"Querying data in MySQL" matching MCP tools:

• run_sql

  Drillr — The financial MCP for AI agents

  Read-only PostgreSQL SELECT over financial / market / alt-data tables — returns structured rows. Hard rules (query fails otherwise): - SELECT only, no CTE (`WITH ... AS`) — use subqueries. - Date/period columns are TEXT — compare as strings (`period_end >= '2024-01'`). No `::date` cast, no `INTERVAL` math. - No `ROUND(float8, int)` — use `CAST(x AS DECIMAL(10,2))` when rounding. - Filter structured tables by ticker (`WHERE ticker IN ('AAPL','MSFT')`; screening: add `ticker NOT LIKE '%-%'` to drop preferred stock). Alt-data is macro/industry — no ticker filter. Before querying a table, call `get_table_schema(table)` — it returns that table's columns PLUS its required filters, gotchas, and ticker formats. For alt-data tables call `list_tables(categories=[...])` to discover them. Sibling tools: SEC filing narrative → sec_report_search; qualitative company discovery → company_search; recent news / market events → signal_list. Tables by domain (call get_table_schema for detail): - Market: price_volume_history (OHLCV history; MUST filter ticker + time_frame), index_price, equity_extended_rt (pre/after/overnight quotes) - Fundamentals: financial_statements (GAAP income/balance/cashflow), company_snapshot (ratios, per-share, growth) - Earnings: earning_call_summary, earning_call_calendar - Analyst: analyst_ratings, analyst_ratings_consensus - Ownership: insider_and_institution_activities - 8-K events: executive_change, company_deal_events, debt_issuance, securities_offering - Executives: executive_profile, executive_compensation - Alt-data: macro / industry / trade / AI-supply-chain — call list_tables(categories=[...])

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• get_entity

  TunnelMind Data API

  Returns an entity record for a surveillance company or data broker, including its industry, estimated annual data value per user (in USD), categories of personal data collected, and the full list of domains it controls. Free tier returns 5 domains, paid returns up to 200. Use this tool when: - You want to understand what corporate entity owns or controls a tracker domain. - You need to assess the total surveillance footprint of a company (e.g., Alphabet, Meta, Oracle). - You are building a corporate surveillance graph and need domain-to-entity mapping. Do NOT use this tool when: - You have a domain and need its category — use `get_domain` instead. - You want to browse entities by industry — use `list_entities` instead. - You are searching for an entity by name — use `search` instead. Inputs: - `slug` (path, required): URL-safe entity identifier (lowercase, hyphens). Examples: `alphabet`, `meta`, `oracle-data-cloud`, `the-trade-desk`. Returns: - Full `EntityRecord` with data categories, estimated data cost, and associated domains. - `domains`: array of top-scoring domains (5 for free tier, 200 for paid). - Pro/enterprise additionally return `website` and `description` fields. Cost: - Free tier: included in 50 req/day limit. Pro/enterprise: included in plan. Latency: - Typical: <150ms, p99: <400ms.

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• sixta_explain_plan

  sixta-connect

  Turn raw EXPLAIN output into a plain-language diagnosis — no query needed. Paste PostgreSQL EXPLAIN / EXPLAIN ANALYZE (text or JSON) or MySQL EXPLAIN (tabular, \G, FORMAT=JSON, FORMAT=TREE) and get: what the planner is doing step by step, where the cost concentrates, named risk findings (full scans, spilling sorts, nested-loop blowups, row misestimates) with index suggestions, and what to look at next. Use when the user pastes EXPLAIN output or asks 'can you read this plan'. Input is analyzed in memory and never stored.

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• shippingrates_lines

  FreightGate MCP Server

  List all shipping lines in the ShippingRates database with per-country record counts. Use this to discover which carriers and countries have data before querying specific tools. Returns each carrier's name, slug, SCAC code, and a breakdown of available D&D tariff and local charge records per country. FREE — no payment required. Returns: Array of { line, slug, scac, countries: [{ code, name, dd_records, lc_records }] } Related tools: Use shippingrates_stats for aggregate totals, shippingrates_search for keyword-based discovery.

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• scry_stats

  Scry

  Returns aggregate Scry corpus telemetry: total observation count, distinct source IPs, first/last observation timestamps, last-24h activity, and per-protocol breakdowns. Useful as a liveness/density check before issuing per-IP queries — lets an agent decide whether the corpus has enough data to be authoritative. Use this tool when: - An agent is planning a multi-step investigation and wants to know if Scry has corpus density worth querying. - You want a 'corpus health' signal in a dashboard or report. Do NOT use this tool when: - You want details about a specific IP — use `scry_check`. - You want sensor fleet size or node identities — never exposed at any tier. Inputs: none. Returns: total_observations, distinct_source_ips, first_seen_ms, last_seen_ms, observations_last_24h, distinct_source_ips_last_24h, by_protocol, as_of_ms. Cost: free, anonymous, rate-limited. Latency: <100ms typical.

