"A platform or tool for accessing historical cryptocurrency data" matching MCP tools:

• lookup_profilesA

  InflushipA

  Batch-fetch up to 100 profiles by (platform, username) pairs. Use this when the user has a list of handles and you need profile data for all of them at once (e.g., "give me follower counts for these 30 accounts I'm considering" or "which of @a @b @c are real accounts?"). One round-trip beats 30 calls to `get_profile`. Use this for exact batch handle lookup, not semantic discovery. For one exact platform+username pair, use `get_profile`. For partial or fuzzy handle/name input, use `search_creators` or `autocomplete_creators`. Use `semantic_search_creators` only for topical/niche/audience discovery where false-positive semantic matches are acceptable. Examples: - User: "Compare @a, @b, and @c on Instagram" -> use this tool for the exact handle batch. - User: "Give me follower counts for these 30 accounts" -> use this tool. - User: "Find wellness creators in Austin" -> use `semantic_search_creators`, not this tool. The response splits results into `data` (profiles found) and `not_found` (the (platform, username) pairs that weren't recognized). Profiles are returned in no particular order — re-correlate via the platform/username fields if you need to preserve input order.

  ConnectorNo auth

• lookup_profilesA

  Influship Influencer Marketing MCPA

  Batch-fetch up to 100 profiles by (platform, username) pairs. Use this when the user has a list of handles and you need profile data for all of them at once (e.g., "give me follower counts for these 30 accounts I'm considering" or "which of @a @b @c are real accounts?"). One round-trip beats 30 calls to `get_profile`. Use this for exact batch handle lookup, not semantic discovery. For one exact platform+username pair, use `get_profile`. For partial or fuzzy handle/name input, use `search_creators` or `autocomplete_creators`. Use `semantic_search_creators` only for topical/niche/audience discovery where false-positive semantic matches are acceptable. Examples: - User: "Compare @a, @b, and @c on Instagram" -> use this tool for the exact handle batch. - User: "Give me follower counts for these 30 accounts" -> use this tool. - User: "Find wellness creators in Austin" -> use `semantic_search_creators`, not this tool. The response splits results into `data` (profiles found) and `not_found` (the (platform, username) pairs that weren't recognized). Profiles are returned in no particular order — re-correlate via the platform/username fields if you need to preserve input order.

  ConnectorNo auth

• arbitrage_historyA

  whale-insightsA

  Historical arbitrage opportunities — top 5 per day (MCP-compatible) — Returns a daily history of the top 5 cross-exchange arbitrage opportunities detected by the platform. Each day entry lists the 5 highest-spread opportunities saved by the cron job, including token symbol, spread percentage, buy/sell exchanges, and average USD volume. Useful for AI agents answering questions like 'which tokens appear most frequently in arbitrage?' or 'what is the average daily spread?'. Data is accumulated daily; older than 180 days is automatically purged. Response: { days, history: [{date, opportunities: [{symbol, spreadPct, buyExchange, sellExchange, usdVolume}]}], total, updatedAt }. Query parameter: ?days=7 (default 7, max 180). No authentication required. 60 requests/min rate limit. 5-min in-process cache. — Use this for daily historical data; use the corresponding live snapshot tool for current conditions and the monthly tool for long-term trends.

  ConnectorNo auth

• analyst_summary_historyA

  whale-insightsA

  Get historical daily AI analyst summaries — query by date or by analyst+days (max 90 days; use analyst_daily_summary for today's data) — Returns a paginated history of daily AI analyst summaries. Query by specific date (?date=YYYY-MM-DD) to see all analyst summaries for one day, or by analystId (?analystId=chain_hawk&days=30) to get the last N days for one analyst. Maximum 90 days. Only shortSummary is returned (full commentary is Pro-only). Fields per record: analystId, analystName, summaryDate (YYYY-MM-DD), shortSummary, summaryAr, summaryHi, summaryZh, summaryRu, signalCount, confluenceScore, fearGreedScore, btcTrend. No auth required. 60 req/min. — Use this for daily historical data; use the corresponding live snapshot tool for current conditions and the monthly tool for long-term trends.

