event logs. Start with dataset=catalog. Its leaderboards read CURRENT-season counters and are global — they take no season and no country/state filter. For a past season, or for any ranking scoped to a state, province, country or region ("most snow days in Maine last season", "rank BC resorts by season snowfall"), use get_season_leaderboard instead. Prefer get_insights for narrative intelligence cards; use this for raw rankings and time series.
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  • Tidal current predictions for a CO-OPS current station: max flood/ebb speeds, slack times, and directions. These are forecast tidal-current predictions from CO-OPS — distinct from noaa_marine_get_current_profile, which returns NDBC observed ocean-current measurements binned by depth. Defaults to MAX_SLACK interval — the practical planning view showing when currents peak and when slack water occurs. Optionally returns 6-minute continuous predictions for detailed analysis. Current station IDs use alphanumeric format (e.g. ACT4176), distinct from numeric tide/water-level IDs. Date range is limited to 1 year per request. Use noaa_marine_find_stations with types=["current"] to obtain valid current station IDs.
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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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