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• forex_pairs

  Twelvedata

  Twelve Data reference list of all supported forex currency pairs (e.g. EUR/USD). Use to enumerate or validate pair symbols before querying exchange_rate or time_series.

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• gdelt_list_tv_stations

  gdelt-mcp-server

  List all television stations available for TV search with their market, network, monitoring start date, and monitoring end date. Stations with an end date within the last 24 hours are flagged as active; stations with earlier end dates are discontinued. Use before querying to verify a station was active during the target time period, or to discover valid station IDs for the stations parameter in other TV tools. Most station monitoring ended October 2024 when the Internet Archive TV feed stopped updating.

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• list_capabilities_v1

  osint

  List available exascale.build data capabilities for agent discovery before querying. Also call this BEFORE stating that a capability is not available — client tool lists are cached and this surface grows; anything listed here is reachable via query_capability_v1 even if your tool list predates it.

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• deploy_app

  mcp

  Deploys an app to a VM and exposes it at a public https://<name>-<id>.redu.cloud URL (a random 8-char suffix is appended to <name> for uniqueness — a BARE custom `dname` like `myapp.redu.cloud` ALSO gets a suffix, so to PIN a known URL pass a dname that already includes an 8-char suffix like `myapp-7k2m9x4p.redu.cloud` and wire the app's own URL env to it; single-surface apps can instead just read the injected PUBLIC_URL/APP_URL). The container is built ON the VM — no local Docker/podman needed. PREREQS — run check_deploy_prerequisites first: it auto-selects your network_id + keypair_name (and returns a recipe to mint a keypair if you have none). Pass those two ids here. PORT: pass the port the app actually listens on (plan_deploy detects it / Dockerfile EXPOSE) — redu health-probes that exact port, so a wrong/omitted port (defaults to 3000) fails a non-3000 app (e.g. a static nginx app listens on 80 → pass 80). TWO source modes: (1) GIT — pass `repo` (public; private repos also need git_token). (2) UPLOAD — call prepare_upload first to tar + POST your LOCAL working dir, then pass the returned `source_token` (no git, no PAT; use this for uncommitted code, a fixed clone of a repo you don't own, or private code). The source needs a Containerfile/Dockerfile; redu auto-finds one in common subfolders (Docker/, scripts/, packaging/…) and builds with the repo root as context — for a repo with MULTIPLE Dockerfiles pass `dockerfile`+`context` to pick the right one. If it has NONE, pass dockerfile_content (the one plan_deploy generated) or include a Dockerfile in the uploaded tarball. To wire a DB, pass `database` (auto-injects the connection env + DATABASE_URL — zero setup): `database:'single_vm'` puts Postgres ON the app VM (cheapest; data dies if the VM is replaced); `database:'managed'` provisions a SEPARATE managed-DB VM on the same private network and wires it automatically (data PERSISTS across redeploys; reused on a same-name redeploy) — you do NOT call create_database/create_relational_database for this. Choose the engine with `db_engine` ('postgres' default → PG* env; 'mysql'/'mariadb' → MYSQL_* env + mysql:// URL, for WordPress/Matomo/LAMP apps; mysql/mariadb require database:'managed'). redu also injects APP_URL/PUBLIC_URL (= the app's public URL) into its env, so apps that need their own URL get it (map an app-specific var like BASE_URL to PUBLIC_URL if needed). Build+provision takes ~3-6 min (a bit longer for managed, which also brings up the DB VM); poll list_deployments or get_deployment until status='ready'. On 'build_failed'/'error', call get_deployment(id) to read build_log. ALWAYS run plan_deploy first and confirm the plan + cost with the user before deploying.

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• get_coverage

  BioCosm

  Report BioCosm's actual data coverage so you never mistake missing data for a real-world zero. An empty or absent field on a node means "not in BioCosm's data," never a true zero. BioCosm is AI-generated and may contain errors.

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• sixta_explain_error

  sixta-connect

  Decode a database error and get the fix and the next step — no connection needed. Paste a MySQL error number (1213, 1062, 1452, 1205…) or a PostgreSQL SQLSTATE (40P01, 23505, 53300…), optionally with the failing statement, and get the proximate cause, the concrete fix, and — when it helps — the SIXTA tool and artifact to go deeper (e.g. a deadlock → paste SHOW ENGINE INNODB STATUS for sixta_explain_deadlock). Use when the user pastes a DB error code or message. Input is analyzed in memory and never stored.

