"Techniques for Analyzing and Interacting with Large MS SQL Databases" matching MCP tools:

• atlas_technique_searchA

  ContrastAPIA

  Search the MITRE ATLAS catalog of AI/ML attack techniques by keyword, tactic, or maturity. Default response is SLIM (description truncated to 240 chars per row); pass include='full' for the verbose record. Pass exclude_id when chaining from atlas_technique_lookup to skip self in sibling-tactic searches. Use this to discover techniques matching a threat-model question, e.g. 'what techniques target LLM serving infrastructure?'. Drill into atlas_technique_lookup with any returned technique_id for the full description, ATT&CK bridge, and pivot hints. For broader cross-referencing: when a result has attack_reference_id, that bridges to D3FEND mitigations via d3fend_defense_for_attack. Free: 30/hr, Pro: 500/hr. Returns {query (echoed filters), total, results [{technique_id, name, description (truncated by default), tactics, inherited_tactics, maturity, attack_reference_id, subtechnique_of}], next_calls}.

  ConnectorNo auth

• getInstagramPostInteractingUsersA

  Social Media Search API — Twitter, Instagram, Reddit, TikTok (XPOZ)A

  Get USER PROFILES of people who interacted with an Instagram post. Returns full user data (bio, followerCount, followingCount, etc.). RETURNS USER PROFILES: id, username, fullName, biography, followerCount, followingCount, isVerified, profilePicUrl. Use for analyzing WHO engaged with a post. NOT FOR COMMENT TEXT: To read the actual comment content (what people wrote), use getInstagramCommentsByPostId instead. INTERACTION TYPES: "commenters" (users who commented), "likers" (users who liked). WHEN TO USE THIS TOOL: Analyzing commenters/likers demographics, finding influencers who engaged, building audience profiles, network analysis of who interacts with posts. WHEN TO USE getInstagramCommentsByPostId: Reading comment text, sentiment analysis of what was said, analyzing discussion content. FAST (default, omit responseType or responseType="fast"): Returns up to 300 results directly (use limit param to reduce, e.g. limit=5). Auto API fallback for commenters when stale. PAGING (responseType="paging"): Async paginated results (1000 users per page with default fields), returns operationId - IMMEDIATELY call checkOperationStatus to get results. CSV export included via dataDumpExportOperationId. Supports pageNumber/tableName for subsequent pages. Optional fields (default: ["id", "username", "fullName"]). Available: biography, isPrivate, isVerified, followerCount, followingCount, mediaCount, profilePicUrl. This is a safe, read-only tool for analyzing searchable information.

  ConnectorOAuth

• list_databasesA

  shiplyA

  List the SQL databases (D1 or Neon Postgres) on my account, including which owned site (if any) each is attached to. Call this BEFORE db_query/db_schema-style work to discover a databaseId — those live on a per-database MCP server reached via GET /api/v1/databases/{id} (see llms.txt), which this id feeds.

  ConnectorNo auth

• scalix_db_text_to_sqlA

  Scalix CloudA

  Translate a plain-language question into a candidate SQL query using pattern-matching against the live schema (no AI model — simple questions only: counts, averages, filtered selects on a named table). Returns the SQL without executing it, with a confidence score; low confidence means the table was guessed. Review the statement and tables_used, then run it with scalix_db_query. For complex questions, read scalix_db_schema and write the SQL directly.

  ConnectorNo auth

• nowA

  x402 Checker (AI Nock)B

  Paid $0.01 USDC exact on Base: UTC clock (unix, ms, iso). No params. Alias of REST GET /now and /time. For IANA zones use tool tz. payTo 0x3903F05a17676566958B0a3E0c21E0bd49B66ea0.

  ConnectorNo auth

• fastero_run_sqlA

  FasteroB

  Run a read-only query against one of this organisation's connected databases — PostgreSQL, MySQL, SQL Server, Redshift, Snowflake, Oracle, BigQuery or Google Sheets — in that connection's own SQL dialect, and return rows. One SELECT, WITH, EXPLAIN or SHOW statement; a statement that could change data is refused. It returns at most 500 rows and about 100 KB: a larger result comes back cut, with truncated: true and totalRows, so prefer a LIMIT or an aggregate. Where a question involves a business number (revenue, churn, active users…), fastero_get_definitions holds this organisation's own expression for it.