  ConnectorNo auth

• list_topicsA

  bill-commonsA

  List Bill Commons' curated cross-state topic trackers (e.g. artificial intelligence, youth online safety, platform accountability, cybersecurity, cryptocurrency, data privacy, local government & preemption) -- the entry point for "what subjects does Bill Commons track across all 50 states + DC" and "how do I get every bill in one". Each topic is a title/subject membership rule tuned for precision over recall, with a live bill_count and how_to_fetch_bills. This tool does not itself return bill rows -- pair it with search_legislation or the REST API's /topics/{slug} for the bills.

  ConnectorNo auth

• get_historical_reaction_contextA

  FX ContextA

  Summarize the aggregate post-event reaction pattern across historical macroeconomic events similar to a selected target release. Use this AGGREGATE-PATTERN tool when the user wants to understand what the historical analog sample collectively showed rather than inspect individual analog events. It summarizes historical outcomes using statistics and behavioral patterns across standardized post-event windows (M5, M15, H1, H4, H24) such as mean, median, quantiles, directional consistency, reaction-path classification (e.g. IMMEDIATE_CONTINUATION, INITIAL_REVERSAL, FADE, DELAYED_REACTION), persistence, and sample-size-based confidence. Supported event types: US_CPI and US_NONFARM_PAYROLLS across EURUSD, GBPUSD, and USDJPY. Similarity methodology is event-specific: US_CPI uses headline/core surprise distance; US_NONFARM_PAYROLLS uses target-relative robust scale normalization (nfp-historical-analog-v1). Do NOT use this tool when the user's primary goal is to identify, rank, enumerate, or inspect specific historical analog events. For individual historical cases, use get_historical_analogs. When the user asks for both specific cases and collective pattern analysis, invoke both tools. The results are deterministic empirical observations only and do not predict future prices or provide trading recommendations.

  ConnectorNo auth

• get_account_metricsA

  SocialGPTA

  Get per-platform engagement (views / likes / comments / shares) as a time series over the trailing window_days (default 28, up to 365). Omit account_id to aggregate across all connected accounts, or pass one from list_accounts; optionally filter to a single platform. post_limit (≤100) fixes how many recent posts form the baseline. granularity buckets the series server-side ('daily' default, 'weekly', or 'raw' for every scrape). Read `series` (a clean per-platform list of typed points) — `metrics` is the legacy column/data matrix kept for back-compat. NB: follower counts here are latest-only; for audience growth over time use get_follower_history.

  ConnectorOAuth

• search_creatorsA

  InflushipA

  Find a creator by name/handle, while preserving legacy semantic creator search. Use this as the default creator lookup tool when the user gives a creator-ish string but not a canonical creator UUID: a handle, partial handle, display name, creator name, or profile-ish text. This is cheap, fast, and backed by the creator lookup index. If the user gives an exact handle on a specific platform (for example "@niickjackson on Instagram"), prefer `get_profile` first because it returns the full platform profile. If you need to resolve a rough creator name or partial handle first, use this tool with `query_type: "creator_lookup"`. For backward compatibility, this tool still accepts the old semantic-search fields (`platforms`, follower/engagement filters, `creator_kinds`) and routes legacy calls to the semantic endpoint unless the query clearly contains a handle/profile URL. For new topical/niche discovery calls such as "fitness creators in NYC" or "vegan recipe creators with high engagement", prefer `semantic_search_creators` because its name is explicit and less likely to be confused with exact creator lookup. Examples: - User: "Find @cris" -> use this tool with query "cris" and query_type "creator_lookup". - User: "Who is that fitness coach called Jane?" -> use this tool with query "Jane" and query_type "creator_lookup". - User: "Pull @niickjackson on Instagram" -> use `get_profile` with platform "instagram" and username "niickjackson". - User: "Find news creators with 1M+ followers" -> use `semantic_search_creators`, not this tool. Returns either autocomplete-style creator lookup results or legacy semantic results, depending on routing. Use returned creator IDs with `get_creator`, `find_lookalike_creators`, or `match_creators`; use returned platform usernames with `get_profile` or `get_posts`.