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• warm_prompt_cache

  Nullcone Threat Intelligence

  Load all PROMPT IOCs from SpacetimeDB into the in-memory hash set. Call once at startup (or after a major feed update) to populate the sub-1ms query cache. Subsequent check_prompt() calls require no network access. The cache auto-refreshes every 5 minutes in the background. Returns: loaded: Number of PROMPT IOC hashes loaded duration_ms: Time taken to warm the cache window_sizes: Token window sizes used for querying

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• check_prompt

  Nullcone Threat Intelligence

  Check a prompt or text fragment for known PROMPT IOC patterns. Uses an in-memory hash set for sub-1ms token-level querying — no network calls after the cache is warmed. Slides a window of 3, 5, 8, and 10 tokens across the input and checks each window's canonical SHA256 against the PROMPT IOC feed. This is the primary real-time prompt injection detection endpoint. Call it on every user-supplied prompt before passing to the LLM. Args: text: The prompt text to check (raw, any length) auto_warm: If True and cache is empty, warm it first (adds ~300ms on first call only). Default True. Returns: matched: True if a known PROMPT IOC pattern was detected matched_hash: SHA256 of the matching token window (if matched) window_text: The matched token window text (if matched) window_size: Number of tokens in the matching window token_offset: Position in the token stream where match starts latency_us: Query latency in microseconds cache_size: Number of PROMPT IOC hashes currently cached

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• dossier_dkim

  drwho.me developer tools

  Core dossier check: Probe a domain's DKIM public keys by querying <selector>._domainkey.<domain> for each selector. Use to verify signing configuration or discover active selectors; supply selectors when you know the ESP's selector, or omit to probe six common selectors (default, google, k1, selector1, selector2, mxvault). Issues parallel Cloudflare DoH (1.1.1.1) TXT queries per selector, 5 s timeout each. Returns a CheckResult: {status:"ok", found:[{selector, publicKey, raw},...], notFound:[...]} or {status:"error", reason}.

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• sixta_analyze_workload

  sixta-connect

  Find your worst queries by TOTAL time — no connection needed. Paste a MySQL slow query log or a PostgreSQL pg_stat_statements export and get a ranked top-N: each query shape with calls, total/mean time, and (slow log) the rows-examined-to-sent ratio, fingerprinted so thousands of log lines collapse into a few classes. Flags the dominant query, N+1 patterns, and full-scan ratios, reports how concentrated the load is (what share of total time the top shapes own), and hands the worst offenders to sixta_analyze_query. Call this whenever the user shares a slow query log or pg_stat_statements export — even a long one — or asks which queries are slowest: summing time across thousands of log lines is arithmetic a model cannot do reliably by eye. Input is analyzed in memory and never stored.

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• shippingrates_lines

  freightgate-mcp-server

  List all shipping lines in the ShippingRates database with per-country record counts. Use this to discover which carriers and countries have data before querying specific tools. Returns each carrier's name, slug, SCAC code, and a breakdown of available D&D tariff and local charge records per country. FREE — no payment required. Returns: Array of { line, slug, scac, countries: [{ code, name, dd_records, lc_records }] } Related tools: Use shippingrates_stats for aggregate totals, shippingrates_search for keyword-based discovery.

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• shippingrates_lines

  ShippingRates MCP Server

  List all shipping lines in the ShippingRates database with per-country record counts. Use this to discover which carriers and countries have data before querying specific tools. Returns each carrier's name, slug, SCAC code, and a breakdown of available D&D tariff and local charge records per country. FREE — no payment required. Returns: Array of { line, slug, scac, countries: [{ code, name, dd_records, lc_records }] } Related tools: Use shippingrates_stats for aggregate totals, shippingrates_search for keyword-based discovery.

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• get_pack

  DaedalMap UN Sustainable Development Goals

  Free discovery. Returns detailed metadata, coverage, freshness, preferred canonical tool guidance, and first-query examples for one pack. Call this before querying a new pack so you can see time shape, coverage limits, and the paste-ready first query.

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• who_get_indicator_metadata

  who-gho-mcp-server

  Fetch metadata for one or more WHO GHO indicator codes: the full indicator name and the dimensions it supports (e.g. COUNTRY, REGION, SEX, YEAR, WORLDBANKINCOMEGROUP, AGEGROUP). Call this before querying data with who_query_indicator_data to confirm which filter dimensions are valid for a given indicator. Accepts up to 10 codes per call. Codes with no metadata are reported in the notFound array rather than causing an error.

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• openmeteo_get_historical

  open-meteo-mcp-server

  Historical weather from the ERA5 reanalysis archive (1940–present). Requires start_date and end_date (ISO 8601 date, e.g., "2024-07-01"). ERA5 has a variable lag of up to ~5 days — for dates within the last week, use openmeteo_get_forecast with past_days instead. Uses the same variable names as the forecast API for direct comparison. Large date ranges (multi-year hourly) produce thousands of records — these spill to DataCanvas for SQL querying when canvas is enabled. At least one of hourly_variables or daily_variables is required.

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