  ConnectorAPI key

• generate_queryA

  ALM X++ MCP ServerA

  WHEN: developer needs correct X++ select or T-SQL for D365 tables with proper joins. Triggers: 'X++ select', 'generate a query', 'SQL for', 'join with', 'how to query', 'générer une requête', 'write a select statement', 'select from', 'X++ query for', 'requête X++', 'écrire une select'. Generate both X++ select statements and equivalent T-SQL queries for D365 F&O tables. Uses real field names, relations, and indexes from the knowledge base to produce correct joins. Supports: field selection, multi-table joins (auto-detects relations), WHERE filters, ORDER BY, TOP/firstonly, cross-company. Also accepts natural language descriptions like 'find all open sales orders for customer 1001 with CustTable join'. [!] For multi-table joins, call find_related_objects (or get_relation_graph if the relation index is loaded) FIRST to get the correct FK relations -- this tool will then produce accurate join conditions. [!] The generated X++ is a template -- adapt it to your custom code context before using in production. Returns side-by-side X++ and SQL with explanations.

  ConnectorNo auth

• list_databasesA

  Bitquery: Crypto & Blockchain DataA

  CATALOG of the databases raw SQL can reach — the SHOW DATABASES equivalent. For each database: what it holds, which tool runs SQL against it, how to see its tables, and which specialized tools answer the same questions without SQL. Call it before writing raw SQL against an unfamiliar database. Takes no parameters and answers instantly. trading_rt comes first: DEX trades, OHLC / volume bars, prices and supply for every trading chain over the last ~30 days — query it with execute_sql, browse it with list_tables, describe_table and search_columns. The per-chain databases (eth_api, bsc_api, matic_api, arbitrum_api, base_api, optimism_api, robinhood_api, arc_api, tron_api, solana, bitcoin, bitcoin_flow, ripple, ripple_flow, cardano, cardano_flow, altcoin, altcoin_flow - Litecoin, Dogecoin and Dash in one database, rows told apart by blockchain_id - bitcash, bitcash_flow for Bitcoin Cash, and stellar) hold transfers, calls, events, transactions and balances; browse them with chain_list_tables, chain_describe_table and chain_search_columns (pass the database name) and query each one with that chain's <chain>_transfers_raw_sql tool (xrp_, ada_, ltc_ / doge_ / dash_, bch_ and xlm_transfers_raw_sql for the ones above after bitcoin_flow). zcash and zcash_flow are queried with zec_transfers_raw_sql but the schema browser does not cover them: that tool's description lists their tables. stellar_flow is not browsable either - it starts in December 2023 and misses some ledgers, so query stellar instead. Address labels have no SQL access at all — use the label tools. Prefer a specialized tool whenever one answers the question: it already filters on the right keys and is far cheaper than hand-written SQL.

  ConnectorOAuth

• bulk_atlas_technique_lookupA

  ContrastAPIA

  Bulk ATLAS technique lookup — retrieve full records for up to 50 techniques in a single request instead of N separate atlas_technique_lookup calls. Designed as the natural follow-up to atlas_case_study_lookup, whose techniques_used array can be passed directly. Each item is the same shape as atlas_technique_lookup, including parent-tactics inheritance for sub-techniques (inherited_tactics=true flag) and per-item next_calls (D3FEND bridge when attack_reference_id present, sibling-technique search by tactic, parent lookup for sub-techniques). Free: 30/hr (1 per item), Pro: 500/hr. Returns {results [{technique_id, status (ok|not_found|invalid_format), technique, error}], total, successful, failed, partial, summary}.

  ConnectorNo auth

• transpile_sqlA

  ai-netcafeA

  Convert a SQL statement from one dialect to another — mysql, postgres, sqlite, tsql, oracle, snowflake, bigquery, redshift, spark, hive, presto, trino, duckdb, clickhouse, databricks, doris, starrocks and more. Deterministic parser (sqlglot), not an LLM: the same input always produces the same output, and syntax errors come back with the exact line and column. Use it when migrating queries between databases or debugging dialect-specific syntax.

  ConnectorNo auth

• transpile_sqlA

  AI NetCaféA

  Convert a SQL statement from one dialect to another — mysql, postgres, sqlite, tsql, oracle, snowflake, bigquery, redshift, spark, hive, presto, trino, duckdb, clickhouse, databricks, doris, starrocks and more. Deterministic parser (sqlglot), not an LLM: the same input always produces the same output, and syntax errors come back with the exact line and column. Use it when migrating queries between databases or debugging dialect-specific syntax.

  ConnectorNo auth

• transpile_sqlA

  netcafe-live-dataA

  Convert a SQL statement from one dialect to another — mysql, postgres, sqlite, tsql, oracle, snowflake, bigquery, redshift, spark, hive, presto, trino, duckdb, clickhouse, databricks, doris, starrocks and more. Deterministic parser (sqlglot), not an LLM: the same input always produces the same output, and syntax errors come back with the exact line and column. Use it when migrating queries between databases or debugging dialect-specific syntax.