  ConnectorNo auth

• get_creatorA

  InflushipA

  Fetch the full record for a single creator by ID or exact platform username. Use this when you already have either: - a canonical creator UUID returned by `search_creators`, `semantic_search_creators`, `autocomplete_creators`, or `find_lookalike_creators`; or - an exact platform+username pair such as platform "instagram" and username "niickjackson". Pass `include: ['profiles']` to also receive the creator's social profile summaries when using a creator UUID. For platform+username inputs, this tool resolves through the profile endpoint and returns the profile record plus the underlying creator record, so you already get the matched profile context. Examples: - User: "Get creator 123e4567-e89b-12d3-a456-426614174000" -> call with id. - User: "Get @niickjackson on Instagram" -> call with platform "instagram" and username "niickjackson", or use `get_profile` if profile metrics are the main need. - User: "Tell me about @niickjackson and include his profiles" -> use platform "instagram" and username "niickjackson"; then use `get_profile`/`get_posts` for platform-specific metrics and content if needed. Use `lookup_profiles` for batch exact profile lookups.

  ConnectorNo auth

• search_creatorsA

  Influship Influencer Marketing MCPA

  Find a creator by name/handle, while preserving legacy semantic creator search. Use this as the default creator lookup tool when the user gives a creator-ish string but not a canonical creator UUID: a handle, partial handle, display name, creator name, or profile-ish text. This is cheap, fast, and backed by the creator lookup index. If the user gives an exact handle on a specific platform (for example "@niickjackson on Instagram"), prefer `get_profile` first because it returns the full platform profile. If you need to resolve a rough creator name or partial handle first, use this tool with `query_type: "creator_lookup"`. For backward compatibility, this tool still accepts the old semantic-search fields (`platforms`, follower/engagement filters, `creator_kinds`) and routes legacy calls to the semantic endpoint unless the query clearly contains a handle/profile URL. For new topical/niche discovery calls such as "fitness creators in NYC" or "vegan recipe creators with high engagement", prefer `semantic_search_creators` because its name is explicit and less likely to be confused with exact creator lookup. Examples: - User: "Find @cris" -> use this tool with query "cris" and query_type "creator_lookup". - User: "Who is that fitness coach called Jane?" -> use this tool with query "Jane" and query_type "creator_lookup". - User: "Pull @niickjackson on Instagram" -> use `get_profile` with platform "instagram" and username "niickjackson". - User: "Find news creators with 1M+ followers" -> use `semantic_search_creators`, not this tool. Returns either autocomplete-style creator lookup results or legacy semantic results, depending on routing. Use returned creator IDs with `get_creator`, `find_lookalike_creators`, or `match_creators`; use returned platform usernames with `get_profile` or `get_posts`.

  ConnectorNo auth

• get_creatorA

  Influship Influencer Marketing MCPA

  Fetch the full record for a single creator by ID or exact platform username. Use this when you already have either: - a canonical creator UUID returned by `search_creators`, `semantic_search_creators`, `autocomplete_creators`, or `find_lookalike_creators`; or - an exact platform+username pair such as platform "instagram" and username "niickjackson". Pass `include: ['profiles']` to also receive the creator's social profile summaries when using a creator UUID. For platform+username inputs, this tool resolves through the profile endpoint and returns the profile record plus the underlying creator record, so you already get the matched profile context. Examples: - User: "Get creator 123e4567-e89b-12d3-a456-426614174000" -> call with id. - User: "Get @niickjackson on Instagram" -> call with platform "instagram" and username "niickjackson", or use `get_profile` if profile metrics are the main need. - User: "Tell me about @niickjackson and include his profiles" -> use platform "instagram" and username "niickjackson"; then use `get_profile`/`get_posts` for platform-specific metrics and content if needed. Use `lookup_profiles` for batch exact profile lookups.

  ConnectorNo auth

• sandbox_backtestA

  dMoERA CreatorB

  Run a sandbox backtest of strategy code without persisting anything. This is the fastest way to test a strategy. The code is run through static checks and a full backtest on historical data, but no Strategy or StrategyVersion rows are created. Use this for rapid iteration. Args: code: Python source code implementing the Strategy contract. Must define a METADATA dict and a class extending Strategy with an on_bar(ctx) -> Signal method. See CREATOR_API.md. domain: Trading domain (e.g. "eth_usdc", "btc_usdc", "sol_usdc"). symbol: Price symbol for historical data (e.g. "ETHUSDT"). user_id: Identifier for trial tracking (used for DSR correction). Returns JSON with: success, metrics (sharpe, sortino, win_rate, total_trades, return_bps, max_drawdown, regime_breakdown, exit_reason_breakdown), or error details if validation failed.

  ConnectorNo auth

• analyze_citation_trendA

  VantageA

  Track how a domain's AI-citation count has moved month over month, so you can see whether visibility is growing or fading instead of only ever checking a single point in time. Use this to answer 'is our AI visibility improving' or 'did that content push actually move the needle'. Read-only: no side effects, safe to retry. Costs 1 quota unit/call (free tier is 30 units/month shared across every metered tool, so up to 30 calls to this tool alone if nothing else is used that period). Returns: {"domain", "platform", "months" (list of {"year", "month", "mentions" (int, 0 for a month with no tracked citations. A zero between two large months can be a gap in the provider's history rather than a real drop, so read isolated zeros with care), "ai_search_volume"}, oldest to newest), "trend": {"direction" ("up"/"down"/"flat"/"no_data"), "earliest_mentions", "latest_mentions", "excluded_current_partial_month" (bool, only present and true when the most recent calendar month was excluded from the trend calculation because it is still in progress and its count is not yet final - it is still returned inside `months`, just not compared)}}. The most recent entry in `months` (or `trend.latest_mentions` when the current month is not excluded) already IS the current count, so there is no need for a separate call just to see it right now. Args: domain: bare domain to check, e.g. "example.com" (no https://, no www). platform: "chat_gpt" or "google" (Google's AI Overview). Defaults to chat_gpt. Perplexity and Gemini aren't available - the underlying data provider doesn't cover them for this check. months: how many recent months of history to return. Defaults to 6, capped at 13 - DataForSEO's historical data only goes back to 2025-08-01. country: market to check, e.g. "Italy". Defaults to "United States". chat_gpt only has data for the United States; use platform "google" for any other country. language: language code, e.g. "it". Defaults to "en" (the only option for chat_gpt).

  ConnectorAPI key

• sti_get_platformsA

  Stimulsoft Documentation MCP ServerA

  List every Stimulsoft product/platform that has indexed documentation available through this MCP server. Returns a JSON array of { id, name, description } objects covering the full Stimulsoft Reports & Dashboards product line (Reports.NET, Reports.WPF, Reports.AVALONIA, Reports.WEB for ASP.NET, Reports.BLAZOR, Reports.ANGULAR, Reports.REACT, Reports.JS, Reports.PHP, Reports.JAVA, Reports.PYTHON, Server API, etc.). CALL THIS FIRST when the user's question is ambiguous about which Stimulsoft platform they are using, or when you need to pick a valid `platform` value to pass into `sti_search`. The returned platform `id` values are the exact strings accepted by the `platform` parameter of `sti_search`. This tool is cheap (no OpenAI call, no vector search) — call it freely whenever you are unsure about platform naming.

  ConnectorNo auth

• epss_timeseriesA

  ZEN SecDBA

  Get the historical EPSS time series for a specific CVE. ## What this tool does Returns the historical EPSS score, percentile, and model version available for a CVE across time, ordered by date. Useful for analyzing how exploitability likelihood has evolved over time. ## When to use this tool Use this tool when the user asks about: - EPSS trend over time - how exploitability probability changed - whether EPSS spiked or dropped - historical comparison of risk If the user only wants the current EPSS score, use `vulnerability_score` instead. ## Inputs - **cve_id**: valid CVE identifier (`CVE-YYYY-NNNNN`). ## Outputs - **series**: array of objects, each containing: - `date`: measurement date in ISO format - `score`: EPSS score - `percentile`: EPSS percentile - `model`: EPSS model version ## LLM usage guidelines - Never guess EPSS values-use this tool for all EPSS time-series questions. - If `cve_id` is malformed or incomplete, ask the user to correct it before calling. - If the user mentions multiple CVEs, call the tool once per CVE as needed. - If no historical data is available, return an empty series and state that no EPSS history was found.