  ConnectorNo auth

• transpile_sqlA

  netcafe-devkitA

  Convert a SQL statement from one dialect to another — mysql, postgres, sqlite, tsql, oracle, snowflake, bigquery, redshift, spark, hive, presto, trino, duckdb, clickhouse, databricks, doris, starrocks and more. Deterministic parser (sqlglot), not an LLM: the same input always produces the same output, and syntax errors come back with the exact line and column. Use it when migrating queries between databases or debugging dialect-specific syntax.

  ConnectorNo auth

• list_code_typesA

  MedPrice AIA

  Returns every distinct code_type (e.g. CPT, MS-DRG) with catalogued cost data, along with each type's distinct code count and total hospital reports. Unpaginated. Use this to discover which code systems have data before drilling into list_codes.

  ConnectorNo auth

• run_terminalA

  ReMCPA

  Use this when the task needs a shell command or an existing ReMCP terminal session: start, read, wait, interact, stop, or list sessions. Choose exactly one operation; parameters are validated against that operation’s closed schema. Starting or interacting with commands can change local or external state, and force termination can lose unsaved process work; reading, waiting, and listing do not mutate the session. Use manage_system for OS-wide process inventory or killing an arbitrary PID.

  Connector

  Destructive

  OAuth

• execute_sqlA

  HostingFor.AIA

  PHP + MySQL plans: runs one SQL statement that can change the site's database (CREATE/ALTER/DROP TABLE, INSERT, UPDATE, DELETE, …). Changes are permanent: confirm destructive changes (DROP, DELETE, TRUNCATE, large UPDATEs) with the user first. Use ? placeholders with params for values. One statement per call; 30-second limit.

  Connector

  Destructive

  OAuth

• describe_tableA

  Bitquery: Crypto & Blockchain DataA

  COLUMNS of one trading_rt table — what columns a table has (e.g. the trades tables), the DESCRIBE TABLE equivalent: exact column name (case-sensitive), type, default kind and expression, comment, and whether the column is part of the sort key (filter on those first) or the partition key. Call it before writing SQL for execute_sql: guessed or lower-cased column names fail with "Missing columns". `table` is a name from list_tables, e.g. trades_by_token_address, trades_by_trader_address, tokens_by_address; a "trading_rt." prefix is accepted. An EMPTY result means trading_rt has no such table — call list_tables. To find which table carries a column, use search_columns. Only trading_rt can be described here; tables of the per-chain databases (eth_api, solana, bitcoin, …) are described with chain_describe_table.

  ConnectorOAuth

• list_tablesA

  Bitquery: Crypto & Blockchain DataA

  TABLES of the trading_rt database — the SHOW TABLES equivalent — with each table's engine, sort key, partition key and approximate row count. Returns up to 500 tables, sorted by name; narrow them with like (e.g. "by_token"). It reads table metadata only, never table data. The sort key is what makes raw SQL fast: filter on its LEADING columns first; a query that skips them scans far more data. trading_rt holds DEX trades, OHLC / volume bars, prices and supply of the last ~30 days for every trading chain; query it with execute_sql, and prefer a specialized tool (find_tokens, token_price, token_ohlcv, top_traders_by_token, trader_positions, …) whenever one answers the question. Next steps: describe_table for one table's columns, search_columns to find which table has a column. Only trading_rt can be listed here. The per-chain transfer databases (eth_api, bsc_api, solana, bitcoin, …) are listed with chain_list_tables; list_databases describes them all. Each row: Database, Table, Engine, Sorting_Key, Partition_Key, Total_Rows.

  ConnectorOAuth

• sixta_quickstartA

  sixta-connectA

  Show a complete SIXTA analysis on a realistic sample (a gnarly production query plus its EXPLAIN output) for PostgreSQL or MySQL — no input needed. Offer this to first-time or empty-handed users who want to see what SIXTA finds before pasting their own SQL. Not for analyzing real artifacts — use the analysis tools for those.

  ConnectorOAuth

• accessibility_matrixA

  Colour MemoryA

  Accept a palette array and return every foreground/background combination with contrast ratio, AA normal, AA large, AAA normal, AAA large pass/fail grades, and a summary. Use this instead of calling accessibility_check multiple times for a palette.

  ConnectorNo auth

• vector_statsA

  IA-QA — 130+ QA & Dev Tools for AI AgentsB

  Compute statistics for a float vector or matrix of vectors: mean, std, L2 norm, min, max, sparsity, top-K indices. Useful for debugging embedding quality and analyzing vector distributions in a vector DB.

  ConnectorNo auth