  ConnectorNo auth

• get_profileA

  InflushipA

  Fetch a single social profile by (platform, username). Always use this first when the user gives an exact handle on a specific platform (for example "@niickjackson on Instagram") and you need the full profile: bio, follower/engagement metrics, recent activity, growth, and the canonical creator ID. Pass exactly the username they typed without the @ sign — case-insensitive matching is handled server-side. Do not use `search_creators` for an exact platform+username lookup. Examples: - User: "Pull @niickjackson on Instagram" -> use this tool with platform "instagram" and username "niickjackson". - User: "Tell me about instagram.com/niickjackson" -> parse the platform and username, then use this tool. - User: "Is @niickjackson a fit for Pixel?" -> use this tool first, then call `get_posts` and/or `match_creators` if the task needs content or fit analysis. Returns the profile record plus the underlying creator record. If you already have a creator UUID, use `get_creator` instead. For batch lookups by handle, use `lookup_profiles`.

  ConnectorNo auth

• secedgar_get_financialsA

  secedgar-mcp-serverA

  Get historical XBRL financial data for a company. Accepts friendly concept names (e.g., "revenue", "net_income", "assets") or raw XBRL tags. Discover available friendly names with secedgar_search_concepts. Handles historical tag changes and deduplicates data automatically. The full series is also staged as df_<id> when a canvas is available — inspect it with secedgar_dataframe_describe, then analyze it with secedgar_dataframe_query.

  ConnectorNo auth

• get_profileA

  Influship Influencer Marketing MCPA

  Fetch a single social profile by (platform, username). Always use this first when the user gives an exact handle on a specific platform (for example "@niickjackson on Instagram") and you need the full profile: bio, follower/engagement metrics, recent activity, growth, and the canonical creator ID. Pass exactly the username they typed without the @ sign — case-insensitive matching is handled server-side. Do not use `search_creators` for an exact platform+username lookup. Examples: - User: "Pull @niickjackson on Instagram" -> use this tool with platform "instagram" and username "niickjackson". - User: "Tell me about instagram.com/niickjackson" -> parse the platform and username, then use this tool. - User: "Is @niickjackson a fit for Pixel?" -> use this tool first, then call `get_posts` and/or `match_creators` if the task needs content or fit analysis. Returns the profile record plus the underlying creator record. If you already have a creator UUID, use `get_creator` instead. For batch lookups by handle, use `lookup_profiles`.

  ConnectorNo auth

• sti_get_platformsA

  docsA

  List every Stimulsoft product/platform that has indexed documentation available through this MCP server. Returns a JSON array of { id, name, description } objects covering the full Stimulsoft Reports & Dashboards product line (Reports.NET, Reports.WPF, Reports.AVALONIA, Reports.WEB for ASP.NET, Reports.BLAZOR, Reports.ANGULAR, Reports.REACT, Reports.JS, Reports.PHP, Reports.JAVA, Reports.PYTHON, Server API, etc.). CALL THIS FIRST when the user's question is ambiguous about which Stimulsoft platform they are using, or when you need to pick a valid `platform` value to pass into `sti_search`. The returned platform `id` values are the exact strings accepted by the `platform` parameter of `sti_search`. This tool is cheap (no OpenAI call, no vector search) — call it freely whenever you are unsure about platform naming.

  ConnectorNo auth

• wait_for_taskA

  Agent RouterC

  Wait for a platform agent task to complete and return its result. Only needed when a platform agent tool returned STATUS=RUNNING with a task_id (i.e. the task was still running after the initial 50s inline wait). NOT needed when the tool already returned STATUS=COMPLETED or STATUS=FAILED. NOT needed for a2a_call_agent — that always returns directly. Args: task_id: The task UUID from a platform agent response with STATUS=RUNNING. max_wait_seconds: Max seconds to wait (default 45, max 300).

  ConnectorNo auth

• devtune_get_visibility_summaryA

  DevTune MCPA

  Get AI search visibility summary metrics for a project. The default aggregates only the project’s currently active platforms and returns measurement metadata; use only measurement.reportablePlatforms for current per-platform reporting. This excludes configured onboarding platforms that have no measurements in the window. measurement.dataStatus=no_data means the platform was not measured in the window, not that visibility was zero. Inactive historical data is excluded unless explicitly requested. Organic percentage fields use 0 to 100; citationPresence and shareOfVoice are null when no response has usable citation data. advertising reports separate forward-only ads detected, measuredResponses coverage, and primaryRate/competitorRate fractions from 0 to 1, null when unmeasured. Never combine advertising with organic Presence.

  ConnectorAPI key